Digital Disruption with Geoff Nielson

What if everything we’ve been told about AI and the future of work is wrong?

John Hagel says most leaders are asking the wrong questions:
“How fast can we automate?”
“How many jobs can we cut?”

According to him, that’s a “going out of business strategy.”

In this episode, we sit down with Silicon Valley veteran John Hagel, an advisor to firms like McKinsey, BCG, and Deloitte, to challenge the dominant narrative around AI, automation, and job elimination. He shares insights into how leaders are approaching AI today, often focusing on cost-cutting and workforce reduction, and what that means for the future of business and entrepreneurship.

John explains that the real opportunity with AI isn’t efficiency, it’s learning. He talks about the shift from scalable efficiency to scalable learning and how organizations can use AI to augment human potential, unlock creativity and curiosity, and build cultures rooted in trust, collaboration, and continuous improvement.

If you’re thinking about the future of work, this episode will challenge how you view AI, strategy, and innovation, and offer a different perspective on AI’s role in the modern economy.

Like and follow for weekly episodes.

In this episode:
00:00 Intro
01:30 Is “this time different” with technology?
02:29 The Big Shift: Why organizations must fundamentally change
03:18 Scalable efficiency vs scalable learning
05:33 The dangerous AI narrative: automation & job cuts
06:19 Why efficiency alone leads to diminishing returns
09:42 Trust: The missing foundation in most organizations
10:50 What happens when companies fail to adapt
12:21 Debunking AI myths and media narratives
12:46 Humans vs machines: who should do what?
13:14 Reskilling vs building human capabilities
15:03 How to convince leaders to rethink AI strategy
16:24 Fear vs opportunity in leadership
20:16 What real workplace learning looks like
21:18 The future leader: asking better questions
24:38 How to structure high-impact teams
26:06 The collapse of trust in institutions
26:58 Corporate narratives & Apple’s “Think Different”
30:06 Creativity vs technology in strategy
30:41 Zoom Out, Zoom In strategy explained
33:08 Microsoft example: seeing the future early
35:14 Why agility without direction fails
37:21 Understanding “the edge” and innovation
39:34 Why transformation efforts fail in large companies
41:22 Scaling the edge vs top-down change
42:52 The power of the “explorer mindset”
47:18 Why companies suppress passion
48:31 Only 14% of workers are truly passionate
50:18 Can passion be cultivated at scale?
52:29 Does IT still matter in the AI era?
55:07 AI, healthcare, and the future of longevity
57:13 From healthcare to “wellness ecosystems”
58:19 The rise of the trusted advisor
59:50 Can AI replace human advisors?
01:02:25 Advice for leaders
01:04:18 AI is a tool humans determine its impact
01:06:29 Why most digital transformations fail

Connect with John:
LinkedIn: https://www.linkedin.com/in/jhagel/
X: https://x.com/jhagel

Our links:
Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast
Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if the AI revolution isn’t what we’ve been promised?

What does an economist and bestselling author have to say about the idea that Big Tech may be overselling the future of artificial intelligence?

In this episode, Oxford economist and Associate Professor of AI & Work, Carl Benedikt Frey, shares his skeptical perspective on the impact of artificial intelligence. He explains what it could mean for the future of work, including job market shifts and the necessity of skills development.

This conversation takes a critical look at the economic changes driven by AI, challenging the dominant narrative around productivity and technological progress. While Big Tech describes a future of abundance, Carl argues that history tells a more complicated story. From the Industrial Revolution to the computer age, breakthrough technologies didn’t automatically lead to sustained productivity or shared prosperity, and AI may follow a similar path.

Like and follow for weekly episodes.

In this episode:
00:00 Intro
00:57 Why the “AI Abundance” narrative might be wrong
01:45 Lessons from the computer revolution & productivity slowdown
03:30 AI vs computers: Automating cognition vs information
05:19 Why Big Tech may be overhyping AI impact
06:20 Automation vs creating new industries
08:08 AI infrastructure race: US vs China
10:25 The “Steam Engine Moment” AI hasn’t reached
12:31 Why technology alone isn’t enough
14:19 Why breakthrough innovation is declining
15:09 The collapse of business dynamism
15:45 Corporate lobbying, patents & barriers to entry
17:27 Why this matters more than AI itself
18:20 Startups vs Big Tech: Who drives innovation?
19:36 Will AI accelerate economic inequality?
21:37 Lessons from the Gilded Age & Antitrust History
24:04 Why strong governments enable competition
25:00 Big Tech vs historical monopolies
26:19 Centralization vs decentralization in innovation
29:01 Japan vs US
33:56 AI and the “more vs better work” problem
35:20 Will AI lower quality in research & knowledge?
36:23 AI: Increasing quantity vs improving quality
38:16 Why AI benefits low-skill workers more
39:49 AI and the rise of global labor competition
40:42 AI-driven offshoring
42:17 Which jobs are most at risk?
44:06 Long-term labor market predictions
46:20 Where humans still beat AI
48:15 The growing anti-AI backlash
49:11 Historical resistance to technology
53:39 Can government reduce AI disruption?
56:01 Why institutions determine outcomes
59:25 Advice for business leaders
01:00:12 Why decentralized companies win
01:02:24 Why innovation requires “waste”

Connect with Carl:
LinkedIn: https://www.linkedin.com/in/carlbfrey/
X: https://x.com/carlbfrey

Our links:
Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast
Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Why are 88% of businesses using AI but only 5% seeing real transformation?

In this episode, we sit down with Dan Diasio, EY’s Global Consulting AI Leader and CTO, to break down the four possible futures of AI, from constraint to full transformation, and what it takes for organizations to win in an AI-driven world.

Drawing from his experience advising Fortune 50 executives, Dan explains how leaders are navigating uncertainty, why many companies fall into the “sameness trap,” and what separates simple AI adoption from true competitive differentiation.

We also explore the rise of AI agents and end-to-end workflows, why mindset and skillset matter more than toolset, and what the future of jobs looks like in an AI-first world.

If you are thinking about AI strategy, leadership, or how to prepare your organization for what comes next, this episode delivers practical and forward-looking insights.

Like and subscribe for weekly episodes.

In this video:
00:00 Intro
00:40 Inside SXSW: Future-proofing AI strategy
02:14 Why predicting AI is impossible
02:56 The four AI futures explained (constraint → collapse)
04:36 What winning teams did differently
05:50 The “sameness trap” in AI
06:19 Positive vs negative AI futures
07:23 Constraint, growth, transform, collapse
09:54 What people actually believe about AI’s future
10:45 How do you win with AI?
13:17 Why business model innovation beats automation
14:02 Hands-on AI
15:46 How AI commoditizes output
17:01 AI investment trends: Productivity vs differentiation
18:13 The shift toward competitive advantage with AI
19:27 The AI Playbook: How leaders get it right
20:34 Going broad vs going deep with AI
21:11 88% vs 5%: The AI Adoption Gap
22:20 Mindset vs skillset vs toolset
23:27 Top-down vs bottom-up AI transformation
25:16 The visibility trap explained
26:06 Why new talent drives AI innovation
28:22 AI resistance & fear in organizations
29:43 “Death by a Thousand Papercuts” automation
30:54 New jobs: Knowledge Engineers & AI Orchestrators
32:48 Future Skills: Critical thinking, creativity, systems thinking
35:12 The role of IT in the AI era
37:34 AI as the new operating system of business
39:01 SaaS vs A
44:35 AI prototyping vs enterprise-scale systems
47:18 Will AI kill consulting?
54:07 AI infrastructure constraints & global risks
56:09 Biggest AI myths & misconceptions
57:34 Are we automating the wrong things?
59:27 Amara’s Law & AI hype cycles
01:00:12 How leaders should prepare
01:01:01 Why value creation beats cost cutting
01:02:17 Aligning AI strategy across the organization

Connect with Dan:
LinkedIn: https://www.linkedin.com/in/dan-diasio/

Our links:
Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast
Follow us on YouTube: https://www.youtube.com/@InfoTechRG

This is not just a technology shift. It is a human, organizational, and identity transformation.

In this episode, we sit down with Ian Beacraft, Founder and Chief Futurist at Signal and Cipher, to talk about one of the most urgent questions facing leaders today: what happens to work, organizations, and identity in the age of AI?

Ian argues that the next two years will matter more than the last 30, and that AI is not just another tool. It is a platform reshaping economies, organizations, and how we define work itself.

We break down why most companies are getting AI wrong, the critical difference between culture and coordination, and how the rise of AI agents is shifting value from doing the work to designing it. We also cover what leaders need to do right now to stay ahead, including real world examples of failed AI adoption, the growing power of small teams, and the coming identity shift in the workplace.

Like and subscribe for weekly episodes.

In this video:
00:00 Intro
01:20 Biggest AI trends since last year
02:28 Why AI is not just a tool
03:28 AI, identity, and the redefinition of work
04:08 The real threat: Outdated organizational thinking
05:00 Culture vs coordination explained
07:08 The danger of replacing humans with AI
09:48 Employee anxiety & leadership impact
11:19 Why AI is NOT an IT problem
12:31 How organizations should approach AI
15:04 Encoding human expertise into AI systems
16:22 Trust, fear, and job replacement concerns
17:23 Leadership, vision & the social contract
20:50 Why most leaders lack vision today
21:46 “What you do in the next 2 years is your legacy”
23:14 Incremental vs transformational AI thinking
24:25 Encoding organizational identity for AI
29:02 Why everyone must redesign their own work
31:16 From doing work to designing work
34:50 How leaders should drive AI adoption
38:08 Lessons from Building an AI-native organization
41:23 Rethinking departments & organizational structure
42:33 AI agents running autonomous workflows
44:08 The future role of culture
45:12 Real examples of AI agents in action
48:21 Small teams vs large organizations
49:04 The rise of entrepreneurship with AI
50:07 Which jobs are most at risk
55:13 Finding your competitive moat in AI
56:47 Why AI adoption is Lagging
57:24 Prediction: The future will be messy
59:38 Why systems must break before they improve
01:00:29 The AI transformation is about people, not tech

Connect with Ian:
LinkedIn: https://www.linkedin.com/in/ianbeacraft
X: https://x.com/ianbcraft
Instagram: https://www.instagram.com/ianbcraft/

Our links:
Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast
Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we giving up our freedom for convenience without realizing it?

In this episode, we sit down with Dr. Rumman Chowdhury, a globally recognized AI ethics leader featured in Time and Forbes, to unpack the real risks of artificial intelligence, Big Tech power, and data privacy.

As the former Head of AI Ethics at Twitter and Accenture, Dr. Chowdhury shares an insider perspective on how Big Tech is consolidating power, why narratives around AGI and “AI intelligence” are often misleading, and how everyday tools from apps to social media, are quietly shaping a surveillance-driven ecosystem.

This conversation dives into AI ethics, surveillance, and the future of work, and explores why trust in AI is declining even as adoption accelerates. We also break down the real-world implications of AI, and most importantly, how you can protect your data, reclaim your agency, and use AI more intentionally.

In this video:
00:00 Intro
01:16 What’s wrong with AI today
02:18 Why people trust AI less every year
03:09 Big tech vs the technology itself
04:22 Dangerous narratives about AI
06:09 Anthropomorphism and moral outsourcing
07:40 The myth of AGI and profit motives
09:20 The economics behind AI power
11:21 Consumer responsibility and the privacy paradox
13:42 “I have nothing to hide” explained
15:04 How big tech is consolidating control
16:42 What consumers should actually do
18:30 Real-world consequences of data misuse
21:05 From Pokémon Go to surveillance systems
22:29 The dilemma of social media and platforms
26:05 Can AI still be used for good
28:20 Algorithms, manipulation, and loss of agency
30:12 Inside AI ethics at Twitter
33:48 Why leadership and trust are changing
35:17 Surveillance capitalism and public backlash
37:31 How to think strategically about AI
41:19 Finding agency and intentional use of AI
45:06 Will society push back against AI power
52:02 The role of AI ethicists and builders
56:41 The future of work and automation reality
01:01:32 Why expertise and discernment matter most
01:06:35 Advice for business leaders using AI
01:11:33 Final thoughts on agency and discernment

Connect with Dr. Rumman Chowdhury:
LinkedIn: https://www.linkedin.com/in/rumman/
Instagram: https://www.instagram.com/rumman_c/?hl=en

Our links:
Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast
Follow us on YouTube: https://www.youtube.com/@InfoTechRG