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