Digital Disruption with Geoff Nielson

The AI Delusion: Why CEOs Still Don’t Get It

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

4 Waves of AI (We're on Wave 2)

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

Top Tech Advisor: Every CEO Is Getting AI Wrong

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

AI Bust: Oxford Economist on Why the AI Boom Will Be Short-Lived

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

AI Revolution or Collapse: EY's AI Leader on 4 Futures of Work in 2030

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