Digital Disruption with Geoff Nielson

Is AI consciousness already here and can we reclaim our technological optimism? Google’s Blaise Agüera y Arcas shares why he believes AGI has already arrived and what AI can teach us about consciousness, cooperation, and the human mind. Blaise joins us on this episode of Digital Disruption to talk about AI consciousness, large language models, and why intelligence is inherently social. He explains how AI agent swarms work together, what recursive self-improvement looks like today, and why he questions the idea that smarter machines will inevitably dominate humanity. He questions why we find it easier to imagine catastrophe than a better future. And this conversation examines how negative news shapes our expectations of AI, and why taking its risks seriously can coexist with optimism about its potential. From AI alignment and mass surveillance to jobs and economic inequality, Blaise considers whether our institutions are ready for the changes ahead. He shares how AI could accelerate progress in medicine, robotics, and climate solutions, while emphasizing the work needed to turn those possibilities into reality. This episode asks an important question: As AI becomes more capable, how do we make sure the benefits reach everyone? Follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 Intro 02:12 Rethinking artificial intelligence 04:35 Can technology be considered alive? 06:13 What does it mean for AI to be conscious? 08:23 Multi-agent systems and the role of self-awareness 11:48 Could AI have a subjective experience? 17:49 What split-brain experiments reveal about consciousness 20:49 Building your AI strategy with Infotech 21:56 The Self: One mind or many parts? 23:38 How LLMs differ from human minds 28:19 Octopus intelligence, AI agent swarms, and identity 32:52 Why Human Intelligence Is Collective 38:19 Why Blaise believes AGI is already here 43:59 Multi-agent AI and the next frontier of intelligence 47:25 Recursive self-improvement and the singularity 50:41 AI coding agents and the risks of faster automation 54:18 AI Alignment: whose values should AI follow? 58:20 Will smarter AI dominate humanity? 1:01:42 Mass surveillance, power, and human disempowerment 1:04:09 AI breakthroughs in medicine, robotics, and space 1:08:12 Why are we so pessimistic about the future? 1:11:29 Why AI doom gets more clicks 1:13:16 Taking AI researchers’ fears seriously 1:16:42 Nostalgia and the accelerating pace of change 1:21:08 Is our economy ready for AI? 1:24:07 AI, job loss, and the fear of losing income 1:26:36 What should leaders and society do next? 1:29:23 AI, climate change, and clean energy 1:31:06 Moving AI computing into space 1:31:42 Final thoughts 1:32:06 About Infotech Connect with Blaise: LinkedIn: https://www.linkedin.com/in/blaise-ag%C3%BCera-y-arcas-85626a42/ X: https://x.com/blaiseaguera IG: https://www.instagram.com/blaiseaguera Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Predictive AI often gets ignored, yet it may hold the real key to business value in the current tech landscape. Machine learning expert Eric Siegel, author of The AI Playbook and Predictive Analytics, joins the Digital Disruption podcast to explain why organizations should invest at least as much in predictive AI as they do in generative AI. He breaks down how predictive AI can improve real-world operations, why so many AI pilots fail to reach deployment, and where the promise of autonomous AI agents encounters reliability challenges. While generative AI captures the headlines, Eric argues that more dependable returns often come from systems that predict outcomes and improve decision-making. The conversation explores the differences between predictive and generative AI, why meaningful business value comes from deployment rather than impressive demos, and the limitations of fully autonomous AI agents and artificial general intelligence. Tune in to learn how predictive AI could make generative AI more reliable, why business leaders and data scientists need to work together, and whether AI will really cause a job apocalypse. Like and follow for more conversations on AI, technology, innovation, the future of work, and digital transformation. 00:00 Why businesses may be investing in the wrong AI 00:47 Predictive AI vs. generative AI 03:01 How large language models fit into predictive AI 06:59 What kind of AI is solving real-world problems? 08:06 The two “wows” of AI: Impressive demos vs. deployment 09:28 Build your AI strategy with Info-Tech 10:37 Why predictive AI is still delivering business value 12:32 Why most AI pilots fail to reach production 16:25 AI hype and mismanaged expectations 19:31 AI agents, AGI, and the promise of autonomy 20:44 Can predictive AI make generative AI more reliable? 23:57 Why full AI autonomy remains unrealistic 26:59 Large language models vs. human intelligence 29:21 The limits and diminishing returns of AI models 31:35 What businesses are getting wrong about AI 35:35 Bridging the gap between technology and business leaders 37:18 Why leaders need a semi-technical understanding of AI 38:59 Three questions every predictive AI project must answer 42:22 Will AI replace developers and other technical roles? 49:29 Who should own AI strategy and accountability? 53:41 Is AI creating the productivity gains we were promised? 55:49 Could future technology overcome today’s AI limitations? 59:21 How organizations can unlock more value from AI 1:01:43 Eric Siegel’s six-step AI deployment framework 1:04:42 Why AI is a business improvement project, not a tech install 1:06:02 What’s new in The AI Playbook 1:09:30 Eric’s advice for business and technology leaders 1:10:46 About Info-Tech Connect with Eric: LinkedIn: https://www.linkedin.com/in/predictiveanalytics/ X: https://x.com/predictanalytic?lang=en IG: https://www.instagram.com/eric_siegel/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

The robot workforce is already here. AI-powered humanoid robots are entering factories and warehouses to address a growing labor gap, but are they filling jobs or replacing the people who do them? Peggy Johnson, CEO of Agility Robotics, joins us to talk about how Digit is moving from robotics demonstrations into real workplaces. She explains why humanoid robots could become essential to manufacturing and logistics, how AI is accelerating their capabilities, and why safety remains the biggest barrier to widespread adoption. From physical AI and labor shortages to robot fleet managers and the future of work, this episode looks beyond the fear of robot overlords to ask: how will humans and robots work together in the years ahead? Subscribe for more conversations on AI, technology, innovation, the future of work, and digital transformation. 00:00 Why humanoid robots may be essential 00:47 Peggy Johnson, CEO of Agility Robotics 01:41 Are humanoid robots creating a dystopian future? 03:43 How workers respond to robots in the workplace 05:42 Why build robots in the human form? 07:27 Will humanoid robots replace human jobs? 11:45 Why reshoring manufacturing will require robotics 14:12 Info-Tech AI strategy 14:42 What humanoid robots could do by 2032 17:35 The biggest barrier to adoption: Robot safety 19:17 Why robots in the home are still years away 22:13 How big and powerful is agility robotics’ Digit? 24:44 Can humanoid robot accidents be prevented? 28:29 Competing with Elon Musk and Tesla Optimus 30:56 What separates deployment from a robotics demo 33:37 How companies deploy humanoid robots 37:01 Which industries are adopting robotics? 39:24 Scaling production to meet demand 41:08 How AI is accelerating humanoid robotics 45:36 How digit makes decisions on the factory floor 48:52 Hardware and software upgrades for robots 50:57 What comes after agility robotics’ Digit? 53:22 Will robots eventually do everything humans can? 55:58 The future of physical AI and automation 58:13 Peggy Johnson’s advice for business and tech leaders 59:32 About Info-Tech Connect with Peggy: LinkedIn: https://www.linkedin.com/in/peggyljohnson/ X: https://x.com/agilityrobotics IG: https://www.instagram.com/agility_robotics/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What is PDoom, and why are the people building artificial intelligence willing to risk human extinction? Kevin Roose, a New York Times technology columnist, Hard Fork co-host, and author of The AGI Chronicles, shares what he learned from interviewing more than 150 people inside the world’s leading AI companies. Kevin joins us on Digital Disruption to talk about what artificial general intelligence really means and how fear, ego, rivalry, and mistrust are accelerating the race between OpenAI, Anthropic, and Google DeepMind. He also explains why AI leaders compare this moment to the Manhattan Project: if they don’t build AGI first, someone more dangerous might. Kevin also shares why he estimates a 10% chance of AI-caused extinction and discusses the private fears of AI researchers, government regulation, autonomous AI agents, and whether the AI boom is a bubble or the beginning of a profound transformation. This episode moves beyond the hype to ask an important question: If advanced AI is inevitable, how much control do we still have over what happens next? Subscribe and follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 Why AI builders fear human extinction 00:43 Inside the race to build AGI 01:24 What does AGI actually mean? 05:16 AI safety warnings or marketing hype? 07:27 The rivalries driving the AI race 08:44 Building a boardroom-ready AI strategy 09:51 The personal feuds behind AGI 10:58 AI’s Manhattan Project mindset 12:27 Is AI the new atomic bomb? 14:58 Can advanced AI be contained? 16:28 AI regulation and the global arms race 17:35 What is P(doom)? 19:54 What will force governments to act? 21:29 What AI researchers say in private 23:08 Why the public backlash is growing 26:15 Why Kevin Roose changed his mind about AI 29:42 Is advanced AI inevitable? 32:28 AGI and the point of no return 34:38 The race to automate AI research 36:23 AI and gradual human disempowerment 40:10 What happens when AI masters your skills? 42:18 Will AI liberate us or replace us? 44:18 The AI claims Kevin does not believe 46:21 Is the AI boom a financial bubble? 50:20 AI labs and economic concentration 55:08 Inside the AGI chronicles 57:07 How should people prepare for AI? 58:29 About Info-Tech #ai #futureofwork #technologypodcast #aibubble #bigtech #artificialintelligence #technology #datacenter #agi #anthropic #futureofai Connect with Kevin: LinkedIn: https://www.linkedin.com/in/kevin-roose/ X: https://x.com/kevinroose IG: https://www.instagram.com/kevinroose/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Why have the United States and China pulled so far ahead in the global technology race? Mehran Gul, author of The New Geography of Innovation, argues that the answer goes far beyond individual companies or breakthrough technologies. In this episode, we sit down with Mehran to discuss how successful innovation ecosystems are actually built, why Silicon Valley remains so difficult to replicate, and how China rapidly emerged as a global technology superpower. We also talk about why Europe and India have struggled to produce technology giants at the same scale, and how talent, capital, universities, government, and entrepreneurship shape long-term competitiveness. Mehran also breaks down the extraordinary concentration of money flowing into AI companies like OpenAI, Anthropic, and Nvidia, whether today’s AI valuations are sustainable, and why a major market correction could still happen without ending America’s technological dominance. From AI investment and venture capital to Silicon Valley, China, Europe, India, and the future of global innovation, this episode looks beyond the AI hype to ask a much bigger question: who will actually shape the next era of technology? Subscribe and follow for more conversations with the world’s leading thinkers on AI, technology, innovation, and digital transformation. In this episode: 00:00 The AI bubble and America’s technology lead 01:47 The new geography of innovation 05:30 How China became a technology superpower 09:13 Can other countries replicate China’s success? 13:17 What does “innovation” actually mean? 16:21 Are tech valuations measuring real innovation? 21:03 Does geography determine who wins in technology? 25:01 Will the U.S. and China dominate the next decade? 29:31 Why Europe’s push for tech sovereignty is struggling 33:05 Can government policy actually create innovation? 37:24 PayPal vs. Skype: How innovation creates more innovation 39:47 Is America’s technology dominance a zero-sum game? 43:52 Who is the world’s third-largest technology power? 45:07 Why “indispensability” may matter more than tech sovereignty 47:00 What This global tech race means for business leaders 48:32 Why AI investment is becoming more concentrated 51:29 Are we betting too much on a few tech leaders? 53:35 What Japan’s collapse can teach us about U.S. tech 56:13 Could the AI bubble actually burst? 59:22 Could China overtake the U.S. in Technology? 1:03:29 When government helps and hurts innovation 1:05:51 Predictions for the next era of global technology 1:07:50 Do We need to redefine innovation? 1:10:02 Where business leaders should look for innovation 1:14:02 Why venture capital isn’t actually global 1:18:00 Final thoughts 1:19:41 About Info-Tech Research Group Connect with Mehran: LinkedIn: https://www.linkedin.com/in/mehrangul?originalSubdomain=ch X: https://x.com/mehrangul_ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we in an AI bubble? Veteran Silicon Valley investor Bill Reichert says yes, but that doesn’t mean the AI revolution is slowing down. In this episode we sit down with Bill Reichert, General Partner at Pegasus Ventures, to discuss the unprecedented investment pouring into AI, why many AI startups will fail, and where the next wave of innovation could emerge. This conversation highlights everything from data centers and quantum computing to China’s growing technology ecosystem and what businesses need to do to innovate and compete. Bill also shares his “Yellow Jacket Paradox,” raising a bigger question about the future of AI: If biological intelligence can accomplish so much with so little energy, could a fundamentally new AI architecture eventually disrupt today’s LLMs, data centers, and AI leaders? Subscribe and follow for more conversations with the world’s leading thinkers on AI, technology, innovation, and digital transformation. In this episode: 00:00 The AI bubble is here 01:02 Why this tech cycle is different 03:30 Is AI growth sustainable? 04:18 Why most AI startups will fail 06:11 What separates AI winners from the hype 09:08 The “unfair advantage” in AI 10:59 Where is the next big AI opportunity? 13:16 Investing beyond generative AI 18:13 Why AI is becoming a commodity 19:05 The data center and energy opportunity 20:17 How AI is transforming every industry 22:23 Is AI changing venture capital? 26:13 Does more investment create better technology? 29:01 China, the US, and the global innovation race 34:28 The race for quantum computing 36:51 Is China really just copying the west? 40:06 Why big companies struggle to innovate 45:54 Startups as corporate innovation labs 47:29 How to spot an overhyped tech vendor 49:13 Why companies need to test before they invest 51:04 Why innovation pilots fail 52:49 Escaping “pilot hell” 54:54 Will the pace of innovation ever slow down? 57:30 How AI changes the future of work 59:48 Does AI mean we’ll have to work harder? 01:03:06 The leadership mistake that causes burnout 01:06:08 Control vs. unlimited growth 01:07:12 The “Yellow Jacket Paradox” 01:09:29 Why today’s AI architecture may be wrong 01:11:13 Will today’s data centers become obsolete? 01:13:38 The price of innovation 01:14:08 Closing thoughts Connect with Bill: LinkedIn: https://www.linkedin.com/in/billreichert/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Hany Farid, one of the world’s leading experts on deepfakes and digital forensics, joins us to explain why AI-generated content is pushing us toward a world where we can no longer trust what we see, hear, or even who we’re talking to online. From AI-generated misinformation and social media manipulation to voice cloning, deepfake video calls, and North Korean IT workers infiltrating major companies, Hany breaks down how rapidly the threat landscape is evolving. He explains why humans are not good at detecting deepfakes, how digital forensics experts actually identify manipulated media, and why organizations need to rethink cybersecurity, remote hiring, and digital identity. This episode also dives into Big Tech’s role in the crisis, whether regulation and liability can make technology safer, the growing influence of large language models on how we access information, and what it will take to rebuild trust online. Despite the risks, Hany remains optimistic about AI’s potential. The challenge, he argues, is learning from the mistakes of the social media era and finding a way to harness AI’s power without sacrificing safety, security, and trust. Subscribe and like this video for more conversations with the world's leading thinkers on AI, technology, innovation, and digital transformation. In this video: 00:00 North Korean IT workers are already inside companies 00:41 Welcome to a “trust no one” digital world 01:49 How much of the internet is already fake? 04:59 Are we heading toward the dead internet? 07:06 What happens when we can’t agree on facts? 08:20 The existential threat of a post-truth world 09:49 Could AI control the information we see? 11:33 Who is manipulating us online? 13:20 How AI is supercharging scams and fraud 15:41 Why you can’t reliably detect a Deepfake 17:28 Should Big Tech be held liable? 19:37 Hany’s Advice: Get social media off your phone 21:26 Can liability force Big Tech to change? 24:25 Should kids be banned from social media? 25:37 The real problem with social media’s business model 28:08 Will Big Tech control the future of AI? 31:20 “China will beat us” and the case against AI regulation 33:31 How experts actually detect deepfakes 36:16 How real-time face swap deepfakes work 39:39 The Deepfake threat facing businesses 40:25 AI fraud is already costing companies millions 41:47 How fake workers get hired 42:49 Why voice biometrics are no longer secure #ai #futureofwork #technologypodcast #cybersecurity #deepfakes #digitaltrust #bigtech #aivoice #digitaltransformation #futureofjobs #futureofai #tedtalk Connect with Hany: LinkedIn: https://www.linkedin.com/in/hany-farid-40a97935/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Claire Stapleton spent 12 years at Google, going from one of the company's biggest believers to one of its most prominent employee organizers. In this episode, former Google communications leader, Google Walkout organizer, and Don’t Be Evil author Claire Stapleton reveals what happened inside Google as its celebrated culture of openness, employee empowerment, and idealism began to change. She takes us inside Google’s transformation from a company that believed people were at the heart of its success to a Big Tech giant grappling with bureaucracy, employee distrust, workplace activism, and questions about its values. She explains what led thousands of Google employees to walk out in protest, what happened after employees challenged leadership, and why speaking up inside powerful organizations can come with serious consequences. We also talk about AI and the future of work, tech layoffs, corporate culture, employee activism, leadership, workplace ethics, the changing relationship between employers and employees, and why the sweeping promises coming from today’s AI companies remind Stapleton of Google’s early years. As companies once again compete for elite technology talent while promising to change the world, could Silicon Valley be repeating the same cycle? Subscribe and like this video for more conversations with the world's leading thinkers on AI, technology, innovation, leadership, and digital transformation. In this video: 00:00 Intro 00:10 How Google’s culture changed 01:33 Claire Stapleton’s 12 years at Google 06:14 Inside Google’s early “change the world” culture 10:50 Shift in language 11:28 What happened to Google? 18:42 The events that led to the Google Walkout 25:31 Organizing the historic Google Walkout 28:59 How Google responded to employee activism 35:16 Would Claire organize the Walkout again? 39:19 The danger of tying your identity to your employer 44:29 What should you do when your employer violates your values? 50:35 Did Silicon Valley lose its people-first culture? 51:38 Are today’s AI companies repeating Google’s mistakes? 55:03 Why being people-first is good for business 56:05 What Google’s leadership got wrong 01:00:09 Why women led the resistance inside Google 01:01:48 The role of men and allies in workplace activism 01:05:58 Why women take on more unpaid work 01:08:19 How leaders can build a better workplace culture 01:11:23 Closing thoughts #futurofwork #google #workplaceculture #leadership #bigtech #aiandjobs #siliconvalley #techleadership #techlayoffs #techpodcast Connect with Claire: LinkedIn: https://www.linkedin.com/in/claire-stapleton-868a935 X: https://x.com/clairewaves Facebook: https://www.instagram.com/clairewaves/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Data center economics are coming under increasing scrutiny. Learn why power constraints could signal a major market correction and why the future of artificial intelligence may depend less on software and more on power grids, data centers, semiconductor chips, and the physical infrastructure powering AI. In this episode, TDK Ventures Investment Director Ankur Saxena joins Geoff Nielson to talk about the economics driving today's AI race. From Nvidia GPUs and hyperscaler spending to semiconductor shortages, AI infrastructure, robotics, edge AI, and quantum computing, Ankur explains why the biggest challenges facing AI aren't just technical, they're economic, physical, and increasingly difficult to ignore. This conversation examines whether today's AI investment boom is sustainable, what could trigger the next wave of market corrections, and where the greatest opportunities lie for investors, startups, and technology leaders. If you're wondering where AI is really headed and what it means for business leaders, investors, CIOs, and the future of technology, this episode is for you. In this episode: 00:00 Intro 00:20 AI's biggest problem isn't software, it's infrastructure 01:37 Ankur Saxena on the future of AI & why he's optimistic 03:20 Is the AI investment boom becoming a bubble? 07:40 AI prototyping for enterprise leaders 08:50 The AI Gold Rush: Are investors chasing hype? 10:17 Why AI infrastructure economics matter more than ever 12:09 The hidden bottleneck: Power, data centers & AI growth 15:45 AI data centers explained 19:53 Supply, demand & what happens when AI gets expensive 21:03 Why AI demand isn't slowing down anytime soon 26:33 Should every enterprise care about AI infrastructure? 27:15 Why most companies aren't ready for AI compute 32:08 The next billion-dollar opportunity: AI infrastructure orchestration 34:22 Where smart investors are looking beyond AI applications 37:35 Edge AI explained: Why AI is moving onto devices 40:43 Why AI chips need hardware & software co-design 44:18 The race to build the operating system for Edge AI 48:33 Self-driving cars, robots & the future of physical AI 52:08 Quantum computing: Beyond the hype 55:25 Quantum computing investment opportunities & "picks and shovels" 58:44 Practical AI advice for CIOs, business leaders & enterprises 1:02:02 Will AI replace humans? The future of human-AI collaboration 1:04:42 Final thoughts Connect with Ankur: LinkedIn: https://www.linkedin.com/in/saxenaankur/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Robin Hanson believes the future of AI is far stranger than most people imagine. In this episode, economist, futurist, and The Age of Em author Robin Hanson explains one of the biggest questions humanity has faced: What happens after humans? Instead of viewing AI as humanity's greatest threat, Hanson argues we should think of AI as our descendants. The conversation looks at why AI replacing humans may be part of civilization's natural evolution, why capitalism and competition aren't disappearing, and how cultural evolution, not technology, may be humanity's biggest existential challenge. We also examine the Great Filter, the future of work, AI regulation, software engineering, technological progress, fertility decline, civilization collapse, AI governance, and why Robin believes our greatest risk isn't AI taking over, but humanity losing its ability to evolve culturally. If you're interested in the future of AI, artificial intelligence, AGI, economics, civilization, technology, and what comes after humanity, this conversation will challenge many of your assumptions. Subscribe and like this video for more conversations with the world's leading thinkers on AI, technology, innovation, and digital transformation. In this episode: 00:00 Intro 01:00 AI will eventually replace humanity 01:36 Robin Hanson’s background 02:20 The future of civilization 03:22 The Age of Em explained 06:03 Why brain emulation changes everything 07:24 Capitalism isn't going away 11:18 Is humanity actually progressing? 13:10 The Great Filter explained 18:17 Why AI isn't the Great Filter 22:02 AI, technological acceleration & the next 20 years 24:24 Will AI leave people behind? 29:04 How to survive technological disruption 33:08 Why AI is humanity's descendants 40:23 Cultural evolution is breaking 47:12 Why civilization is becoming maladaptive 55:06 Is modern society quietly declining? 01:00:45 Can AI solve civilization's biggest problem? 01:07:01 AI risk vs AI progress 01:12:00 Should AI be regulated? 01:17:03 The US, China & the AI race 01:22:26 AI's economic impact 01:25:19 Advice for business leaders 01:30:45 AI's biggest opportunity for humanity 01:38:48 What gives Robin Hanson hope 01:42:24 Final thoughts Connect with Robin: X: https://x.com/robinhanson Facebook: https://www.facebook.com/robin.hanson.754/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Is AI actually making work better? Discover why many employees are feeling more constrained by machines instead of being empowered by them. In this episode, Financial Times journalist and author Sarah O'Connor joins Geoff Nielson to talk about the reality of AI in the workplace, challenging the common belief that automation will free us from repetitive work. Drawing from her new book, “We Are Not Machines,” and months of reporting inside Amazon warehouses, Swedish mines, hospitals, translation agencies, and software teams, Sarah explains how AI isn't just eliminating jobs, it is reshaping them in ways that can either empower people or reduce them to "human robots." The conversation breaks down why the promise of AI creating more time for creative, meaningful work hasn't become reality for many employees. Instead, many workers feel like they're being managed by software, algorithms, and increasingly automated systems. If you're wondering how AI will transform your career, your organization, or the future of work, this episode is for you. In this episode: 00:00 Intro 01:17 The surprising truth about AI and work 02:31 Why AI predictions are missing the real story 06:10 What Sarah discovered on the front lines of automation 07:54 Inside Amazon's robot-powered warehouses 13:25 How AI transformed professional translators 18:07 About Info-Tech Research Group 19:06 Is AI making work less human? 19:56 Why software developers are thriving with AI 23:46 The Swedish mine where automation actually works 31:10 Who should decide how AI changes work? 34:23 AI surveillance, trust, and workplace governance 37:56 Why companies shouldn't blindly adopt AI 39:06 Healthcare, nursing, and the cost of over-optimization 46:30 Can healthcare become human again? 49:56 Productivity, burnout, and becoming like machines 53:18 Have we lost faith in ourselves? 59:26 AI hype, fear of missing out, and smarter adoption 01:03:45 What gives Sarah hope about the future of work? 01:08:07 Advice for business and technology leaders 01:11:00 Final thoughts 01:11:47 Closing Connect with Sarah: LinkedIn: https://www.linkedin.com/in/sarah-o-connor-86067a31/ X: https://x.com/sarahoconnor_ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Government AI projects are often criticized for moving slowly, but Alberta is proving otherwise. In this episode, we sit down with Janak Alford, Deputy Minister of Technology and Innovation for the Government of Alberta, to understand how Alberta is using AI to save $2 million every week while accelerating digital service delivery, improving compliance, and raising software quality standards. Janak shares why governments and enterprises should stop waiting for the "perfect" AI solution and start building internal AI capabilities. From AI factories and builder culture to open-source tools, sovereign AI, cybersecurity, and AI-powered software development, this conversation offers a practical blueprint for organizations looking to modernize with AI and deliver measurable results. If you're tired of AI hype and want to see what real implementation looks like, don't miss this one. Follow and like this video for weekly conversations on AI, technology, digital transformation, and the future of work and technology. In this episode: 00:00 Intro 01:08 Alberta's mission to transform government with AI 04:28 Why every government faces the same AI challenge 07:53 About Info-Tech 08:33 The vision for AI-driven government 10:33 AI Academy: Training 30,000 public servants 12:12 Building thousands of AI applications 15:25 The future of AI agents in government services 17:03 Beyond AI tools: Building an AI strategy 18:07 AI factories, compliance & software development 23:53 Overcoming bureaucracy with builder culture 30:35 Saving $2 million every week with AI 32:19 The velocity papers explained 37:02 AI factory, AI garage & government modernization 42:25 Open-Source AI tools changing government 48:18 Where organizations should start with AI 54:34 The biggest AI myths leaders believe 55:16 Why Copilot isn't your AI strategy 57:44 Why subject matter experts drive AI success 01:02:19 Making AI safe without slowing innovation 01:08:28 Sovereign AI and Canada's AI future 01:15:08 Building Canada's AI ecosystem 01:16:20 Final thoughts Connect with Janak: LinkedIn: https://www.linkedin.com/in/janak-alford/ X: https://x.com/JanakAlford Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Is vibe coding the future of software development? Or is it just another AI buzzword? In this episode, Geoff Nielson sits down with Laurence Moroney, former Head of AI Advocacy at Google and now Director of AI at Arm, to separate AI hype from reality and discuss what software development actually looks like in the age of generative AI. This conversation takes a look at the future of coding, the rise of AI-generated code, and why claims that software developers are becoming obsolete miss the bigger picture. From vibe coding and enterprise AI to agentic AI and the evolving role of engineers, this Laurence and Geoff look at how AI is reshaping software development, and why the best developers will become even more valuable by moving up the value chain. Subscribe for weekly conversations on the future of technology, artificial intelligence, and innovation. Comment below: Do you think vibe coding has a place in your professional workflow? In this episode: 00:00 Intro 01:16 Has the AI bubble burst? 04:44 AI hype vs. real business value 09:21 Why AI should become invisible 12:30 The biggest AI myths leaders still believe 16:15 Will AI replace software developers? 19:28 Why developers are moving up the value chain 20:54 The rise of "ephemeral" software 26:34 Enterprise use cases for disposable code 29:02 Is vibe coding ready for the enterprise? 32:10 Small AI models vs. large language models 35:46 Fine-tuning AI for enterprise success 38:17 Why companies still need engineers 41:57 The future role of developers, CIOs & CTOs 45:09 How developers can future-proof their careers 47:09 Should students still study computer science? 49:09 Does AI create 100x developers? 51:20 What is Agentic AI? 57:06 Building enterprise AI the right way 1:02:11 AI hardware and Arm's vision 1:05:18 Advice for technology leaders 1:07:05 The future of Sovereign AI 1:14:30 Final thoughts Connect with Laurence: LinkedIn: https://www.linkedin.com/in/laurence-moroney/ X: https://x.com/lmoroney Facebook: https://www.facebook.com/laurence.moroney Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

This is THE AI debate you've been waiting for. Will AI become as transformational as the internet, or will history remember it more like blockchain and the metaverse? In this episode of Digital Disruption, Info-Tech's Geoff Nielson and Jeremy Roberts go head-to-head over one of the biggest technology questions of our time: Is AI overhyped? The debate looks at whether generative AI is delivering measurable business value or whether the excitement surrounding OpenAI, Microsoft Copilot, Google, Nvidia, and today's AI investments has outpaced reality. From enterprise productivity and healthcare innovation to AI adoption, venture capital, cloud computing, autonomous vehicles, and the future of work, both sides present compelling evidence at the Info-Tech LIVE Conference in Las Vegas. You'll hear why the profitability of today's AI industry is being questioned, how massive capital investments are shaping the race among AI leaders, and what these financial realities could mean for the future of artificial intelligence. Whether you're an IT leader, business executive, or AI enthusiast, this debate offers practical insights into where AI is delivering real value, and where expectations may be running ahead of reality. Which side of the debate are you on? Like and follow for weekly episodes. In this episode: 00:00 Is AI Overhyped? 00:52 The case against AI being overhyped 03:31 How AI is already transforming business 04:18 AI's impact on healthcare, science & society 05:20 AI is overhyped 06:40 Why many people still don't like AI 07:18 Is the AI business model sustainable? 08:45 Does AI actually save time? 09:23 AI and the future of jobs 10:17 The human cost of AI 12:04 AI adoption vs. AI skepticism 13:52 Is AI following the same path as cloud computing? 15:05 Are AI companies creating another tech bubble? 16:50 Technology vs. company valuations 18:02 AI search, Google & the future of the internet 19:31 Is AI becoming the next Blockchain? 20:24 Is AI's transformation inevitable? 21:29 Healthcare, Watson & enterprise AI 23:34 Microsoft Copilot, enterprise adoption & ROI 24:18 The future of AI in business 25:12 Audience votes on winner 26:04 Final thoughts on if AI really is overhyped. Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Stop fearing the future of work. Learn why our current infrastructure is failing and how to adapt your mindset for the age of artificial intelligence and technology. AI isn't taking your job; it's forcing humanity to rethink what work, identity, and purpose actually mean. In this conversation, Geoff Nielson sits down with innovation strategist, futurist, and author Alexander Manu to discuss why so many professionals fear a loss of income. The core issue, he argues, is not technology itself but our tendency to apply old systems to new realities. Instead of viewing artificial intelligence as a threat, Alexander explains that AI represents the next stage of human evolution, one where technology frees us from repetitive work and allows us to focus on creativity, learning, and what makes us uniquely human. The conversation also explores disruption, digital transformation, Maslow's concept of self-transcendence, the future of work, education, leadership, and what it truly means to live in an AI-first world. Whether you're a CIO, technology leader, business executive, innovator, or simply curious about where artificial intelligence is taking society, this episode offers one of the most optimistic, and challenging, perspectives you'll hear on the future of AI. Like and follow for weekly episodes. In this episode: 00:00 Intro 00:46 Why everyone is afraid of AI 01:01 Why Alexander isn't afraid of artificial intelligence 03:02 AI, work & the future of human purpose 05:24 Will AI make society happier? 06:32 Why AI is different from every technology before it 08:07 AI as a creative partner instead of a tool 10:17 The real fear behind AI: Money & identity 12:48 How do we reach an AI future? 14:03 Why we need to redesign everything from scratch 16:12 AI, identity & Maslow's self-transcendence 19:07 Using AI to unlock human creativity 20:33 Lessons from building one of the first portable computers 22:34 Technology, identity & human evolution 24:24 How every technology becomes normal 27:07 AI learns you as you learn it 28:57 Why technology exists to eliminate friction 30:19 Why society needs to embrace AI earlier 31:44 Understanding the disruption continuum 34:10 Why disruption never ends 39:45 Are we living through an AI bridge moment? 42:06 Why most companies get AI completely wrong 46:31 Stop fitting AI into old systems 51:30 The biggest AI lessons for business leaders 53:12 The question every organization should ask 56:09 Leadership, AI & the future of organizations 59:18 Why AI is not optional 1:00:52 AI's true promise isn't speed 1:05:36 AI, contemplation & finding meaning 1:06:36 Social media, creativity & human attention 1:11:48 Final thoughts Connect with Alexander: LinkedIn: https://www.linkedin.com/in/alexander-manu-458b7b3/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

AI is moving faster than most organizations can keep up with, but according to Siri co-creator Dag Kittlaus , the biggest challenge isn't the technology itself. It's adoption. In this episode, Dag shares his insights on how artificial intelligence will reshape your career, your business, and the future of work. Drawing on his experience building Siri and investing in the next generation of AI startups, Dag explains why widespread AI-driven job loss is unlikely in the near term and how business leaders can successfully integrate AI into their organizations. He explores the important differences between AI capability and AI diffusion, arguing that this distinction will shape the next decade of innovation, productivity, and economic growth. The conversation covers AI productivity gains, enterprise AI adoption, AI-first startups, Apple's AI future, personalized virtual assistants, healthcare innovation, data centers, AI infrastructure, and the emerging opportunities that business and technology leaders can't afford to ignore. Whether you're a CIO, business leader, entrepreneur, or technology professional, this episode offers practical insights into how artificial intelligence is transforming industries and why understanding AI today may be one of the most important investments you can make in your future. Like and follow for weekly episodes. In this episode: 00:00 Intro 00:53 Co-creator of Siri 01:15 AI's promise vs. AI's peril 02:28 Capability vs. diffusion: The real AI challenge 03:15 Why AI still can't replace entire jobs 04:31 Will AI cause massive white-collar job loss? 07:14 Why laying off employees for AI is a mistake 08:14 How businesses should actually adopt AI 10:30 How Dag personally uses AI today 12:41 AI investment trends and opportunities 13:27 What's next for AI infrastructure and data centers? 15:27 Hidden AI opportunities most investors miss 16:41 Winners and losers in the AI economy 17:56 How leaders should prepare their organizations 21:32 AI-first startups vs. large enterprises 23:11 Should established companies fear AI-native competitors? 24:00 Ignore AI and you're in trouble 25:21 The 10-year AI adoption timeline 26:22 Is AI ready or does it need more breakthroughs? 28:00 The original vision for Siri 29:30 AI agents, APIs, and autonomous assistants 31:32 Why apple lost ground in AI 34:53 Dag's vision for the future of Siri 35:29 The 'Conductor Thesis' for personal AI 38:30 Why personalization Is AI's missing link 39:07 Consumer backlash against AI 40:20 Why AI job loss fears are overblown 41:15 AI, productivity growth, and the four-day workweek 43:51 How to change public perception of AI 47:05 Convincing employees to embrace AI 47:50 Why incentives matter more than mandates 50:05 Practical advice for business leaders 53:03 The biggest AI trend nobody understands 53:38 How AI will transform healthcare 56:11 AI regulation and innovation challenges 58:23 Why Dag is optimistic about AI's future 59:15 Final thoughts #ai #futureofwork #leadership #siri #apple #futureofai #technologypodcast #digitaltransformation #innovation #entrepreneurship #futureofjobs #stevejobs #dagkittlaus Connect with Dag: LinkedIn: https://www.linkedin.com/in/dagkittlaus/ X: https://x.com/dagk Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if AI isn't the biggest disruption we're facing? What if the real problem is that we're trying to force 24th-century technology into an economy designed for another era? In this episode, AI and transformation leader, Michael Clark explains why AI is exposing fundamental flaws in education, business, leadership, and the global economy, and what we need to do next. Michael argues that we're trying to fit next-generation AI into systems designed for the industrial age. The conversation explores how organizations can move beyond automation and embrace collaborative intelligence, where humans and AI work together to create value. They discuss the future of work, data as an asset, workforce transformation, AI adoption, leadership in the intelligence economy, and why critical thinking, judgment, and adaptability will become the most valuable skills in the AI era. Like and follow for weekly episodes. In this episode: 00:00 Intro 01:23 Two possible futures for 2030 04:05 Why education must be rebuilt for the AI era 07:12 Teaching critical thinking, data literacy & adaptability 10:40 How work changes in the age of AI 13:22 Why people should be treated as assets, not costs 16:16 The economic model that no longer works 20:24 Rethinking value, GDP, and the future economy 24:23 Can we actually value people and data? 27:29 Why governments need an AI consortium 28:54 AI, data ownership & wealth distribution 33:05 Should AI and cloud computing be treated as utilities? 35:45 Why most organizations mismanage data 37:05 Treating data as a business asset 42:53 Why AI can't fix bad data 47:27 What data-mature organizations do differently 48:05 Schneider electric's data monetization strategy 50:24 John Deere's AI and data advantage 51:21 The ethics of data monetization 55:28 Workforce transformation and leadership in the AI era 58:29 Why leaders struggle with long-term thinking 01:00:00 Leadership, risk, and better decision making 01:03:48 Rethinking leadership for the Intelligence Economy 01:06:19 Human wisdom vs machine knowledge 01:09:23 Final advice for leaders adopting AI 01:12:14 Final thoughts Connect with Michael: LinkedIn: https://www.linkedin.com/in/mclarkglobal/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Artificial intelligence is reshaping work, creativity, business, and society faster than ever before, but how worried should we really be? In this episode, we sit down with The AI Doc producers Charlie Tyrell and Ted Tremper to discuss the biggest lessons they learned after spending years investigating AI and interviewing leading experts, including Sam Altman, Dario Amodei, Karen Hao, and many of the influential voices shaping the future of artificial intelligence. The conversation goes far beyond the typical AI debate, exploring AI ethics, generative AI, creative industries, wealth inequality, AI regulation, AGI, automation, AI governance, and the growing question of whether artificial intelligence is an inevitable force—or a technology that society can still shape. Charlie and Ted discuss the risks of concentrated power, the impact of AI on artists and filmmakers, ethical AI development, transparency, consent, and what individuals can do to influence the future of technology. AI is changing everything. The way we work, the way we create, the way we build businesses, and potentially the future of society itself. But beneath the headlines, hype, and fear, what’s actually true? If you're interested in artificial intelligence, technology, leadership, innovation, creativity, or the future of humanity, this is a conversation you won't want to miss. Like and follow for weekly episodes. In this episode: 00:00 Intro 01:25 Why Charlie Tyrell & Ted Tremper made the film 02:20 The origins of The AI Doc 04:45 AI anxiety, parenthood & the future 06:57 Wealth inequality and AI concentration 08:17 Reasons for hope and concern 11:01 How individuals can shape AI's future 11:49 Why education creates agency 13:02 AI's impact on artists and creators 15:12 Did The AI Doc use AI? 16:56 Human creativity vs AI-generated content 18:14 The filmmaking industry's AI debate 19:20 Generative AI and storytelling 21:23 Audience demand and the future of human-made art 23:13 Technology's impact on creativity throughout history 24:50 Ethical AI, consent & compensation 27:02 Can AI ever be ethical? 28:12 Policy, regulation & AI accountability 30:59 The AI arms race explained 32:14 AI competition, China & global innovation 34:07 AI narratives we should question 35:00 The Myth of AI Inevitability 37:08 Democratizing AI and power structures 38:11 What AI advocates get wrong 40:40 Radical imagination & AI governance 42:45 What gives Charlie and Ted Hope? 46:22 Raising children in an AI world 51:56 Technology, optimism & intellectual humility 55:00 The most influential voices in AI 57:39 Karen Hao, Deborah Raji & human-centered AI 1:00:08 Responsible AI use for business leaders 1:02:13 Fighting over-optimization and AI dependence 1:04:19 The hidden risks of AI services 1:07:12 Final Thoughts Connect with The AI Doc: X: https://x.com/theaidocfilm Instagram: https://www.instagram.com/theaidocfilm/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Artificial Intelligence is changing faster than most people realize, but are we asking the wrong questions about AI, AGI, consciousness, and the future of society? In this episode, cognitive scientist and AI researcher Joscha Bach joins us for a thought-provoking conversation on artificial intelligence, machine consciousness, large language models (LLMs), AGI, human intelligence, and the future of work. Joscha explains why intelligence is fundamentally about model-building, why consciousness may be a biological training algorithm, and what current AI systems are still missing. The conversation goes far beyond technology, tapping into innovation, capitalism, regulation, scientific progress, institutional trust, democracy, media narratives, AI safety, employment disruption, economic incentives, and the future of human civilization. Joscha shares his perspective on AI doom scenarios, why he believes many fears around artificial intelligence are overstated, and how AI could ultimately empower individuals rather than replace them. This episode offers a different look into artificial intelligence, human progress, and what comes next. Like and follow for weekly episodes. In this episode: 00:00 Intro 01:04 AI doom scenarios & humanity's future 02:00 Defining intelligence & consciousness 05:00 Why AI intelligence is different from human intelligence 06:52 Are LLMs actually intelligent? 08:10 Why AI hallucinates 10:09 Human learning vs machine learning 11:22 Can transformers lead to agi? 12:28 The scaling hypothesis explained 13:58 Mechanistic interpretability & neural networks 15:13 Can AI surpass human understanding? 18:42 AI and the future of scientific discovery 20:14 Why scientific progress feels slower today 22:03 Institutions, incentives & organizational decline 25:05 Trust in government and society 28:31 Can AI improve democracy? 30:40 Why AI gets such negative media coverage 33:03 The AI extinction debate 36:30 AI, automation & the future of jobs 40:05 Big Tech, AI power & capitalism 41:15 Money, markets & resource allocation 46:28 Regulation, innovation & economic growth 49:13 Why innovation is slowing down 51:08 Is Big Tech starving other industries? 54:39 Is there an AI bubble? 57:30 Could the financial system be rebooted? 01:00:17 Cryptocurrency, regulation & economic stability 01:08:27 Regulation, governance & innovation 01:10:33 Lessons from Berlin's innovation culture 01:16:08 AI, surveillance & centralized power 01:18:07 Decentralized AI and individual empowerment 01:20:05 AI, healthcare & professional expertise 01:23:36 Control, society & human responsibility 01:25:00 Advice for leaders and innovators 01:26:03 Escaping filter bubbles Connect with Joscha Bach: LinkedIn: https://www.linkedin.com/in/joschabach X: https://x.com/Plinz Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Modern work is broken. Endless meetings. Constant notifications. Work invading every corner of life. So, what does the future of work actually look like in the age of AI agents, generative AI, and organizational transformation? Microsoft’s Head of Future of Work & AI, Matthew Loys Duncan, says we’ve reached “human capacity” and that AI may not replace knowledge workers, but instead replace the worst parts of work itself. In this episode, Matthew joins Geoff Nielson to unpack how AI agents, generative AI, and organizational redesign are reshaping white-collar work. He explains why most companies are approaching AI the wrong way, why culture matters more than technology, and how the future of work will be “human-led, agent-operated.” From Microsoft’s Work Trend Index research and AI-native organizations to tacit knowledge, burnout, productivity, and leadership transformation, this conversation explores what happens when businesses stop optimizing old workflows and start redesigning work from the ground up. If you’re trying to understand the real impact AI will have on work, leadership, and business strategy over the next decade, this episode is for you. Like and subscribe for weekly conversations on AI, business, leadership, and the future of work. In this episode: 00:00 Intro 00:01:15 Will AI replace white-collar jobs? 00:02:29 Why AI is a reimagination of work, not doom & gloom 00:03:08 Human-led, agent-operated work 00:03:37 The broken reality of modern office work 00:04:36 Digital overload, meetings & workplace chaos 00:06:16 Human agency vs AI agents 00:07:33 Using AI to redesign your job 00:09:02 Why the best AI users don’t outsource judgment 00:09:49 Delegation, intentional AI use & skill preservation 00:10:54 AI as a team member, not just a tool 00:11:27 The four ways people use generative AI 00:14:10 The rise of AI agents in the workplace 00:16:16 From personal productivity to organizational transformation 00:17:10 Where is the ROI from AI? 00:18:02 Why AI adoption alone fails 00:20:13 Finding the highest-leverage AI opportunities 00:23:27 Re-architecting work in the AI era 00:25:27 Should employees build their own AI agents? 00:28:39 AI-native organizations vs legacy enterprises 00:30:05 AI adoption vs AI absorption 00:32:31 Discovering hidden business value through AI 00:33:27 How legacy firms can compete with AI-native companies 00:35:06 Why AI transformation starts with culture 00:36:05 The role of HR, CEOs & leadership in AI strategy 00:39:14 Why AI is bigger than a technology initiative 00:41:12 The expanding role of the C-Suite in AI transformation 00:46:32 Microsoft’s “learn it all” leadership culture 00:50:00 Democratizing innovation with AI 00:53:23 Tacit knowledge & AI-powered learning 00:57:09 Information retrieval, organizational knowledge & AI 00:59:37 Capturing institutional intelligence with AI 01:00:03 Advice for business & technology leaders 01:03:17 Why there is no AI playbook yet Connect with Matthew: LinkedIn: https://www.linkedin.com/in/matthewloysduncan/ X: https://x.com/matthewloys Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if the biggest threat from AI isn’t artificial intelligence… but the economic system controlling it? Author and creator of the Lean Startup methodology, Eric Ries says many of the biggest fears around AI are actually fears about capitalism. In this episode, Eric joins us to talk about why great companies lose their value over time, how shareholder prioritization reshaped modern business, and why AI could either amplify human creativity or become the ultimate cost-cutting machine. He explains the hidden forces behind corporate corruption, the concept of “financial gravity,” and why companies like Costco continue to outperform despite rejecting many traditional Wall Street “best practices.” From private equity and governance structures to AI alignment and the future of human creativity, this conversation explores the incentives shaping business, technology, and society itself. Like and follow for weekly episodes. In this episode: 00:00 Intro 01:00 Why great companies “go bad” 02:10 The rise of corporate corruption 05:48 Is capitalism itself the problem? 07:08 Making money without creating value 10:33 Corporate accountability & human flourishing 13:06 Why this problem keeps getting worse 18:21 How investors destroyed FedMart 21:22 Why Costco defies wall street logic 23:00 Financialization & the collapse of institutions 24:27 How leaders can protect mission-driven companies 27:12 “Financial gravity” explained 31:10 Trustworthiness as a business asset 34:37 Governance structures that actually work 36:20 Transitioning into AI & the future of work 37:42 AI governance & Anthropic 38:37 The AI alignment problem 41:30 Why AI is being optimized for cost cutting 42:15 AI should augment creativity, not replace humans 44:04 How to use AI as a learning tool 46:34 Real examples of AI augmentation done right 49:47 AI-assisted reading & learning 50:22 The problem with AI-generated “slop” 54:58 Why human-made work will become premium 57:19 The future of the attention economy 59:12 Will AI become addictive like social media? 01:00:03 The case for an AI Bill of Rights 01:04:11 Costco, DEI & organizational integrity 01:07:13 AI Regulation, governance & human flourishing 01:13:24 Fighting the “normative consensus” of shareholder primacy 01:21:21 Is the era of shareholder primacy already over? 01:22:22 Final thoughts Connect with Eric: LinkedIn: https://www.linkedin.com/in/eries/ X: https://x.com/ericries Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we entering the most transformative era of work in history? Technology is evolving weekly, and culture takes time to adapt. In this episode, AI futurist and award-winning innovation leader Maurice Conti explains how rapid technological change, especially in artificial intelligence, will shape our world, the economy, and the future of jobs, and what AI leadership means for navigating these shifts. Drawing on his experience with companies like Amazon, Nike, Mercedes, and Lululemon, Maurice shares insights from Fortune 100 companies and explains how generative AI, automation, and human-AI collaboration are transforming the workplace. The key insight is simple. The future of AI is not big, flashy, or “sexy.” It is quiet, invisible, and massively impactful. Maurice explains why we have entered the “Augmented Age,” where humans and AI work together, and outlines the major shifts known as the 4 Waves of AI defining this transformation, including the grassroots AI revolution happening inside organizations and the rise of AI agents and ecosystems. If you want to understand where AI is really going beyond the hype, this is a must-watch episode. Like and follow for weekly episodes. In this episode: 00:00 Intro 01:04 The “Augmented Age”: Humans + AI working together 02:10 Sci-Fi to reality: Talking to computers like Star Trek 04:11 Have we arrived at intuitive AI? 05:15 Why AI progress isn’t linear 06:05 Can anyone predict the future of AI? 07:05 The Nvidia story & “more AI in the future” principle 08:57 Amara’s Law: Short-term hype vs long-term impact 10:08 Why AI will be bigger (and slower) than expected 10:54 The 4 Waves of AI explained 11:00 Wave 1: “Interesting but not useful” AI 12:31 Wave 2: Grassroots AI (hidden ROI inside companies) 13:16 Why CEOs can’t see AI ROI 14:09 Tool users → tool makers (the real shift) 16:17 The invisible productivity explosion 20:10 Wave 3: AI agents & ecosystems 21:48 Wave 4: AI as electricity (invisible & everywhere) 23:18 The dark side of “interesting AI” 26:15 Personal AI use cases (daily life & work) 27:09 Why most organizations are still “Grassroots” 28:38 The explosion of tools (new risks for IT) 30:15 CIO/CTO challenges: Control vs innovation 33:09 Building the right AI infrastructure layer 34:45 Where should companies invest in AI? 37:14 Start with the problem, not the technology 40:04 Toolset vs skillset vs mindset 42:45 Why mindset & culture matter most 44:28 The race to the bottom vs innovation 45:15 New workplace norms & ethical questions 49:49 Why culture changes slowly 51:33 Tech vs culture: A fundamental tension 52:30 Can organizations adapt to constant change? 56:06 The myth of big, sexy AI 57:01 Small AI, massive impact 58:18 Where real innovation is happening 59:13 Why young workers lead AI adoption 01:01:22 Advice for leaders 01:02:59 AI is a “Lord of the Rings” journey 01:05:15 Will AI replace jobs? 01:10:23 Lessons from past tech revolutions 01:13:47 Why humans need ~25 years to adapt 01:16:02 Why expectations rise with technology 01:17:38 Why there will always be more work to do 01:18:55 Final thoughts Connect with Maurice: LinkedIn: https://www.linkedin.com/in/mauriceconti/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if everything we’ve been told about AI and the future of work is wrong? John Hagel says most leaders are asking the wrong questions: “How fast can we automate?” “How many jobs can we cut?” According to him, that’s a “going out of business strategy.” In this episode, we sit down with Silicon Valley veteran John Hagel, an advisor to firms like McKinsey, BCG, and Deloitte, to challenge the dominant narrative around AI, automation, and job elimination. He shares insights into how leaders are approaching AI today, often focusing on cost-cutting and workforce reduction, and what that means for the future of business and entrepreneurship. John explains that the real opportunity with AI isn’t efficiency, it’s learning. He talks about the shift from scalable efficiency to scalable learning and how organizations can use AI to augment human potential, unlock creativity and curiosity, and build cultures rooted in trust, collaboration, and continuous improvement. If you’re thinking about the future of work, this episode will challenge how you view AI, strategy, and innovation, and offer a different perspective on AI’s role in the modern economy. Like and follow for weekly episodes. In this episode: 00:00 Intro 01:30 Is “this time different” with technology? 02:29 The Big Shift: Why organizations must fundamentally change 03:18 Scalable efficiency vs scalable learning 05:33 The dangerous AI narrative: automation & job cuts 06:19 Why efficiency alone leads to diminishing returns 09:42 Trust: The missing foundation in most organizations 10:50 What happens when companies fail to adapt 12:21 Debunking AI myths and media narratives 12:46 Humans vs machines: who should do what? 13:14 Reskilling vs building human capabilities 15:03 How to convince leaders to rethink AI strategy 16:24 Fear vs opportunity in leadership 20:16 What real workplace learning looks like 21:18 The future leader: asking better questions 24:38 How to structure high-impact teams 26:06 The collapse of trust in institutions 26:58 Corporate narratives & Apple’s “Think Different” 30:06 Creativity vs technology in strategy 30:41 Zoom Out, Zoom In strategy explained 33:08 Microsoft example: seeing the future early 35:14 Why agility without direction fails 37:21 Understanding “the edge” and innovation 39:34 Why transformation efforts fail in large companies 41:22 Scaling the edge vs top-down change 42:52 The power of the “explorer mindset” 47:18 Why companies suppress passion 48:31 Only 14% of workers are truly passionate 50:18 Can passion be cultivated at scale? 52:29 Does IT still matter in the AI era? 55:07 AI, healthcare, and the future of longevity 57:13 From healthcare to “wellness ecosystems” 58:19 The rise of the trusted advisor 59:50 Can AI replace human advisors? 01:02:25 Advice for leaders 01:04:18 AI is a tool humans determine its impact 01:06:29 Why most digital transformations fail Connect with John: LinkedIn: https://www.linkedin.com/in/jhagel/ X: https://x.com/jhagel Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if the AI revolution isn’t what we’ve been promised? What does an economist and bestselling author have to say about the idea that Big Tech may be overselling the future of artificial intelligence? In this episode, Oxford economist and Associate Professor of AI & Work, Carl Benedikt Frey, shares his skeptical perspective on the impact of artificial intelligence. He explains what it could mean for the future of work, including job market shifts and the necessity of skills development. This conversation takes a critical look at the economic changes driven by AI, challenging the dominant narrative around productivity and technological progress. While Big Tech describes a future of abundance, Carl argues that history tells a more complicated story. From the Industrial Revolution to the computer age, breakthrough technologies didn’t automatically lead to sustained productivity or shared prosperity, and AI may follow a similar path. Like and follow for weekly episodes. In this episode: 00:00 Intro 00:57 Why the “AI Abundance” narrative might be wrong 01:45 Lessons from the computer revolution & productivity slowdown 03:30 AI vs computers: Automating cognition vs information 05:19 Why Big Tech may be overhyping AI impact 06:20 Automation vs creating new industries 08:08 AI infrastructure race: US vs China 10:25 The “Steam Engine Moment” AI hasn’t reached 12:31 Why technology alone isn’t enough 14:19 Why breakthrough innovation is declining 15:09 The collapse of business dynamism 15:45 Corporate lobbying, patents & barriers to entry 17:27 Why this matters more than AI itself 18:20 Startups vs Big Tech: Who drives innovation? 19:36 Will AI accelerate economic inequality? 21:37 Lessons from the Gilded Age & Antitrust History 24:04 Why strong governments enable competition 25:00 Big Tech vs historical monopolies 26:19 Centralization vs decentralization in innovation 29:01 Japan vs US 33:56 AI and the “more vs better work” problem 35:20 Will AI lower quality in research & knowledge? 36:23 AI: Increasing quantity vs improving quality 38:16 Why AI benefits low-skill workers more 39:49 AI and the rise of global labor competition 40:42 AI-driven offshoring 42:17 Which jobs are most at risk? 44:06 Long-term labor market predictions 46:20 Where humans still beat AI 48:15 The growing anti-AI backlash 49:11 Historical resistance to technology 53:39 Can government reduce AI disruption? 56:01 Why institutions determine outcomes 59:25 Advice for business leaders 01:00:12 Why decentralized companies win 01:02:24 Why innovation requires “waste” Connect with Carl: LinkedIn: https://www.linkedin.com/in/carlbfrey/ X: https://x.com/carlbfrey Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Why are 88% of businesses using AI but only 5% seeing real transformation? In this episode, we sit down with Dan Diasio, EY’s Global Consulting AI Leader and CTO, to break down the four possible futures of AI, from constraint to full transformation, and what it takes for organizations to win in an AI-driven world. Drawing from his experience advising Fortune 50 executives, Dan explains how leaders are navigating uncertainty, why many companies fall into the “sameness trap,” and what separates simple AI adoption from true competitive differentiation. We also explore the rise of AI agents and end-to-end workflows, why mindset and skillset matter more than toolset, and what the future of jobs looks like in an AI-first world. If you are thinking about AI strategy, leadership, or how to prepare your organization for what comes next, this episode delivers practical and forward-looking insights. Like and subscribe for weekly episodes. In this video: 00:00 Intro 00:40 Inside SXSW: Future-proofing AI strategy 02:14 Why predicting AI is impossible 02:56 The four AI futures explained (constraint → collapse) 04:36 What winning teams did differently 05:50 The “sameness trap” in AI 06:19 Positive vs negative AI futures 07:23 Constraint, growth, transform, collapse 09:54 What people actually believe about AI’s future 10:45 How do you win with AI? 13:17 Why business model innovation beats automation 14:02 Hands-on AI 15:46 How AI commoditizes output 17:01 AI investment trends: Productivity vs differentiation 18:13 The shift toward competitive advantage with AI 19:27 The AI Playbook: How leaders get it right 20:34 Going broad vs going deep with AI 21:11 88% vs 5%: The AI Adoption Gap 22:20 Mindset vs skillset vs toolset 23:27 Top-down vs bottom-up AI transformation 25:16 The visibility trap explained 26:06 Why new talent drives AI innovation 28:22 AI resistance & fear in organizations 29:43 “Death by a Thousand Papercuts” automation 30:54 New jobs: Knowledge Engineers & AI Orchestrators 32:48 Future Skills: Critical thinking, creativity, systems thinking 35:12 The role of IT in the AI era 37:34 AI as the new operating system of business 39:01 SaaS vs A 44:35 AI prototyping vs enterprise-scale systems 47:18 Will AI kill consulting? 54:07 AI infrastructure constraints & global risks 56:09 Biggest AI myths & misconceptions 57:34 Are we automating the wrong things? 59:27 Amara’s Law & AI hype cycles 01:00:12 How leaders should prepare 01:01:01 Why value creation beats cost cutting 01:02:17 Aligning AI strategy across the organization Connect with Dan: LinkedIn: https://www.linkedin.com/in/dan-diasio/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

This is not just a technology shift. It is a human, organizational, and identity transformation. In this episode, we sit down with Ian Beacraft, Founder and Chief Futurist at Signal and Cipher, to talk about one of the most urgent questions facing leaders today: what happens to work, organizations, and identity in the age of AI? Ian argues that the next two years will matter more than the last 30, and that AI is not just another tool. It is a platform reshaping economies, organizations, and how we define work itself. We break down why most companies are getting AI wrong, the critical difference between culture and coordination, and how the rise of AI agents is shifting value from doing the work to designing it. We also cover what leaders need to do right now to stay ahead, including real world examples of failed AI adoption, the growing power of small teams, and the coming identity shift in the workplace. Like and subscribe for weekly episodes. In this video: 00:00 Intro 01:20 Biggest AI trends since last year 02:28 Why AI is not just a tool 03:28 AI, identity, and the redefinition of work 04:08 The real threat: Outdated organizational thinking 05:00 Culture vs coordination explained 07:08 The danger of replacing humans with AI 09:48 Employee anxiety & leadership impact 11:19 Why AI is NOT an IT problem 12:31 How organizations should approach AI 15:04 Encoding human expertise into AI systems 16:22 Trust, fear, and job replacement concerns 17:23 Leadership, vision & the social contract 20:50 Why most leaders lack vision today 21:46 “What you do in the next 2 years is your legacy” 23:14 Incremental vs transformational AI thinking 24:25 Encoding organizational identity for AI 29:02 Why everyone must redesign their own work 31:16 From doing work to designing work 34:50 How leaders should drive AI adoption 38:08 Lessons from Building an AI-native organization 41:23 Rethinking departments & organizational structure 42:33 AI agents running autonomous workflows 44:08 The future role of culture 45:12 Real examples of AI agents in action 48:21 Small teams vs large organizations 49:04 The rise of entrepreneurship with AI 50:07 Which jobs are most at risk 55:13 Finding your competitive moat in AI 56:47 Why AI adoption is Lagging 57:24 Prediction: The future will be messy 59:38 Why systems must break before they improve 01:00:29 The AI transformation is about people, not tech Connect with Ian: LinkedIn: https://www.linkedin.com/in/ianbeacraft X: https://x.com/ianbcraft Instagram: https://www.instagram.com/ianbcraft/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we giving up our freedom for convenience without realizing it? In this episode, we sit down with Dr. Rumman Chowdhury, a globally recognized AI ethics leader featured in Time and Forbes, to unpack the real risks of artificial intelligence, Big Tech power, and data privacy. As the former Head of AI Ethics at Twitter and Accenture, Dr. Chowdhury shares an insider perspective on how Big Tech is consolidating power, why narratives around AGI and “AI intelligence” are often misleading, and how everyday tools from apps to social media, are quietly shaping a surveillance-driven ecosystem. This conversation dives into AI ethics, surveillance, and the future of work, and explores why trust in AI is declining even as adoption accelerates. We also break down the real-world implications of AI, and most importantly, how you can protect your data, reclaim your agency, and use AI more intentionally. In this video: 00:00 Intro 01:16 What’s wrong with AI today 02:18 Why people trust AI less every year 03:09 Big tech vs the technology itself 04:22 Dangerous narratives about AI 06:09 Anthropomorphism and moral outsourcing 07:40 The myth of AGI and profit motives 09:20 The economics behind AI power 11:21 Consumer responsibility and the privacy paradox 13:42 “I have nothing to hide” explained 15:04 How big tech is consolidating control 16:42 What consumers should actually do 18:30 Real-world consequences of data misuse 21:05 From Pokémon Go to surveillance systems 22:29 The dilemma of social media and platforms 26:05 Can AI still be used for good 28:20 Algorithms, manipulation, and loss of agency 30:12 Inside AI ethics at Twitter 33:48 Why leadership and trust are changing 35:17 Surveillance capitalism and public backlash 37:31 How to think strategically about AI 41:19 Finding agency and intentional use of AI 45:06 Will society push back against AI power 52:02 The role of AI ethicists and builders 56:41 The future of work and automation reality 01:01:32 Why expertise and discernment matter most 01:06:35 Advice for business leaders using AI 01:11:33 Final thoughts on agency and discernment Connect with Dr. Rumman Chowdhury: LinkedIn: https://www.linkedin.com/in/rumman/ Instagram: https://www.instagram.com/rumman_c/?hl=en Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What happens when AI, energy, and technology all go exponential at the same time? Salim Ismail says we’re entering a “messy decade” of disruption… In this episode, we sit down with Salim, the founding executive director of Singularity University and author of Exponential Organizations, to break down the rapid acceleration of AI, robotics, space tech, and solar energy, and what it all means for jobs, business, governments, and your future. Salim explains why AI is doubling every 8–10 weeks, how the cost of technology is collapsing, and how this shift is reshaping innovation, the workforce, and global power structures. From space-based data centers and abundant energy to the rise of AI-native companies, this conversation explores the technologies driving one of the biggest transformations of our time. Like and follow for weekly episodes. In this episode: 00:00 Intro 01:00 What’s actually going exponential right now 03:30 The convergence of multiple exponential technologies 05:00 Space tech breakthroughs & $6M rocket launches 06:30 Data centers in space & infinite compute 07:45 From scarcity to abundance: the big shift 10:30 Real-world examples: music, communication, and industry disruption 12:45 The “messy decade” before the future gets better 14:00 Why institutions are breaking down (government, media, education) 15:30 Star Trek vs mad max: two possible futures 17:00 Why humans fear AI 20:00 Why technology is still humanity’s biggest advantage 23:00 Will AI take your job? 25:00 The ATM example: why jobs don’t disappear 26:30 AI organizations and 80% workforce reduction myth 28:30 The future of companies: small teams, big impact 30:00 The rise of the creative economy 32:00 Why human experience becomes more valuable 34:30 AI and human experts (doctors, teachers, consultants) 37:00 Which industries will be disrupted first 40:00 Why governments are falling behind 41:30 How to actually innovate 46:30 What leaders must do right now 50:00 What is an exponential organization? 52:30 “What do I do on Monday?” practical advice 57:00 The only strategy that works 59:00 AI startups & the future of entrepreneurship 01:02:00 Why most companies will fail to adapt 01:06:00 How to increase organizational speed 01:10:00 Leadership in the age of exponential change 01:15:00 The future of nations vs cities 01:20:00 Remote work vs in-person work 01:25:00 Robots, AI, and the coming inner loop 01:26:30 Why AGI is misunderstood 01:32:00 What most people get wrong about the future 01:34:00 Fixing civilization & human evolution 01:37:00 Psychedelics, creativity, and human potential 01:42:00 AI solving science and R&D autonomously 01:48:00 Raising kids in an AI world 01:52:00 The risk of losing human connection 01:53:00 Where we’re headed Connect with Salim: LinkedIn: https://www.linkedin.com/in/salimismail/ X: https://x.com/salimismail Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are businesses falling behind in the AI revolution? While AI is transforming everything from workflows to decision-making, many companies are facing a surprising reality: they’re becoming less prepared for AI, not more. In this episode, we sit down with Brian Solis, a globally recognized futurist and thought leader, to explore how disruptive technology is reshaping business, society, and the future of work. As Head of Global Innovation at ServiceNow, Brian shares expert insights on business innovation, AI adoption, and what it truly takes to succeed in this rapidly evolving landscape. We also talk about the growing gap between AI-native companies and traditional enterprises, the rise of the agentic enterprise, and why true AI-driven reinvention requires far more than simple automation. Like and follow for weekly episodes. In this episode: 00:00 Intro 00:55 Are businesses falling behind in AI? 01:30 What “AI disruption” really means for business 03:30 The hidden dangers of AI: Bias, sycophancy & atrophy 05:20 Why most companies are underusing AI (capability overhang) 07:00 The AI index explained: Why readiness is declining 08:30 AI maturity scores are dropping and here’s why 10:50 Will AI-native startups disrupt enterprise giants? 13:00 How AI is reshaping jobs, roles, and workflows 15:30 The biggest myth: “AI transformation is easy” 16:30 What is the agentic enterprise? (future of AI work) 18:30 Automation vs innovation: Where AI creates real value 20:30 Why AI needs vision, not just it execution 22:30 IKEA’s $1B AI Pivot: A real business case study 25:00 AI business reinvention vs digital transformation 27:00 AI agents explained: How they actually work in business 30:00 Who manages AI? The Rise of HR and IT collaboration 33:30 The Chief Workflow Officer: A new c-suite role? 37:30 Innovation culture vs reality: Why most companies fail 45:00 Can you succeed in AI without an innovation culture? 53:00 Biggest AI myth debunked and final takeaways Connect with Brian: LinkedIn: https://www.linkedin.com/in/briansolis/ X: https://x.com/briansolis Instagram: https://www.instagram.com/briansolis/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What happens to leadership, meaning, and human value in the age of AI? On this episode of Digital Disruption, we’re joined by Chip Conley, the former Head of Strategy at Airbnb, New York Times bestselling author, and founder of the Modern Elder Academy. Chip joins Geoff to explore whether humans are becoming obsolete or more important than ever. Chip makes the case that while AI is commoditizing knowledge, it’s elevating the value of human wisdom, intuition, and soulful leadership. They unpack the difference between knowledge and wisdom, why AI struggles to ask the right questions, how leaders can balance efficiency with humanity, and what the future of work looks like in an AI-driven world. From philosophy and ethics making a comeback to practical frameworks and wisdom as metabolized experiences shared for the common good, this episode is for anyone navigating AI transformation, searching for meaning, or rethinking what it means to lead and work today. If AI is the age of intelligence, this conversation argues that wisdom is the real competitive advantage. Chip is an American hotelier, hospitality entrepreneur, author, and speaker who founded Joie de Vivre Hospitality, growing it into the second-largest boutique hotel brand in the U.S., and later served as Airbnb’s Head of Global Hospitality & Strategy. A New York Times bestselling author of books like Peak, Emotional Equations, and Wisdom@Work, he founded the Modern Elder Academy, the first “midlife wisdom school,” to reframe aging and midlife. He is a prominent speaker, board member, and advocate for social impact initiatives. In this episode: 00:00 Intro 00:27 Are humans becoming obsolete in the age of AI? 01:08 What is Chip Conley’s core philosophy today? 01:27 Knowledge vs. wisdom: Why it matters more than ever 02:30 AI, intelligence, and the limits of answers 03:16 Why AI can’t ask the right questions (yet) 04:06 Human intuition, storytelling, and experience 06:19 Is AI a useful tool for leaders? 07:06 How to use AI effectively as a leader 07:43 Efficiency vs. soulfulness in work 09:18 The human + AI partnership 11:27 What is “soulfulness” in leadership? 14:10 Leadership, agency, and accountability 15:30 Leaders as resource allocators 17:17 Great leaders create future leaders 18:29 Defining soulfulness: Empathy, intuition & connection 20:19 Why soulful leaders feel different 21:36 Is society losing its soul? 22:25 Why scarcity makes wisdom more valuable 24:27 Leadership, culture, and emotional contagion 27:04 “Win at All Costs” vs. soulful leadership 28:16 Is being human a weakness in business? 29:53 The return of philosophy, ethics & humanities 31:09 Why wisdom is making a comeback 34:23 The future of work and what changes 37:31 AI as a partner, not a replacement 38:20 New careers: Coaches, curators & meaning makers 39:04 What is Wisdom? 42:18 Viktor Frankl & the equation for meaning 44:24 Purpose vs. meaning explained 46:47 Growth mindset vs. Know-it-all culture 49:32 Turning pain into wisdom 50:29 The Midlife “U-Curve” of happiness 53:21 The “Diet of Despair” in modern media 59:19 Advice for young people in the AI era 01:02:10 Why usefulness matters more than youth Connect with Chip: LinkedIn: https://www.linkedin.com/in/chipconleysf/ X: https://x.com/ChipConley Instagram: https://www.instagram.com/chipconley/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we in an AI bubble or at the beginning of the biggest technological convergence cycle since the Industrial Revolution? On this episode of Digital Disruption, we’re joined by the CEO of the Future Today Strategy Group and tech futurist Amy Webb. Amy joins Geoff Nielson to unpack what 2026 really looks like through the lens of artificial intelligence, programmable biology, quantum computing, biological computing, geopolitics, and systems-level change. Amy argues that we’ve officially entered a new convergence cycle, a rare historical moment where AI, biotech, computing architectures, economic systems, and geopolitics collide to create an entirely new reality. This isn’t incremental innovation. It’s structural transformation. If you’re looking for a conversation grounded in data-backed frameworks to help you navigate disruption, understand convergence cycles, and build real strategic vision in an age of uncertainty, this episode is for you. Tune in to hear what “creative destruction” truly means for business leaders, how power is shifting between Big Tech, governments, and capital markets, why “future-proofing” is a myth, and why many CEOs are falling short when it comes to long-term strategic foresight. Amy is recognized as the global authority who transformed the practice of strategic foresight into a rigorous, data-driven discipline. A pioneering quantitative futurist, she established the field’s foundational methodologies that today guide leaders, organizations, and governments in anticipating disruption, shaping the future, and securing long-term growth. Ranked the #4 Most Influential Management Thinker in the World by Thinkers50, Amy is regarded as one of the most important voices on the future of technology, business, and society. Forbes named her “one of the five women changing the world,” and the BBC recognized her among its 100 Women of the Year. In this video: 00:00 Intro 01:08 Where are we in 2026? A world in technological “Typhoon” 01:49 What is a convergence cycle? (Industrial revolution to internet era) 04:14 Why AI is the foundation of this new era 05:04 Systems-level change vs trend stacking 06:19 From AI winters to generative AI breakthroughs 07:27 Power shifts: OpenAI, Microsoft, Google & Competitive Dynamics 08:31 Winners vs losers in the convergence economy 09:26 Fear, FOMO & leadership paralysis 12:17 Rethinking regulation & geopolitical power shifts 15:40 Why “Future-Proofing” is a myth 17:14 AI capital flood: Is there a bubble? 19:25 Enterprise AI & the 80% workforce threshold 23:27 The attention economy & AI hype 27:28 Where AI actually creates real impact 28:11 Programmable biology & DeepMind’s Evo 2 30:00 Climate solutions, agriculture & synthetic biology 31:59 Dolly the Sheep & why transparency matters 38:19 mRNA, public trust & technology communication 40:15 The polycompute future: AI + quantum + biological computing 41:01 Quantum computing’s business implications 42:20 Brain organoids & biological computers 46:48 Creative destruction: What must die for you to survive? 49:00 Why evolution isn’t enough anymore 51:47 Why leaders avoid dangerous conversations 52:39 Strategic foresight & data-backed vision 56:36 Why AI navel-gazing is procrastination 57:23 Leadership in an age of convergence Connect with Amy: LinkedIn: https://www.linkedin.com/in/amywebb/ X: https://x.com/amywebb Instagram: https://www.instagram.com/amywebbfuturist/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Is AI really replacing software engineers, or just changing how they work? On this episode of Digital Disruption, we’re joined by Bala Muthiah, Director of Engineering at Lyft. Bala sits down with Geoff to cut through the hype around AI in software development and explain what’s actually changing inside high-performing engineering teams and what that means for the future of work. From vibe coding and AI-powered prototyping to production-ready systems, productivity gains, and the reality behind 10x (or 100x) engineer claims, Bala shares a grounded perspective on why true improvements are closer to 10–20%, not exponential overnight disruption. They discuss engineering leadership in the AI era, bridging skeptics and evangelists, why value creation matters more than lines of code, the importance of customization over out-of-the-box AI, data privacy and governance responsibilities, the growing digital divide, and the critical role of curiosity, culture, and trust in building modern tech teams. Bala is a technology leader who builds high-performing teams and AI that enhances human connection. Beyond his technical leadership, he serves as a startup advisor and served as an advisory board member at Defy Ventures (nonprofit focused on prison reform), reflecting his belief that community impact and innovation should grow together. He emphasizes that AI with humans in the forefront shapes everything he does. AI. He promotes positive aspects of AI while recognizing that leaders must guide its development responsibly. In this episode: 00:00 Intro 00:57 Why this is the most pivotal moment in tech 02:21 Bridging the AI dreamers and skeptics 03:18 Productivity vs. value creation 04:44 Vibe Coding: Hype vs. reality 05:27 Democratizing software development 06:09 Prototyping vs. production code 08:17 Will AI reduce the need for engineers? 12:25 What engineers should focus on now 13:59 Curiosity as a core engineering trait 15:34 Why engineers must be close to customers 17:28 Feature slop & intentionality 20:39 Lyft’s real-time AI design workflow (cursor example) 23:32 When AI is (and isn’t) truly real-time 25:18 Custom AI vs. out-of-the-box tools 26:55 Data ethics, privacy & governance in ai 29:04 A framework for sensitive data 31:18 Why leaders must act before regulation 32:38 AI Hype: Utopia vs. doomsday narratives 36:23 Culture as a competitive advantage 38:55 What makes a great engineering leader 40:42 Common mistakes new tech managers make 45:19 From “sell” to “tell” 47:55 Leading hybrid & remote engineering teams 49:46 The 10x (or 100x?) engineer debate 53:29 Advice for young engineers 55:23 The future of work 56:55 Bridging the digital divide 58:51 “Give Before You Take” philosophy Connect with Bala: LinkedIn: https://www.linkedin.com/in/balaarjunan/ X: https://x.com/balaarjunan Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What does it actually take to lead in the age of AI? On this episode of Digital Disruption, we’re joined by Deborah Liu, former CEO of Ancestry and former VP of Facebook Marketplace at Meta. Deborah joins Geoff to share a candid, practical look at modern leadership in 2026. Drawing on her experience scaling billion-user platforms and transforming legacy organizations, she explains why “adding AI” isn’t a strategy and what it truly means to build an AI-native company. They unpack Facebook’s mobile-first pivot and what it teaches about leading through disruption, why adaptability may be the most important executive skill of the next decade, and how CEOs should think about AI governance, security, and enterprise guardrails. Deborah also discusses building with a founder mindset inside large organizations and creating a culture where innovation comes from the bottom up. This conversation also explores the human side of leadership and why communication makes up 80% of the job. Deborah was most recently President and CEO of Ancestry, where she brought the legacy company into its next phase of growth. In her prior role at Meta, she turned persistence into a platform. The idea for Facebook Marketplace came to her during her first interview, though it took six years of strategic thinking and tenacious advocacy to build what would become a global marketplace serving over a billion people. She also architected Facebook’s first mobile ad products and payments infrastructure, proving that the most powerful solutions emerge when you connect the right people, ideas, and opportunities. Her 20+ years in tech began with integration work at PayPal and eBay — complex projects that taught her how to see the connections others miss. In this video: 00:00 Intro 01:00 What Being a CEO Means in 2026 06:30 Rebuilding a legacy company for the AI era 07:20 Facebook’s mobile-first pivot (stock price crisis) 10:45 The power of top-down buy-in 12:00 Big bets vs incremental change 15:00 The “Future Us” decision-making framework 19:35 How to build great products 21:00 Fall in love with the problem, not the solution 22:45 AI: Blessing or curse for product teams? 24:30 AI governance, security & data risks 26:45 Are developers becoming obsolete? 28:30 Why senior engineers are more valuable in AI 30:00 Should CEOs own AI strategy? 34:30 Magic wand dinners & listening as a leader 36:00 Remote work vs in-person culture 40:00 Breaking the CEO archetype 44:00 Failure as a career advantage 47:00 Communication is 80% of leadership 51:00 Why experts often fail as managers 53:30 Building a culture of innovation 58:00 Scaling infrastructure to unlock product velocity 1:10:00 Parenthood & career stalls (the honest truth) 1:15:00 Networking for introverts 1:20:00 Adaptability: The most important skill of the next decade 1:21:30 Closing thoughts Connect with Deborah: LinkedIn: https://www.linkedin.com/in/deborahliu/ X: https://x.com/debliu_ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Is AI actually going to replace developers? Or is the hype getting ahead of reality? On this episode of Digital Disruption, we’re joined by Sebastian Raschka, AI Research Engineer and author. Sebastian Raschka sits down with Geoff Nielson to unpack the real state of Large Language Models (LLMs) in 2026. As an LLM research engineer, Sebastian bridges deep technical expertise with practical, real-world AI implementation. In this conversation, he cuts through AI hype to focus on what’s actually achievable with modern LLMs, reasoning models, reinforcement learning, and inference scaling and where the limitations still exist. Sebastian explains why most companies should not build a large language model from scratch, but also why understanding the fundamentals may be one of the most important investments technology leaders can make. This conversation breaks down: ◼️Why coding is currently the strongest LLM use case ◼️Why “reasoning” models still fail simple tasks like counting letters in “strawberry” ◼️The reality behind Math Olympiad gold-level AI claims ◼️The true cost of training large models (millions in GPU compute) ◼️The privacy risks of uploading proprietary data into APIs ◼️How enterprises should think about fine-tuning vs API-based prompting ◼️Why benchmarks and leaderboards can be misleading Sebastian Raschka has over a decade of experience in artificial intelligence and machine learning. His work bridges academia and industry, serving as a Senior Engineer at Lightning AI and as a faculty member at the University of Wisconsin–Madison. He is the author of Build a Large Language Model from Scratch and is widely recognized for his practical, code-driven approach to AI education and research. His expertise lies in LLM research, transformer architectures, reinforcement learning, and the development of high-performance AI systems, with a strong focus on real-world implementation. In this video: 00:00 Intro 01:23 The Rise of “Reasoning” and Thinking Models 03:06 Inference scaling vs training scaling 06:17 What LLMs are actually good (and bad) at 07:09 The “Strawberry” Problem and Reasoning Limits 09:00 Tool use and why LLMs don’t need to count letters 10:20 Math Olympiads & self-refinement techniques 12:01 Why coding is the killer use case 13:28 Does AI make developers obsolete? 18:02 The Reality of 10x developer productivity claims 21:43 Generalist vs specialized models 23:53 Build from scratch vs fine-tune vs API prompting 25:01The true cost of training an LLM 27:33 API customization vs owning your model 29:12 Who should build an LLM from scratch? 33:16 Data requirements & why you need terabytes 34:28 Enterprise data challenges 35:40 Retrieval-Augmented Generation (RAG) explained 46:05 Multi-agent systems & tool calling 49:48 The problem with LLM benchmarks 55:43 Using LLMs as judges 58:00 Biggest misconceptions about LLMs 1:04:19 Reinforcement learning with verifiable rewards 1:06:32 Advice for technology leaders 1:11:48 Escaping AI hype through fundamentals Connect with Sebastian: LinkedIn: https://www.linkedin.com/in/sebastianraschka/ X: https://x.com/rasbt Connect with Sebastian: LinkedIn: https://www.linkedin.com/in/sebastianraschka/ X: https://x.com/rasbt Our links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

Is artificial intelligence strengthening democracy or quietly reshaping power in ways we’re not prepared for? On this episode of Digital Disruption, we’re joined by world-renowned security technologist and author Bruce Schneier. Bruce is described by the Economist as a "security guru," he is best known as a refreshingly candid and lucid security critic and commentator. He works at the intersection of security, technology, and people. and has been writing about security issues on his blog since 2004 and monthly newsletter since 1998. He is a fellow and lecturer at Harvard’s Kennedy School, a board member of the Electronic Frontier Foundation, and the Chief of Security Architecture at Inrupt, Inc. Bruce joins Geoff to explore one of the most important questions: Will AI strengthen democracy or quietly undermine it? From government services and public policy to cybersecurity, labor, and the justice system, Bruce breaks down how artificial intelligence acts as a power-magnifying technology, amplifying both the best and worst intentions of those who use it. Drawing from real-world examples in Germany, Brazil, Japan, France, Canada, and the United States, this conversation examines where AI is already reshaping democratic institutions. He also outlines four concrete strategies for steering AI toward democratic outcomes: resisting harmful uses, reforming the AI ecosystem, responsibly deploying AI where it helps, and fixing the underlying societal problems AI tends to amplify. This conversation also dives into: ◼️How AI can improve government efficiency without replacing human judgment ◼️The risks of AI concentration in the hands of powerful corporations and governments ◼️AI’s impact on work, jobs, and hiring in an era of automation ◼️The role of regulation, reform, and resistance in shaping AI’s future ◼️Whether AI will ultimately democratize power or reinforce inequality In this video: 00:00 Intro 02:10 AI as a power-magnifying technology 05:00 The four ways AI can help or harm democracy 07:20 Real-World AI use in elections and civic engagement (Germany & Japan) 10:00 AI in courts, justice systems, and public administration (Brazil) 12:30 Journalism, transparency, and AI as an investigative tool 15:00 Human-in-the-loop: Why oversight still matters 18:20 Designing AI that can say “yes” but not “no” 21:00 AI, Work, hiring, and the automation arms race 24:00 Fraud, trust, and remote work in the AI Era 27:00 Does AI democratize power or reinforce it? 30:00 Trustworthy AI vs. “good enough” AI 33:00 When AI is forced on citizens without choice 36:00 Regulation, markets, and the myth of the AI arms race 39:00 What leaders should ask before deploying AI 42:00 Jobs, backlash, and AI-driven inequality 44:00 Lessons from blockchain and past tech hype cycles 48:00 AI, cybersecurity, and the attacker vs. defender balance 52:00 The future of AI skills and careers 55:00 Steering AI toward democracy Connect with Bruce: Facebook: https://www.facebook.com/bruce.schneier Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What does the future of AI really look like as we head toward 2026, beyond the hype, headlines, and fear-driven narratives? On this episode of Digital Disruption, we’re joined by internationally recognized advisor, speaker, and researcher on AI strategy, Walter Pasquarelli. Walter is one of the world’s leading voices on ethical and strategic AI. He has advised governments, global institutions, and leading technology companies on AI governance, policy, and readiness, and brings a grounded perspective on what it really takes to lead in the age of artificial intelligence. Walter joins Geoff to unpack what’s actually happening with artificial intelligence and what most media coverage gets wrong. He brings a 360-degree view of AI adoption and how AI is moving out of boardrooms and into everyday life, reshaping how people think, decide, work, and relate to technology. This conversation dives into: Why AI adoption is accelerating among consumers not just enterprises The rise of AI companions, humanoid robots, and everyday AI use The real risks behind automation anxiety, data privacy, and emotional dependency What “AI psychosis” is and why it’s a growing concern Why AI literacy matters more than fear, hype, or blind regulation How AI is reshaping work, leadership, and global competitiveness In this video: 00:00 Intro 01:14 AI’s trajectory toward 2026 02:09 AI moves from boardrooms to living rooms 03:16 Humanoid robots: From screens to physical bodies 05:35 Household robots, prestige, and consumer adoption 07:33 Military, drones, and high-stakes AI applications 08:46 Self-driving cars as robotics, not just vehicles 13:49 Automation anxiety and ethical reality 18:30 Shifting authority from humans to algorithms 19:58 Power concentration and data privacy risks 22:49 AI, mental health, and emotional dependency 28:11 Why regulation alone will always lag 33:25 Business leaders’ biggest AI misconceptions 36:49 Data, talent, and capability gaps 42:18 Estonia, strategy, and digital leadership 44:42 Advising governments: What leaders must do 49:49 AI, sector disruption, and the future of work 53:22 Why top performers benefit most from AI 56:14 Judgment, curation, and human excellence Connect with Walter: LinkedIn: https://www.linkedin.com/in/walter-m-pasquarelli/?originalSubdomain=uk X: https://x.com/waltpasquarelli Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if AI becomes the most consequential technology in human history? On this episode of Digital Disruption, we’re joined by Nina Schick, geopolitical analyst and one of the world’s leading voices on AI. Nina Schick is a globally recognized expert on AI, geopolitics, and power. She was among the first to forecast the societal impact of AI-generated content and now leads the conversation on Industrial Intelligence, the idea that AI is not just software, but a geopolitical and industrial transformation. Nina sits down with Geoff to unpack how intelligence itself is becoming a geopolitical weapon. She explains why we are entering the Age of Intelligence, where non-biological intelligence may soon rival or surpass human intelligence, reshaping economics, warfare, democracy, labor, and global power structures This conversation goes far beyond AI tools and chatbots. We explore: Why AGI may arrive sooner than expected How AI infrastructure and scaling laws are reshaping global power What AI means for warfare, democracy, and national security How near-zero-cost intelligence will transform work and leadership In this episode: 00:00 Intro 01:33 The AI scaling laws accelerating toward AGI 03:09 Excitement vs fear: how disruptive will AI really be? 05:16 Deepfakes, information warfare, and early AI misuse 06:58 AI’s true killer app: scientific discovery 08:49 Intelligence as a utility and the speed of global disruption 10:38 Why AI is becoming the biggest political issue of our time 12:12 Concentration of power and the rise of AI monopolies 14:33 Technology, history, and why power always follows innovation 16:18AI infrastructure, hyperscalers, and trillion-dollar CapEx 19:05 AI as hard power and American technological dominance 21:15 NATO, national security, and autonomous warfare 23:55 The end of American hegemony and the rise of hard power politics 27:36 Democracy vs authoritarianism in the AI race 29:48 Why trivial consumer AI is a strategic failure 35:52 What AI deployment really means for businesses 39:13 The myth of AI tools vs intelligence as a capability 41:41 Will AI actually cause mass layoffs? 46:32 Asset ownership in a world of cheap intelligence 50:24 How AI empowers individuals and emerging economies 52:51 The most important skills for the AI age 55:38 Why being human matters more than ever 56:41 Resilience, risk, and the future Connect with Nina: LinkedIn: https://www.linkedin.com/in/ninaschick/ X: https://x.com/NinaDSchick Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Is the metaverse actually dead or just badly branded? On this episode of Digital Disruption, we’re joined by Christian Venables, co-founder of Radical Realities. Christian specializes in immersive technology and AI, staying at the forefront of emerging tools, platforms, and workflows. With a strong foundation in architecture and design, he has transitioned into extended reality (XR), exploring the evolving possibilities of virtual reality (VR), augmented reality (AR), and spatial computing. He is the Co-Founder of Radical Realities, a global immersive studio of creative innovators operating entirely virtually. The studio delivers experiences that transcend the physical world, spanning metaverse development, gaming, AR/VR/MR, CGI, VFX, and AI consultancy. Throughout his career, Christian has led and contributed to immersive projects for globally recognized brands including Coachella, Universal, Disney, Cartier, and Hyundai. Christian sits down with Geoff to break down why the metaverse will be rebranded and not abandoned. The real future isn’t cartoon avatars or fantasy worlds, but spatial computing, AR glasses, and ambient interfaces that blend seamlessly into everyday life. Despite years of hype, backlash, and false hope, the metaverse may finally be entering its most practical and powerful phase. Christian explains why the term itself may disappear, while the underlying technologies XR, spatial computing, AI-driven 3D design, and wearable AR glasses, are already reshaping how we work, learn, design, and collaborate. From Meta Ray-Ban display glasses and neural wristbands to Gravity Sketch, Unreal Engine, and AI-assisted worldbuilding; This conversation explores how immersive computing is moving beyond gimmicks into real-world utility, especially across architecture, engineering, education, and the creative industries. In this video: 00:00 Intro 03:00 Is the metaverse dead or just misbranded? 06:00 Spatial computing vs virtual worlds 09:00 Why AR glasses matter more than headsets 12:00 Smart glasses: why this wave is different 15:00 Neural wristbands and gesture-based control 18:00 How quickly humans become dependent on tech 21:00 The split between human-made and AI-generated culture 24:00 Augmenting creativity instead of replacing it 27:00 Designing entirely inside VR 30:00 Gravity Sketch: true 3D creation explained 34:00 Why spatial collaboration beats screens 38:00 Real-world use cases: architecture & manufacturing 42:00 Why mouse and keyboard are reaching their limits 47:00 AI + XR: generating worlds in real time 52:00 What needs to happen before immersive tech scales 56:00 Should immersive computing be back on our radar? Connect with Christian: LinkedIn: https://www.linkedin.com/in/christian-venables-74542836/ Instagram: https://www.instagram.com/csavenables/ X: https://x.com/Csavenables Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What happens when the people building artificial intelligence quietly believe it might destroy us? On this episode of Digital Disruption, we’re joined by Gregory Warner, Peabody Award–winning journalist, former NPR correspondent, and host of the hit AI podcast The Last Invention. Gregory Warner is a versatile journalist and podcaster. He has been recognized with a Peabody Award and other awards from organizations like Edward R. Murrow, New York Festivals, AP, and PRNDI. Warner's career includes serving as an East Africa correspondent, where he covered the region's economic growth and terrorism threats. He has also worked as a senior reporter for American Public Media's Marketplace, focusing on the economics of American health care. His work has been recognized with a Best News Feature award from the Third Coast International Audio Festival. Gregory sits down with Geoff for an honest conversation about the AI race unfolding today. After years spent interviewing the architects, skeptics, and true believers behind advanced AI systems, Gregory has come away with an unsettling insight: the same people racing to build more powerful models are often the most worried about where this technology is heading. This episode explores whether we’re already living inside the AI risk window, why AI safety may be even harder than nuclear safety, and why Silicon Valley’s “move fast and fix later” mindset may not apply to superintelligence. It also examines the growing philosophical divide between AI doomers and AI accelerationists. This conversation goes far beyond chatbots and job-loss headlines. It asks a deeper question few are willing to confront: are we building something we can’t control and, doing it anyway? In this video: 00:00 Intro 03:00 AI models that already behave like elite hackers 05:00 Why the AI risk window may already be open 06:30 What AI safety actually means (and why it’s so hard) 12:00 Human-in-the-loop: safety feature or illusion? 15:00 AI as an alien intelligence, not a human one 19:00 The Silicon Valley AI arms race explained 21:00 OpenAI, DeepMind, Anthropic, xAI: who’s racing and why 25:00 The “Compressed Century” and radical AI optimism 27:00 Can AI actually solve humanity’s biggest problems? 33:00 Capital, competition, and the pressure to deploy 37:00 Is AI more dangerous than nuclear weapons? 39:00 The problem with comparing AI to past technologies 43:00 What happens to human agency in an AI-driven world? 45:00 How AI reshapes creativity, journalism, and truth 53:00 The quiet assumptions built into AI systems 55:00 Why optimism and fear both miss the full picture 59:00 What responsibility do users have? 01:01:00 The most important question we’re not asking about AI Connect with Gregory:LinkedIn: https://www.linkedin.com/in/radiogrego/Instagram: https://www.instagram.com/radiogrego/ Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

What happens to jobs, money, and meaning when intelligence becomes cheaper than labor and humans are no longer the smartest ones in the room? On this episode of Digital Disruption, we’re joined by Emad Mostaque, founder of Stability AI and a leading voice in the global AI revolution. Emad Mostaque is a businessman, mathematician, and former hedge fund manager. He is the co-founder and was CEO of Stability AI, the company behind the popular text-to-image generator Stable Diffusion. With a master’s degree in mathematics and computer science from Oxford, Emad Mostaque has significantly contributed to artificial intelligence. His vision for Stability AI was to “build the foundation to activate humanity’s potential” through open-source generative AI. Emad sits down with Geoff to explore a future that may arrive far sooner than most people expect. He argues that within the next 1,000 days, artificial intelligence will fundamentally reshape the global economy, upending work, capitalism, enterprise software, and even how we define human value. Drawing from his book The Last Economy, Emad lays out a stark and deeply thought-provoking framework for understanding what comes next when cognitive labor becomes economically irrelevant. This conversation explores the inevitabilities of exponential AI progress, including why intelligence is becoming “too cheap to measure,” how AI agents will replace many jobs done behind a screen, and the coming shift from human-plus-AI teams to AI-only systems. Beyond the economics, Emad also tackles the human question: where meaning comes from in a world where AI outperforms us at most cognitive tasks. He argues that resilience in the AI age will depend less on job titles and more on community, networks, relationships, and how deeply individuals engage with the technology itself. In this video: 00:00 Intro 04:30 What is “The Last Economy”? 08:45 Intelligence becomes too cheap to measure 13:30 The three possible AI futures 18:00 Are humans becoming the weakest link? 22:15 The rise of economic agents 27:00 Digital doubles and the end of white-collar work 31:45 Enterprises racing toward zero employees 36:30 Why AI is cheaper than human labor (by orders of magnitude) 41:15 Software, SaaS, and the collapse of enterprise moats 46:00 The internet after AI agents 50:15 Who controls the “AI next to you”? 54:30 Open-Source vs Big Tech AI 58:45 The first one-person billion-dollar company 1:03:30 What humans are still for 1:07:00 How to prepare for the AI economy now Connect with Emad: LinkedIn: https://www.linkedin.com/in/emad-mostaque-9840ba274/?originalSubdomain=uk X: https://x.com/EMostaque Facebook: https://www.facebook.com/mostaquee/ Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

Is artificial intelligence humanity’s greatest salvation, or the most dangerous force we’ve ever unleashed? Artificial intelligence is no longer a future concept, it’s a force already reshaping geopolitics, economics, warfare, and the human experience itself. In this year in review episode of Digital Disruption, we bring together the most provocative, conflicting, and urgent ideas from this past year to confront the biggest question of our time: What does AI actually mean for humanity’s future? Across more than 40 conversations with leading technologists, journalists, researchers, and futurists, one theme dominated every debate, AI. Some guests argue that artificial general intelligence (AGI) and superintelligence could trigger an extinction-level event. Others believe AI may usher in an era of total abundance, solving humanity’s hardest problems. And still others claim today’s AI hype is little more than marketing smoke and mirrors. This episode puts those worldviews head-to-head. In this episode: 00:00 The AI singularity is here 05:00 Existential threat or greatest opportunity? 10:00 Why no one agrees on ai’s future 15:00 The race toward AGI and superintelligence 20:00 The control problem nobody has solved 25:00 Intelligence has no morality 30:00 Capitalism, venture capital, and the AI arms race 35:00 Is AI just a marketing illusion? 40:00 Generative AI: Power, limits, and misuse 45:00 Autonomous weapons and modern warfare 50:00 Fear as the driver of dangerous innovation 55:00 Why AI is not like nuclear weapons 1:00:00 The first and second AI dilemmas 1:05:00 Handing decisions over to machines 1:10:00 Collapse, abundance, or course correction? Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

Are companies preparing for an AI-powered future or reacting out of fear of being left behind? Looking ahead to 2026, Geoff Nielson and Jeremy Roberts sit down for an unfiltered conversation about artificial intelligence, the economy, and the future of work. As AI hype accelerates across markets, boardrooms, and headlines, they ask the hard questions many leaders and workers are quietly worrying about: Are we in an AI bubble? If so, what happens when expectations collide with reality? This episode explores whether today’s massive investment in AI, GPUs, infrastructure, copilots, and generative tools is laying the foundation for long-term value or repeating the familiar patterns of past tech bubbles like the dot-com boom and the subprime mortgage crisis. Geoff and Jeremy break down why traditional metrics like price-to-earnings ratios matter, why Nvidia and big tech dominate the narrative, and why the real risk may not be collapse but widespread underperformance. The conversation goes far beyond markets. They dig into the impact of AI on jobs, layoffs, and corporate restructuring, challenging the idea that AI is “taking jobs” versus being used as convenient cover for economic tightening. From IT, HR, and operations to customer-facing roles, they examine how AI could reshape workforce composition, accelerate automation, and create a new and potentially unsettling employment equilibrium. You’ll also hear a candid critique of how organizations are actually using AI today and what is to come next in 2026. Tech Trends Report 2026: https://www.infotech.com/research/ss/tech-trends-2026?utm_source=youtube&utm_medium=social&utm_campaign=research In this video: 00:00 Just add AI to everything? 03:45 Looking ahead to 2026: Nobody knows what’s coming 07:10 Are we in an AI bubble? 12:30 Comparing AI to the dot-com and 2008 crashes 18:10 Nvidia, GPUs, and the AI Gold Rush 24:20 Why AI infrastructure may be ahead of real-world use cases. 30:40 Markets untethered from reality 36:50 is AI really taking jobs or is something else happening? 43:30 The real employment question for 2026 49:40 Corporate bloat, back-office roles, and automation 56:10 Why most AI projects fail to deliver value 1:02:45 From productivity theater to real ROI 1:09:20 Faster horses vs. Real cars in AI 1:15:40 AI 2.0: Agents, experiments, and what comes next 1:22:10 The real risk ahead: Underperformance, not collapse Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we using AI in a way that actually makes us smarter or are we unknowingly making ourselves less capable, less curious, and easier to automate? On this episode of Digital Disruption, we are joined by artificial intelligence expert and neuroscientist, Dr. Vivienne Ming. Over her career, Dr. Vivienne Ming has founded 6 startups, been chief scientist at 2 others, and founded The Human Trust, a philanthropic data trust and “mad science incubator” that explores seemingly intractable problems—from a lone child’s disability to global economic inclusion—for free. She co-founded Dionysus Health, combining AI and epigenetics to invent the first ever biological test for postpartum depression and change the lives of millions of families. She also develops AI tools for learning at home and in school, models of bias in hiring and promotion, and neurotechnologies to treat dementia and TBI. Vivienne was named one of “10 Women to Watch in Tech” by Inc. Magazine and one of the BBC’s 100 Women in 2017. She is featured frequently for her research and inventions in The Financial Times, The Atlantic, Quartz Magazine and the New York Times. Dr. Vivienne Ming sits down with Geoff to unpack one of the most misunderstood truths about artificial intelligence: AI isn’t here to replace your thinking it’s here to challenge it. And whether you grow or get left behind depends entirely on how you choose to engage with it. Dr. Ming reveals why most organizations and most individuals are using AI in the worst possible way. Instead of creating leverage, they’re creating “work slop,” cognitive dependency, shallow automation, and declining human capability. She explains why the real competitive advantage in the AI age comes from productive friction, creative complementarity, and teams that know how to use AI to explore the ill-posed problems—the ambiguous, uncertain, high-value challenges machines can’t solve on their own. From how to robot-proof your company, to why AI tutors fail when they give answers, to the science of courage, reward systems, and organizational culture, this conversation is one of the most honest explorations of the future of human capability in an AI-saturated world. In this video: 00:00 Intro 02:30 The real value of hybrid intelligence 05:00 Cognitive automation vs. true complementarity 08:20 Ill-posed problems: where humans still win 12:10 What elite performers really do differently 16:00 The paradox of AI: why more automation creates more work 18:30 How hybrid teams beat prediction markets 20:50 Inequality & imagination disease in AI 23:10 AI tutors & the golden rule: never give the answer 28:00 The nemesis prompt: how to robot-proof yourself 44:20 Courage, ethics & reward structures in organizations 54:00 Using AI without losing the human story 01:06:30 How to robot-proof your company Connect with Vivienne: Website: https://socos.org/about-vivienne LinkedIn: https://www.linkedin.com/in/vivienneming/ Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

If AI is becoming a “playground” for experimentation, are today’s organizations bold enough to explore it or are they still too afraid to try? On this episode of Digital Disruption, we are joined by Kenneth Cukier, Deputy Executive Editor at The Economist and bestselling author. Kenneth Cukier is the Deputy Executive Editor at The Economist. He is the author of several books on technology and society, notably “Framers” on the power of mental models and the limitations of AI, with Viktor Mayer-Schönberger and Francis de Vericourt, as well as “Big Data: A Revolution That Transforms How We Live, Work and Think” with Viktor. It was a NYT bestseller translated into over 20 languages, and sold over two million copies worldwide. It won the National Library of China’s Wenjin Book Award and was a finalist for the FT Business Book of the Year. Kenn also coauthored a follow-on book, “Learning with Big Data: The Future of Education”. He has been a frequent commentator on CBS, CNN, NPR, the BBC and was a member of the World Economic Forum’s global council on data-driven development. Kenneth has spent decades at the intersection of AI, journalism, business strategy, and global policy. In this conversation, he sits down with Geoff to share candid insights on how AI is reshaping organizations, leadership, economics, and the future of work. He breaks down the real state of AI, what’s hype, what’s real, and what it means for workers, leaders, and companies. Kenneth explains how AI is shifting from automating tasks to expanding the frontier of knowledge, why today’s multi-trillion-dollar AI investment wave is both overhyped and underhyped, and how everything from healthcare to management is poised to transform. This episode explores why most companies should treat AI as a “playground” for experimentation, how The Economist is using generative AI behind the scenes, the human skills needed to stay competitive, and why great leadership now requires enabling curiosity, psychological safety, and responsible innovation. Kenneth also unpacks the growing “AI-lash,” the limits of GDP as a measure of progress, and why the organizations that learn fastest, not the ones that simply know the most, will win the future. In this episode: 00:00 Intro 05:00 AI Today: Overhyped, underhyped, or both? 10:00 From Big Data to LLMs: How we got here 15:00 The $3 trillion AI wave: What it really signals 20:00 Automation vs. knowledge expansion 25:00 Inside The Economist: How they actually use Generative AI 30:00 Why “more content” isn’t a strategy 35:00 Leadership in the age of AI: Curiosity, judgment, culture 40:00 The skills humans must keep and why they matter more now 45:00 The rise of the “AI-lash” and public skepticism 50:00 GDP, progress, and what we’re measuring wrong 55:00 Why the fastest learners win the future 1:01:00 What can this technology really do? Connect with Kenneth: Connect with Kenneth: Website: http://www.cukier.com/ LinkedIn: https://www.linkedin.com/in/kenneth-cukier-9ab56335/ X: https://x.com/kncukier Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What does the future of work really look like when AI, identity, and culture collide? On this episode of Digital Disruption, we’re joined by Dr. Anne-Marie Imafidon, Chair of the Institute for the Future of Work. Anne-Marie is a leading voice in the tech world, known for her work as a trustee at the Institute for the Future of Work and as the temporary Arithmetician on Channel 4’s Countdown. A former child prodigy who passed A-level computing at 11 and earned a Master’s in Maths and Computer Science from Oxford by 20, she has since spoken globally for companies including Facebook, Amazon, Google and Mastercard. She hosts the acclaimed Women Tech Charge podcast and is a sought-after presenter who has interviewed figures such as Jack Dorsey and Sir Lewis Hamilton. Anne-Marie has received multiple Honorary Doctorates, serves on several national boards, and continues to champion diversity and innovation in tech. Her latest book, She’s In CTRL, was published in 2022. Dr. Anne-Marie joins Geoff to break down how AI, big data, quantum, and the wider “Fourth Industrial Revolution” are transforming jobs, workplaces, identity, culture, and society. From redefining long-held beliefs about “jobs for life,” to the cultural fractures emerging between companies, workers, and society, Dr. Anne-Marie goes deep on what’s changing, what still isn’t understood, and what leaders must do right now to avoid being left behind. This conversation dives into why most AI use cases are still limited to fraud detection and customer service, and the hidden cultural blockers preventing real transformation. She emphasizes the danger of hype cycles, and how to stay focused on real value and how to build organizations that can experiment, learn, and make “high-quality mistakes.” In this episode: 00:00 Intro 00:31 The Future of Work: What’s changing now 02:32 Generational identity, legacy jobs & why work is no longer “for life” 04:36 Work identity crisis & fragmentation of modern careers 07:45 Rethinking digital transformation & the fourth industrial revolution 11:36 Why the institute avoids the AI hype & looks beyond it 13:39 AI Hype vs. reality 17:50 High-quality mistakes 21:06 Tech design failures 23:18 Culture, customers & building organizations that reflect the real world 29:04 Destroying the “Einstein Myth” & rewriting who tech is for 39:37 First-principles thinking 50:34 Norms, unintended consequences & system-level change 55:32 When will the dust settle? ai timelines, disruption & what’s next 57:28 Closing thoughts Connect with Dr. Ann-Marie: LinkedIn: https://www.linkedin.com/in/aimafidon/ Instagram: https://www.instagram.com/notyouraverageami/ Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG