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Digital Disruption is where industry leaders and experts share insights on leveraging technology to build the organizations of the future.
As intelligent technologies reshape our lives and our livelihoods, we speak with the thinkers, the doers and innovators who will help us predict and harness this disruption. Join us as we explore how to adapt to and harness digital transformation.
Copyright: © Info-Tech Research Group
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:
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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
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