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: 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

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

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