Digital Disruption with Geoff Nielson

Episod

• Everything You Believe About Work is About to be Broken by AI | Alexander Manu 06.07.2026 1j 12min

  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 Intro00:46 Why everyone is afraid of AI01:01 Why Alexander isn't afraid of artificial intelligence03:02 AI, work & the future of human purpose05:24 Will AI make society happier?06:32 Why AI is different from every technology before it08:07 AI as a creative partner instead of a tool10:17 The real fear behind AI: Money & identity12:48 How do we reach an AI future?14:03 Why we need to redesign everything from scratch16:12 AI, identity & Maslow's self-transcendence19:07 Using AI to unlock human creativity20:33 Lessons from building one of the first portable computers22:34 Technology, identity & human evolution24:24 How every technology becomes normal27:07 AI learns you as you learn it28:57 Why technology exists to eliminate friction30:19 Why society needs to embrace AI earlier31:44 Understanding the disruption continuum34:10 Why disruption never ends39:45 Are we living through an AI bridge moment?42:06 Why most companies get AI completely wrong46:31 Stop fitting AI into old systems51:30 The biggest AI lessons for business leaders53:12 The question every organization should ask56:09 Leadership, AI & the future of organizations59:18 Why AI is not optional1:00:52 AI's true promise isn't speed1:05:36 AI, contemplation & finding meaning1:06:36 Social media, creativity & human attention1:11:48 Final thoughtsConnect 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=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG
• Will AI Take Your Job? Dag Kittlaus Separates Hype from Reality 29.06.2026 1j

  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 Intro00:53 Co-creator of Siri01:15 AI's promise vs. AI's peril02:28 Capability vs. diffusion: The real AI challenge03:15 Why AI still can't replace entire jobs04:31 Will AI cause massive white-collar job loss?07:14 Why laying off employees for AI is a mistake08:14 How businesses should actually adopt AI10:30 How Dag personally uses AI today12:41 AI investment trends and opportunities13:27 What's next for AI infrastructure and data centers?15:27 Hidden AI opportunities most investors miss16:41 Winners and losers in the AI economy17:56 How leaders should prepare their organizations21:32 AI-first startups vs. large enterprises23:11 Should established companies fear AI-native competitors?24:00 Ignore AI and you're in trouble25:21 The 10-year AI adoption timeline26:22 Is AI ready or does it need more breakthroughs?28:00 The original vision for Siri29:30 AI agents, APIs, and autonomous assistants31:32 Why apple lost ground in AI34:53 Dag's vision for the future of Siri35:29 The 'Conductor Thesis' for personal AI38:30 Why personalization Is AI's missing link39:07 Consumer backlash against AI40:20 Why AI job loss fears are overblown41:15 AI, productivity growth, and the four-day workweek43:51 How to change public perception of AI47:05 Convincing employees to embrace AI47:50 Why incentives matter more than mandates50:05 Practical advice for business leaders53:03 The biggest AI trend nobody understands53:38 How AI will transform healthcare56:11 AI regulation and innovation challenges58:23 Why Dag is optimistic about AI's future59:15 Final thoughts#ai #futureofwork #leadership #siri #apple #futureofai #technologypodcast #digitaltransformation #innovation #entrepreneurship #futureofjobs #stevejobs #dagkittlausConnect with Dag:LinkedIn: https://www.linkedin.com/in/dagkittlaus/X: https://x.com/dagkOur 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
• AI is Breaking the Economy and Education. Here's How to Fix it 22.06.2026 1j 13min

  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 203004:05 Why education must be rebuilt for the AI era07:12 Teaching critical thinking, data literacy & adaptability10:40 How work changes in the age of AI13:22 Why people should be treated as assets, not costs16:16 The economic model that no longer works20:24 Rethinking value, GDP, and the future economy24:23 Can we actually value people and data?27:29 Why governments need an AI consortium28:54 AI, data ownership & wealth distribution33:05 Should AI and cloud computing be treated as utilities?35:45 Why most organizations mismanage data37:05 Treating data as a business asset42:53 Why AI can't fix bad data47:27 What data-mature organizations do differently48:05 Schneider electric's data monetization strategy50:24 John Deere's AI and data advantage51:21 The ethics of data monetization55:28 Workforce transformation and leadership in the AI era58:29 Why leaders struggle with long-term thinking01:00:00 Leadership, risk, and better decision making01:03:48 Rethinking leadership for the Intelligence Economy01:06:19 Human wisdom vs machine knowledge01:09:23 Final advice for leaders adopting AI01:12:14 Final thoughtsConnect 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=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG
• The Most Insidious AI Narrative: We Can't Shape the Future 15.06.2026 1j 8min

  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 Intro01:25 Why Charlie Tyrell & Ted Tremper made the film02:20 The origins of The AI Doc04:45 AI anxiety, parenthood & the future06:57 Wealth inequality and AI concentration08:17 Reasons for hope and concern11:01 How individuals can shape AI's future11:49 Why education creates agency13:02 AI's impact on artists and creators15:12 Did The AI Doc use AI?16:56 Human creativity vs AI-generated content18:14 The filmmaking industry's AI debate19:20 Generative AI and storytelling21:23 Audience demand and the future of human-made art23:13 Technology's impact on creativity throughout history24:50 Ethical AI, consent & compensation27:02 Can AI ever be ethical?28:12 Policy, regulation & AI accountability30:59 The AI arms race explained32:14 AI competition, China & global innovation34:07 AI narratives we should question35:00 The Myth of AI Inevitability37:08 Democratizing AI and power structures38:11 What AI advocates get wrong40:40 Radical imagination & AI governance42:45 What gives Charlie and Ted Hope?46:22 Raising children in an AI world51:56 Technology, optimism & intellectual humility55:00 The most influential voices in AI57:39 Karen Hao, Deborah Raji & human-centered AI1:00:08 Responsible AI use for business leaders1:02:13 Fighting over-optimization and AI dependence1:04:19 The hidden risks of AI services1:07:12 Final Thoughts Connect with The AI Doc:X: https://x.com/theaidocfilmInstagram: https://www.instagram.com/theaidocfilm/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
• Joscha Bach: AGI, Consciousness, and the Evolution of Intelligence 08.06.2026 1j 29min

  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 Intro01:04 AI doom scenarios & humanity's future02:00 Defining intelligence & consciousness05:00 Why AI intelligence is different from human intelligence06:52 Are LLMs actually intelligent?08:10 Why AI hallucinates10:09 Human learning vs machine learning11:22 Can transformers lead to agi?12:28 The scaling hypothesis explained13:58 Mechanistic interpretability & neural networks15:13 Can AI surpass human understanding?18:42 AI and the future of scientific discovery20:14 Why scientific progress feels slower today22:03 Institutions, incentives & organizational decline25:05 Trust in government and society28:31 Can AI improve democracy?30:40 Why AI gets such negative media coverage33:03 The AI extinction debate36:30 AI, automation & the future of jobs40:05 Big Tech, AI power & capitalism41:15 Money, markets & resource allocation46:28 Regulation, innovation & economic growth49:13 Why innovation is slowing down51:08 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 stability01:08:27 Regulation, governance & innovation01:10:33 Lessons from Berlin's innovation culture01:16:08 AI, surveillance & centralized power01:18:07 Decentralized AI and individual empowerment01:20:05 AI, healthcare & professional expertise01:23:36 Control, society & human responsibility01:25:00 Advice for leaders and innovators01:26:03 Escaping filter bubblesConnect with Joscha Bach:LinkedIn: https://www.linkedin.com/in/joschabachX: https://x.com/PlinzOur 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
• AI vs The Invasion of Work: Could We Take Back Our Lives? 01.06.2026 1j 5min

  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 Intro00:01:15 Will AI replace white-collar jobs?00:02:29 Why AI is a reimagination of work, not doom & gloom00:03:08 Human-led, agent-operated work00:03:37 The broken reality of modern office work00:04:36 Digital overload, meetings & workplace chaos00:06:16 Human agency vs AI agents00:07:33 Using AI to redesign your job00:09:02 Why the best AI users don’t outsource judgment00:09:49 Delegation, intentional AI use & skill preservation00:10:54 AI as a team member, not just a tool00:11:27 The four ways people use generative AI00:14:10 The rise of AI agents in the workplace00:16:16 From personal productivity to organizational transformation00:17:10 Where is the ROI from AI?00:18:02 Why AI adoption alone fails00:20:13 Finding the highest-leverage AI opportunities00:23:27 Re-architecting work in the AI era00:25:27 Should employees build their own AI agents?00:28:39 AI-native organizations vs legacy enterprises00:30:05 AI adoption vs AI absorption00:32:31 Discovering hidden business value through AI00:33:27 How legacy firms can compete with AI-native companies00:35:06 Why AI transformation starts with culture00:36:05 The role of HR, CEOs & leadership in AI strategy00:39:14 Why AI is bigger than a technology initiative00:41:12 The expanding role of the C-Suite in AI transformation00:46:32 Microsoft’s “learn it all” leadership culture00:50:00 Democratizing innovation with AI00:53:23 Tacit knowledge & AI-powered learning00:57:09 Information retrieval, organizational knowledge & AI00:59:37 Capturing institutional intelligence with AI01:00:03 Advice for business & technology leaders01:03:17 Why there is no AI playbook yetConnect with Matthew:LinkedIn: https://www.linkedin.com/in/matthewloysduncan/X: https://x.com/matthewloysOur 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
• The AI Delusion: Why CEOs Still Don’t Get It 25.05.2026 1j 24min

  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 Intro01:00 Why great companies “go bad”02:10 The rise of corporate corruption05:48 Is capitalism itself the problem?07:08 Making money without creating value10:33 Corporate accountability & human flourishing13:06 Why this problem keeps getting worse18:21 How investors destroyed FedMart21:22 Why Costco defies wall street logic23:00 Financialization & the collapse of institutions24:27 How leaders can protect mission-driven companies27:12 “Financial gravity” explained31:10 Trustworthiness as a business asset34:37 Governance structures that actually work36:20 Transitioning into AI & the future of work37:42 AI governance & Anthropic38:37 The AI alignment problem41:30 Why AI is being optimized for cost cutting42:15 AI should augment creativity, not replace humans44:04 How to use AI as a learning tool46:34 Real examples of AI augmentation done right49:47 AI-assisted reading & learning50:22 The problem with AI-generated “slop”54:58 Why human-made work will become premium57:19 The future of the attention economy59:12 Will AI become addictive like social media?01:00:03 The case for an AI Bill of Rights01:04:11 Costco, DEI & organizational integrity01:07:13 AI Regulation, governance & human flourishing01:13:24 Fighting the “normative consensus” of shareholder primacy 01:21:21 Is the era of shareholder primacy already over?01:22:22 Final thoughtsConnect with Eric:LinkedIn: https://www.linkedin.com/in/eries/X: https://x.com/ericriesOur 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
• 4 Waves of AI (We're on Wave 2) 18.05.2026 1j 19min

  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 Intro01:04 The “Augmented Age”: Humans + AI working together02:10 Sci-Fi to reality: Talking to computers like Star Trek04:11 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” principle08:57 Amara’s Law: Short-term hype vs long-term impact10:08 Why AI will be bigger (and slower) than expected10:54 The 4 Waves of AI explained11:00 Wave 1: “Interesting but not useful” AI12:31 Wave 2: Grassroots AI (hidden ROI inside companies)13:16 Why CEOs can’t see AI ROI14:09 Tool users → tool makers (the real shift)16:17 The invisible productivity explosion20:10 Wave 3: AI agents & ecosystems21:48 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 innovation33:09 Building the right AI infrastructure layer34:45 Where should companies invest in AI?37:14 Start with the problem, not the technology40:04 Toolset vs skillset vs mindset42:45 Why mindset & culture matter most44:28 The race to the bottom vs innovation45:15 New workplace norms & ethical questions49:49 Why culture changes slowly51:33 Tech vs culture: A fundamental tension52:30 Can organizations adapt to constant change?56:06 The myth of big, sexy AI57:01 Small AI, massive impact58:18 Where real innovation is happening59:13 Why young workers lead AI adoption01:01:22 Advice for leaders01:02:59 AI is a “Lord of the Rings” journey01:05:15 Will AI replace jobs?01:10:23 Lessons from past tech revolutions01:13:47 Why humans need ~25 years to adapt01:16:02 Why expectations rise with technology01:17:38 Why there will always be more work to do01:18:55 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=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG
• Top Tech Advisor: Every CEO Is Getting AI Wrong 11.05.2026 1j 8min

  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 Intro01:30 Is “this time different” with technology?02:29 The Big Shift: Why organizations must fundamentally change03:18 Scalable efficiency vs scalable learning05:33 The dangerous AI narrative: automation & job cuts06:19 Why efficiency alone leads to diminishing returns09:42 Trust: The missing foundation in most organizations10:50 What happens when companies fail to adapt12:21 Debunking AI myths and media narratives12:46 Humans vs machines: who should do what?13:14 Reskilling vs building human capabilities15:03 How to convince leaders to rethink AI strategy16:24 Fear vs opportunity in leadership20:16 What real workplace learning looks like21:18 The future leader: asking better questions24:38 How to structure high-impact teams26:06 The collapse of trust in institutions26:58 Corporate narratives & Apple’s “Think Different”30:06 Creativity vs technology in strategy30:41 Zoom Out, Zoom In strategy explained33:08 Microsoft example: seeing the future early35:14 Why agility without direction fails37:21 Understanding “the edge” and innovation39:34 Why transformation efforts fail in large companies41:22 Scaling the edge vs top-down change42:52 The power of the “explorer mindset”47:18 Why companies suppress passion48:31 Only 14% of workers are truly passionate50:18 Can passion be cultivated at scale?52:29 Does IT still matter in the AI era?55:07 AI, healthcare, and the future of longevity57:13 From healthcare to “wellness ecosystems”58:19 The rise of the trusted advisor59:50 Can AI replace human advisors?01:02:25 Advice for leaders01:04:18 AI is a tool humans determine its impact01:06:29 Why most digital transformations failConnect with John:LinkedIn: https://www.linkedin.com/in/jhagel/X: https://x.com/jhagelOur 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
• AI Bust: Oxford Economist on Why the AI Boom Will Be Short-Lived 04.05.2026 1j 3min

  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 Intro00:57 Why the “AI Abundance” narrative might be wrong01:45 Lessons from the computer revolution & productivity slowdown03:30 AI vs computers: Automating cognition vs information05:19 Why Big Tech may be overhyping AI impact06:20 Automation vs creating new industries08:08 AI infrastructure race: US vs China10:25 The “Steam Engine Moment” AI hasn’t reached12:31 Why technology alone isn’t enough14:19 Why breakthrough innovation is declining15:09 The collapse of business dynamism15:45 Corporate lobbying, patents & barriers to entry17:27 Why this matters more than AI itself18:20 Startups vs Big Tech: Who drives innovation?19:36 Will AI accelerate economic inequality?21:37 Lessons from the Gilded Age & Antitrust History24:04 Why strong governments enable competition25:00 Big Tech vs historical monopolies26:19 Centralization vs decentralization in innovation29:01 Japan vs US33:56 AI and the “more vs better work” problem35:20 Will AI lower quality in research & knowledge?36:23 AI: Increasing quantity vs improving quality38:16 Why AI benefits low-skill workers more39:49 AI and the rise of global labor competition40:42 AI-driven offshoring42:17 Which jobs are most at risk?44:06 Long-term labor market predictions46:20 Where humans still beat AI48:15 The growing anti-AI backlash49:11 Historical resistance to technology 53:39 Can government reduce AI disruption?56:01 Why institutions determine outcomes59:25 Advice for business leaders01:00:12 Why decentralized companies win01:02:24 Why innovation requires “waste”Connect with Carl:LinkedIn: https://www.linkedin.com/in/carlbfrey/X: https://x.com/carlbfreyOur 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
• AI Revolution or Collapse: EY's AI Leader on 4 Futures of Work in 2030 27.04.2026 1j 4min

  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 Intro00:40 Inside SXSW: Future-proofing AI strategy02:14 Why predicting AI is impossible 02:56 The four AI futures explained (constraint → collapse)04:36 What winning teams did differently05:50 The “sameness trap” in AI06:19 Positive vs negative AI futures07:23 Constraint, growth, transform, collapse09:54 What people actually believe about AI’s future10:45 How do you win with AI?13:17 Why business model innovation beats automation14:02 Hands-on AI15:46 How AI commoditizes output 17:01 AI investment trends: Productivity vs differentiation18:13 The shift toward competitive advantage with AI19:27 The AI Playbook: How leaders get it right20:34 Going broad vs going deep with AI21:11 88% vs 5%: The AI Adoption Gap22:20 Mindset vs skillset vs toolset23:27 Top-down vs bottom-up AI transformation25:16 The visibility trap explained26:06 Why new talent drives AI innovation28:22 AI resistance & fear in organizations29:43 “Death by a Thousand Papercuts” automation30:54 New jobs: Knowledge Engineers & AI Orchestrators32:48 Future Skills: Critical thinking, creativity, systems thinking35:12 The role of IT in the AI era37:34 AI as the new operating system of business39:01 SaaS vs A44:35 AI prototyping vs enterprise-scale systems47:18 Will AI kill consulting?54:07 AI infrastructure constraints & global risks56:09 Biggest AI myths & misconceptions57:34 Are we automating the wrong things?59:27 Amara’s Law & AI hype cycles01:00:12 How leaders should prepare01:01:01 Why value creation beats cost cutting01:02:17 Aligning AI strategy across the organizationConnect 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=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG
• Jobs After AI: Futurist Ian Beacraft on What Happens When AI Does All the Work 20.04.2026 1j 3min

  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 Intro01:20 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 techConnect with Ian:LinkedIn: https://www.linkedin.com/in/ianbeacraftX: https://x.com/ianbcraftInstagram: https://www.instagram.com/ianbcraft/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
• Ex-Twitter AI Ethicist Warns: The 2016 Data You Forgot About is Now Dangerous 13.04.2026 1j 14min

  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 Intro01:16 What’s wrong with AI today02:18 Why people trust AI less every year03:09 Big tech vs the technology itself04:22 Dangerous narratives about AI06:09 Anthropomorphism and moral outsourcing07:40 The myth of AGI and profit motives09:20 The economics behind AI power11:21 Consumer responsibility and the privacy paradox13:42 “I have nothing to hide” explained15:04 How big tech is consolidating control16:42 What consumers should actually do18:30 Real-world consequences of data misuse21:05 From Pokémon Go to surveillance systems22:29 The dilemma of social media and platforms26:05 Can AI still be used for good28:20 Algorithms, manipulation, and loss of agency30:12 Inside AI ethics at Twitter33:48 Why leadership and trust are changing35:17 Surveillance capitalism and public backlash37:31 How to think strategically about AI41:19 Finding agency and intentional use of AI45:06 Will society push back against AI power52:02 The role of AI ethicists and builders56:41 The future of work and automation reality01:01:32 Why expertise and discernment matter most01:06:35 Advice for business leaders using AI01:11:33 Final thoughts on agency and discernmentConnect with Dr. Rumman Chowdhury:LinkedIn: https://www.linkedin.com/in/rumman/Instagram: https://www.instagram.com/rumman_c/?hl=enOur 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
• The AI Comet Has Struck: Moonshots' Salim Ismail Warns Most Organizations Won't Survive AI 06.04.2026 1j 54min

  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 Intro01:00 What’s actually going exponential right now03:30 The convergence of multiple exponential technologies05:00 Space tech breakthroughs & $6M rocket launches06:30 Data centers in space & infinite compute07:45 From scarcity to abundance: the big shift10:30 Real-world examples: music, communication, and industry disruption12:45 The “messy decade” before the future gets better14:00 Why institutions are breaking down (government, media, education)15:30 Star Trek vs mad max: two possible futures17:00 Why humans fear AI 20:00 Why technology is still humanity’s biggest advantage23:00 Will AI take your job?25:00 The ATM example: why jobs don’t disappear26:30 AI organizations and 80% workforce reduction myth28:30 The future of companies: small teams, big impact30:00 The rise of the creative economy32:00 Why human experience becomes more valuable34:30 AI and human experts (doctors, teachers, consultants)37:00 Which industries will be disrupted first40:00 Why governments are falling behind41:30 How to actually innovate46:30 What leaders must do right now50:00 What is an exponential organization?52:30 “What do I do on Monday?” practical advice57:00 The only strategy that works59:00 AI startups & the future of entrepreneurship01:02:00 Why most companies will fail to adapt01:06:00 How to increase organizational speed01:10:00 Leadership in the age of exponential change01:15:00 The future of nations vs cities01:20:00 Remote work vs in-person work01:25:00 Robots, AI, and the coming inner loop01:26:30 Why AGI is misunderstood01:32:00 What most people get wrong about the future01:34:00 Fixing civilization & human evolution01:37:00 Psychedelics, creativity, and human potential01:42:00 AI solving science and R&D autonomously01:48:00 Raising kids in an AI world01:52:00 The risk of losing human connection01:53:00 Where we’re headedConnect with Salim:LinkedIn: https://www.linkedin.com/in/salimismail/X: https://x.com/salimismailOur 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
• AI is Losing Ground: Futurist Brian Solis on Why AI Adoption is Failing 30.03.2026 55min

  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 Intro00:55 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 why10:50 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 takeawaysConnect with Brian:LinkedIn: https://www.linkedin.com/in/briansolis/X: https://x.com/briansolisInstagram: https://www.instagram.com/briansolis/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
• The End of Wisdom: Chip Conley on AI and the Decline of Leadership 23.03.2026 1j 4min

  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 Intro00:27 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 ever02:30 AI, intelligence, and the limits of answers03:16 Why AI can’t ask the right questions (yet)04:06 Human intuition, storytelling, and experience06:19 Is AI a useful tool for leaders?07:06 How to use AI effectively as a leader07:43 Efficiency vs. soulfulness in work09:18 The human + AI partnership 11:27 What is “soulfulness” in leadership?14:10 Leadership, agency, and accountability15:30 Leaders as resource allocators17:17 Great leaders create future leaders18:29 Defining soulfulness: Empathy, intuition & connection20:19 Why soulful leaders feel different21:36 Is society losing its soul?22:25 Why scarcity makes wisdom more valuable24:27 Leadership, culture, and emotional contagion27:04 “Win at All Costs” vs. soulful leadership28:16 Is being human a weakness in business?29:53 The return of philosophy, ethics & humanities31:09 Why wisdom is making a comeback34:23 The future of work and what changes37:31 AI as a partner, not a replacement38:20 New careers: Coaches, curators & meaning makers39:04 What is Wisdom?42:18 Viktor Frankl & the equation for meaning44:24 Purpose vs. meaning explained46:47 Growth mindset vs. Know-it-all culture49:32 Turning pain into wisdom 50:29 The Midlife “U-Curve” of happiness53:21 The “Diet of Despair” in modern media59:19 Advice for young people in the AI era01:02:10 Why usefulness matters more than youthConnect with Chip:LinkedIn: https://www.linkedin.com/in/chipconleysf/X: https://x.com/ChipConleyInstagram: https://www.instagram.com/chipconley/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
• AI Convergence: Amy Webb On Why This is the Year of Creative Destruction 16.03.2026 58min

  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 era05:04 Systems-level change vs trend stacking06:19 From AI winters to generative AI breakthroughs07:27 Power shifts: OpenAI, Microsoft, Google & Competitive Dynamics08:31 Winners vs losers in the convergence economy09:26 Fear, FOMO & leadership paralysis12:17 Rethinking regulation & geopolitical power shifts15:40 Why “Future-Proofing” is a myth17:14 AI capital flood: Is there a bubble?19:25 Enterprise AI & the 80% workforce threshold23:27 The attention economy & AI hype27:28 Where AI actually creates real impact28:11 Programmable biology & DeepMind’s Evo 230:00 Climate solutions, agriculture & synthetic biology31:59 Dolly the Sheep & why transparency matters38:19 mRNA, public trust & technology communication40:15 The polycompute future: AI + quantum + biological computing41:01 Quantum computing’s business implications42:20 Brain organoids & biological computers46:48 Creative destruction: What must die for you to survive?49:00 Why evolution isn’t enough anymore51:47 Why leaders avoid dangerous conversations52:39 Strategic foresight & data-backed vision56:36 Why AI navel-gazing is procrastination57:23 Leadership in an age of convergenceConnect with Amy:LinkedIn: https://www.linkedin.com/in/amywebb/X: https://x.com/amywebbInstagram: https://www.instagram.com/amywebbfuturist/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
• Will AI Replace Software Engineers? Here’s What an Engineering Leader Says 09.03.2026 1j 2min

  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 Intro00:57 Why this is the most pivotal moment in tech02:21 Bridging the AI dreamers and skeptics03:18 Productivity vs. value creation04:44 Vibe Coding: Hype vs. reality05:27 Democratizing software development06:09 Prototyping vs. production code08:17 Will AI reduce the need for engineers?12:25 What engineers should focus on now13:59 Curiosity as a core engineering trait15:34 Why engineers must be close to customers17:28 Feature slop & intentionality20:39 Lyft’s real-time AI design workflow (cursor example)23:32 When AI is (and isn’t) truly real-time25:18 Custom AI vs. out-of-the-box tools26:55 Data ethics, privacy & governance in ai29:04 A framework for sensitive data31:18 Why leaders must act before regulation32:38 AI Hype: Utopia vs. doomsday narratives36:23 Culture as a competitive advantage38:55 What makes a great engineering leader40:42 Common mistakes new tech managers make45:19 From “sell” to “tell”47:55 Leading hybrid & remote engineering teams49:46 The 10x (or 100x?) engineer debate53:29 Advice for young engineers55:23 The future of work56:55 Bridging the digital divide58:51 “Give Before You Take” philosophyConnect with Bala:LinkedIn: https://www.linkedin.com/in/balaarjunan/X: https://x.com/balaarjunanOur 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
• Ex-Ancestry CEO: How AI is Forcing Companies to Rethink Everything 02.03.2026 1j 22min

  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 Intro01:00 What Being a CEO Means in 202606:30 Rebuilding a legacy company for the AI era07:20 Facebook’s mobile-first pivot (stock price crisis)10:45 The power of top-down buy-in12:00 Big bets vs incremental change15:00 The “Future Us” decision-making framework19:35 How to build great products21:00 Fall in love with the problem, not the solution22:45 AI: Blessing or curse for product teams?24:30 AI governance, security & data risks26:45 Are developers becoming obsolete?28:30 Why senior engineers are more valuable in AI30:00 Should CEOs own AI strategy?34:30 Magic wand dinners & listening as a leader36:00 Remote work vs in-person culture40:00 Breaking the CEO archetype44:00 Failure as a career advantage47:00 Communication is 80% of leadership51:00 Why experts often fail as managers53:30 Building a culture of innovation58:00 Scaling infrastructure to unlock product velocity 1:10:00 Parenthood & career stalls (the honest truth)1:15:00 Networking for introverts1:20:00 Adaptability: The most important skill of the next decade1:21:30 Closing thoughtsConnect 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=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG
• LLMs in 2026: What’s Real, What’s Hype, and What’s Coming Next 23.02.2026 1j 14min

  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 Intro01:23 The Rise of “Reasoning” and Thinking Models03:06 Inference scaling vs training scaling06:17 What LLMs are actually good (and bad) at07:09 The “Strawberry” Problem and Reasoning Limits09:00 Tool use and why LLMs don’t need to count letters10:20 Math Olympiads & self-refinement techniques12:01 Why coding is the killer use case13:28 Does AI make developers obsolete?18:02 The Reality of 10x developer productivity claims21:43 Generalist vs specialized models23:53 Build from scratch vs fine-tune vs API prompting25:01The true cost of training an LLM27:33 API customization vs owning your model29:12 Who should build an LLM from scratch?33:16 Data requirements & why you need terabytes34:28 Enterprise data challenges35:40 Retrieval-Augmented Generation (RAG) explained46:05 Multi-agent systems & tool calling49:48 The problem with LLM benchmarks55:43 Using LLMs as judges58:00 Biggest misconceptions about LLMs1:04:19 Reinforcement learning with verifiable rewards1:06:32 Advice for technology leaders1:11:48 Escaping AI hype through fundamentalsConnect with Sebastian:LinkedIn: https://www.linkedin.com/in/sebastianraschka/X: https://x.com/rasbtConnect 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