Digital Disruption with Geoff Nielson

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance. Check it out here: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=cio-analytics-youtube-organic

As AI reshapes work, help your team build the human judgment and practical skills to adapt with McLean & Company’s Human-Centric AI Program here: https://hr.mcleanco.com/training/programs/human-centric-ai?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruption

What if we can never fully predict or understand AI and need to rethink how we use it?

Stephen Wolfram, creator of Mathematica and Wolfram|Alpha, explains why artificial intelligence remains fundamentally unpredictable and how we can make it useful despite those limits.

Stephen joins us to discuss large language models, AI-generated code, and the difference between generating convincing answers and performing precise computation. He explains how combining generative AI with computational tools can help bridge that gap and why understanding what you’re building matters more as automation advances.

The conversation also explores how AI could transform cybersecurity, powering both attacks and defenses. Stephen considers how these increasingly complex interactions could outpace human understanding and what that means for oversight and AI transparency. He explains why safeguards need to operate outside the AI itself to limit the consequences of unpredictable behavior.

Follow for more conversations about AI, technology, innovation, and digital transformation.

In this episode:

00:00 AI beyond human understanding

01:29 AI hype vs. long-term potential

05:35 ChatGPT and natural language interfaces

06:47 Combining generative AI with Wolfram Language

08:41 CIO Analytics: API-Driven Advisory

10:00 Understanding the world through computation

13:17 How Simple rules create complex behavior

16:15 Human-like AI vs. precise computation

21:08 Why AI struggles with 100% accuracy

22:39 McLean & Company’s Human-Centric AI program

23:37 Where AI works and where it falls short

27:17 The risks of AI-generated code

29:49 Why understanding matters more than implementation

33:51 Can we understand AI’s black box?

36:37 Computational irreducibility explained

39:49 Why AI needs external guardrails

42:08 The limits of AI control

43:25 AI-powered cyberattacks and defenses

45:03 Automation and the future of work

49:48 How Wolfram research uses automation

54:00 AI coding and the rise of small software tools

55:57 Choosing what to build when more is possible

59:58 Finding value as an AI startup

01:01:33 Leading innovation at Wolfram research

01:07:47 Bringing Wolfram|Alpha to life

01:10:48 Why managing scientific research is different

01:13:01 Building teams that think broadly

01:15:07 Matching people to projects and preserving their work

01:19:30 Advice for founders: Build something you want

01:21:03 Why CEOs need to understand their business

01:24:03 Hiring beyond the polished interview

01:26:15 Final thoughts

01:27:02 About Infotech

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

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionnow.

Tech moves fast. So does work. Digital Disruption NOW helps you keep up and make sense of what matters.

Coming to you from the Masonic Temple, Digital Disruption NOW is the latest podcast in the Digital Disruption network, bringing you a weekly take on tech, work, and what it all means. We break down the biggest headlines, debate the hottest topics, and explore how technology is changing the way we live and work. From the news everyone’s talking about to the developments you might have missed, get real perspectives and insights you can actually use.

All signal. No static. An Infotech production.

Is AI delivering real business value, or just bigger promises?

Geoff and Jeremy break down Anthropic’s IPO prospectus, debate AI productivity and ROI beyond Big Tech, and examine OpenAI’s claims about modernizing legacy COBOL systems.

From Claude’s growth and AI bubble risks to the gap between faster tasks and measurable business results, explore what the headlines mean for tech and work.

In this episode:

00:00 Intro: AI, productivity, and the guacamole problem

00:28 Welcome to Digital Disruption NOW

00:59 Anthropic’s IPO prospectus: promises and risks

03:58 Anthropic’s finances: revenue, losses, and profitability

06:28 Can Claude justify Anthropic’s valuation?

11:48 AI bubble risks and an interconnected tech economy

17:12 Anthropic IPO: final takeaways

18:08 CIO Analytics: a single platform to run IT

19:16 Apollo’s AI payoff report: Big Tech vs. everyone else

20:46 The AI productivity paradox

23:23 Is AI investment being measured in the right companies?

26:41 Will more AI actually improve productivity?

29:08 Why individual time savings don’t guarantee business growth

33:20 Is AI becoming essential to staying competitive?

34:52 Can OpenAI solve the COBOL code crisis?

36:59 Why rewriting code isn’t the same as replacing systems

38:03 The reality of legacy mainframe migration

40:35 The doorman fallacy: what automation overlooks

42:09 Why institutional knowledge still matters

43:23 Episode recap and closing credits

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

Check out other episodes from the Digital Disruption podcast: https://youtube.com/playlist?list=PLIImliNP0zfxRA1X67AhPDJmlYWcFfhDT&feature=shared

AI promises to transform the economy. When will that promise translate into measurable business growth?

Entrepreneur and Silicon Valley Girl creator Marina Mogilko explores the gap between AI hype and economic impact, sharing where she sees opportunities for businesses, workers, and entrepreneurs.

Marina joins us to discuss AI productivity, entrepreneurship, and the future of work. She examines why AI’s economic contribution remains difficult to measure, even as it helps small teams do more and creates new revenue opportunities.

Drawing on her own experience, Marina explains how AI could lower the barriers to starting a business for solopreneurs and women entrepreneurs. She also questions the idea of a one-person billion-dollar company.

From organizing company data to building targeted AI agents, the conversation explores what it takes to turn AI adoption into business value. Marina shares why experience, strategic thinking, and accountability remain essential, and how leaders can prepare their teams for sustainable growth.

Follow for more conversations about AI, technology, innovation, and digital transformation.

In this episode:

00:00 Intro

01:04 Why AI’s economic impact is hard to measure

04:16 The case for optimism about AI

05:49 How AI is changing tasks and productivity

09:24 CIO Analytics: API-Driven IT Advisory

10:15 Turning AI productivity into new revenue

13:16 Lowering the barriers to entrepreneurship

14:43 Can one person build a billion-dollar company?

17:18 The AI agents marina uses in work and life

20:19 Which tasks are worth automating?

23:32 Why better AI results start with organized data

28:28 How AI can reinforce bad business decisions

30:53 Using AI as a data analyst while keeping human judgment

32:01 Building an authentic brand without chasing AI doom

37:44 Making AI useful and accessible to more people

40:23 Women, AI adoption, and the need for relatable use cases

46:49 Why education still matters in the AI era

49:29 Questioning AI predictions and taking responsibility

53:10 Lessons on entrepreneurship and long-term success

55:55 Avoiding burnout and knowing when to pivot

59:20 Finding the confidence to change careers

1:00:52 Why telling your team to “Use AI” isn’t enough

1:02:50 Building entrepreneurial teams and managing AI agents

1:04:55 Lead AI adoption from the front

1:05:36 McLean & Company’s Human-Centric AI Program

Connect with Marina:

LinkedIn: https://www.linkedin.com/in/marinamogilko/

Instagram: https://www.instagram.com/siliconvalleygirl/

X: https://x.com/siliconvalleymm

Facebook: https://www.facebook.com/marina.mogilko

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

If AI can free up half a company’s labor capacity, what happens to the people doing the work?

Ravin Jesuthasan describes AI transformations that have freed up 40–50% of labor capacity. Is your organization ready for what that means for its workforce?

The futurist and bestselling author explains how AI is reshaping the future of work and why its productivity gains don’t have to translate into layoffs.

Ravin joins Geoff on this episode of Digital Disruption to discuss generative AI, AI agents, and the impact of automation on jobs. He explains why entry-level roles are under pressure, how traditional career paths are changing, and why judgment, empathy, and curiosity are becoming increasingly valuable.

Drawing on examples from Standard Chartered and Unilever, he explores how organizations can prepare employees for new opportunities through upskilling and reskilling. He breaks down what it means to build a skills-powered organization where learning becomes part of everyday work.

Ravin also shares how leaders can reinvest AI productivity gains in employee wellbeing, better customer experiences, and continued innovation.

Follow for more conversations about AI, technology, innovation, and digital transformation.

In this episode:

00:00 Intro

00:40 AI frees up half the work. what happens next?

01:12 How AI is reshaping the future of work

03:30 How AI changes the cost of work and access to talent

06:23 Will AI replace all human work?

09:40 Is the fear of becoming obsolete justified?

12:12 McLean & Company’s human-centric AI program

12:52 AI and the erosion of the entry-level career ladder

17:32 What does “work ready” mean in the age of AI?

19:51 Why human judgment is becoming an essential skill

20:58 How to build a skills-powered organization

23:20 Making learning part of everyday work

24:38 Reskilling employees for new career opportunities

26:23 Turning workforce transformation into action

29:56 Setting a vision and proving ROI with focused pilots

32:15 Who should own workforce transformation?

33:35 Involving employees and preparing them for what comes next

35:12 Unilever’s approach to reskilling and career transitions

36:43 Why digital transformations fail

39:17 Moving from one-time transformation to continuous reinvention

41:16 Making space for learning and employee wellbeing

42:34 How to reinvest AI’s productivity gains

45:44 Why IT, HR, and business leaders need to work together

48:15 Why adding AI isn’t enough to transform work

51:12 The value of outside perspectives in AI transformation

53:13 Final Advice: Learn, unlearn, and relearn

54:40 About Infotech

Connect with Ravin:

LinkedIn: https://www.linkedin.com/in/ravinjesuthasan/

X: https://x.com/RavinJesuthasan

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 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