AI and the Future of Work
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Episode Number : 400
Wade Foster argues that the late 2025 model leap gave every knowledge worker an engineer. In this episode, he explains why the real bottleneck is not tooling but culture, and why companies still waiting on ROI are the ones that never changed how work gets done.
Show moreShow lessWade Foster is the CEO and co-founder of Zapier, the workflow automation and AI orchestration platform used by more than 4 million people to connect over 7,000 work apps. Since launching in the Y Combinator Summer 2012 batch, Zapier has automated more than 81 billion tasks, users have built more than 25 million Zaps, and the company has bootstrapped its way to a valuation north of $5 billion.
He holds degrees in industrial engineering and business administration from the University of Missouri, and has spent more than a decade on a single problem: making the tools people work in every day work for them instead of against them. He is also one of the show’s rare repeat guests. His first conversation with Dan was in January 2024, back when coding agents mostly did not work.
In this episode, Wade draws on running the automation layer that sits between thousands of enterprise tools to argue that the frontier model leap of late 2025 handed every knowledge worker an engineer, and that the companies still waiting on returns are the ones that never changed how the work itself gets done.
In this conversation, we discuss:
- Why the late 2025 model leap means every knowledge worker now has an engineer, and what that changes about ordinary work.
- Where deterministic workflows still beat AI at work, and why the most sophisticated teams refuse to choose between the two.
- What happens when white collar workers start pasting API keys into files, and the third option most security leaders are missing.
- Why Wade says culture, not tooling, is the real constraint, and what leaders get wrong when the board demands AI first.
- Why individuals report real AI gains while their organizations report none, and what has to be rethought before that gap closes.
- How Zapier built its AI Fluency Framework from its own teams, and why version one was already dated the day it shipped.
Explore this conversation:
00:00 Welcome to Episode 400
02:01 AI Fun Fact: Is Agentic AI the End of SaaS Tools?
04:35 Introducing Wade Foster: How Zapier Bootstrapped to 81 Billion Automated Tasks
06:01 From Coding Agents That Kind of Worked to an Engineer for Every Knowledge Worker
07:53 What Zapier Does Today: Deterministic Workflows Meet Non-Deterministic AI
11:12 Hybrid Workflows: Build It With AI, Run It Like a Program
13:30 MCP and the Orchestration Layer: API Keys, Agent Harnesses, and the Daily Recap
20:23 The Third Option for CISOs: Governing AI Agents Without Saying No
24:00 Foot Guns and Default Settings: The Product Judgment Behind Agent Permissions
27:03 Accountability When Software Is No Longer Deterministic: Evals and Spec Adherence
28:34 AI Strategy Office Hours: Why Individual AI Gains Are Not Becoming Institutional ROI
33:03 The Zapier AI Fluency Framework: Why Version One Was Dated on Arrival
36:15 Looking Ahead to 2028: The Hive Mind Company and a New Management Playbook
Resources:
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Episode Number : 399
AI won’t replace human judgment overnight. It will reveal who is strengthening it and who is surrendering it. NYU Stern professor Vasant Dhar explains why trust in AI depends on the cost of being wrong, when algorithms outperform people, and where human judgment remains irreplaceable.
Show moreShow lessVasant Dhar teaches data science at NYU’s Stern School of Business and has spent more than 45 years at the frontier of artificial intelligence. He brought machine learning to Wall Street in the 1990s and founded SCT Capital Management, one of the first machine learning based hedge funds.
He hosts the Brave New World podcast, downloaded more than a million times, where he has interviewed Nobel laureates, technologists, and global thinkers on the implications of AI. His work has appeared in The New York Times, The Wall Street Journal, Financial Times, Wired, and MIT Technology Review. His latest book, Thinking with Machines, traces AI from its origins to the present.
For more than forty years, Vasant has built systems that sat right on the edge of human trust. People had to decide whether to rely on them or walk away.
In this episode, he makes a stark claim: AI will not just change how we work; it will sort us into two groups. One uses it to extend their judgment. The other slowly hands that judgment over. The gap comes down to habits you are forming today, not some distant future.
In this conversation, we discuss:
- Why trusting AI comes down to just two variables, and the simple test Vasant has applied since his Harvard Business Review piece a decade ago
- The bifurcation Vasant believes AI is about to create, splitting humanity into two groups, and which side you do not want to be on
- What tennis great Roger Federer’s win rate reveals about succeeding with algorithms, and the counterintuitive math behind every winning edge
- Why the edge returns to humans the moment everyone runs the same algorithms, and what only people can do in situations no system has seen
- The one word in the title Thinking with Machines that Vasant says matters most, and what it asks of how we work alongside AI
- The areas of life where Vasant argues we may need to restrict AI entirely, and the legal framework we already have to govern it
Resources:
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Episode Number : 398
Ariel Assaraf, CEO of Coralogix, argues that observability is no longer just about preventing downtime. It has become the most truthful, real-time source of intelligence any company owns, and AI agents are about to change who acts on it.
Show moreShow lessAriel Assaraf is the CEO and co-founder of Coralogix, a leading observability platform that most recently raised $115 million at a unicorn valuation. He started the company in 2014, and today Coralogix serves more than 4,000 customers, monitors more than 500,000 applications, and processes over 3 million events per second.
Before co-founding Coralogix, Ariel served in Israel’s Elite Intelligence Unit 8200, where the sheer scale and complexity of data he worked with made one thing clear: existing architectures weren’t built for what was coming. He later joined Varent Systems, a homeland security company, leading automation, integration, and QA.
In this episode, Ariel draws on more than a decade of building at the frontier of data infrastructure to argue that observability is no longer just a tool for preventing downtime. It is becoming the most truthful, real-time source of intelligence any company owns.
In this conversation, we discuss:
- The evolution from the data collection era (“oil phase”) to a landfill crisis, and now the AI-driven “brain phase” where telemetry has become the most valuable raw material for business decision making
- How Coralogix separates the data plane from the control plane, storing data in open format on the customer’s own infrastructure to enable data ownership, infinite retention, and freedom from vendor lock-in
- Why Ariel invested over $100 million in R&D to build query engines that always return answers, not constrained by predefined schemas that agents will quickly exceed
- How SREs evolve from reactive incident responders into autonomous operators as agents like Ollie, Coralogix’s AI agent, take over incident triage, root cause analysis, and narrative generation
- The emerging role of the AI-forward product manager who sits between customer needs and autonomous agents, reshaping how software gets built, priced, and sold in real time
- How Ariel thinks about linear versus exponential impact as a leadership principle, and why the intuition to prioritize exponential value is something agents will never replicate
Explore more in the conversation:00:00 Welcome & AI’s societal impact paradox
01:53 AI Fun Fact: New data on productivity and employment
04:15 Introducing Ariel Assaraf and the Coralogix origin story
05:15 Evolving data architecture: from oil to landfill to brain phase
07:28 Coralogix’s data ownership and open format advantages
13:27 From telemetry data lake to autonomous, agent-driven analytics
20:00 Building scalable, answer-guaranteeing query engines for complex data
25:44 The future of natural language interfaces like Olly for SREs and DevOps
28:15 Orchestrating multiple AI agents for better decision-making
30:20 Responsibility, autonomy, and the evolving role of customer success
35:37 How Coralogix turns telemetry into strategic business decisions
38:18 Linear vs. exponential value in your career
Resources:
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Episode Number : 397
Maryjo Charbonnier helped build Kyndryl’s people strategy from scratch when it spun out of IBM as one of the largest public company spin-offs in history. She argues that as AI automates tasks, careers are shifting from what you know to how you judge, lead, and decide.
Show moreShow lessMaryjo Charbonnier is the former CHRO and Executive Advisor at Kyndryl, the world’s largest provider of IT infrastructure services , with more than 70,000 employees across roughly 60 countries. When Kyndryl was spun out of IBM in 2021 as one of the largest public company spin-offs in history, Maryjo helped build its culture and people strategy from the ground up, which is why she and others have called it the world’s largest startup.
She has spent nearly two decades as a public company CHRO on both sides of the Atlantic, including Wolters Kluwer (traded on the Dutch exchange) and Broadridge Financial Solutions, after a formative run at PepsiCo where she led change management for Frito-Lay. She was named CHRO of the Year in the Netherlands and earned her MBA at Southern Methodist University.
In this episode, Maryjo draws on a career spent leading messy transformations and building a 70,000-person workforce to argue that as AI automates tasks and chunks of jobs, the work that defines a career is moving from what you know to how you judge, lead, and decide, and most organizations are not teaching for it yet.
In this conversation, we discuss:
- Why Mary Jo “seeks the heat” in messy transformations and what she learned leading HR through turnarounds, spin‑offs, and large‑scale change.
- How Kyndryl defined the “Kindryl way” with six core behaviors and uses culture as an operating plan in the world’s largest startup.
- Why HR must focus on which skills are rare and most valuable, and how Kyndryl’s Make Yourself Discoverable campaign turned skills into a strategic asset.
- How AI-powered career profiles, skills-based redeployment, and role-specific AI curricula were intentionally designed to show Kyndryls that AI is an asset to their career, not a threat to it.
- Why Mary Jo believes HR has three roles in AI, including reshaping commercial work and building an AI governance council that balances speed with risk.
- How leadership “ORE” (job design, risk management, empathy) and human skills like change management and people leadership will define careers in an AI‑enabled workplace
Resources:
- Subscribe to the AI & The Future of Work Newsletter
- Connect with Maryjo on LinkedIn
- AI fun fact article
- On How Rory O’Driscoll Explains Success Modes for AI Companies and Three Essential Startup Strategies
- Episode with Keith Sonderling, then an EEOC Commissioner and now the U.S. Deputy Secretary of Labor
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Episode Number : 396
Futurist and Stanford scholar Trond Undheim argues that knowledge is becoming superfluous in the AI era. What replaces it is system awareness: the ability to see how humans and machines co-evolve, and design for what that actually requires.
Show moreShow lessTrond Undheim is a futurist, innovation expert, and research scholar at Stanford University whose work spans governments, startups, and leading academic institutions. His ideas have been featured in outlets including Forbes, The Boston Globe, Fast Company, Fortune, and MIT News, and he previously hosted the Futurized podcast.
He holds a PhD in AI and cognition from the Norwegian University of Science and Technology and is the author of eight books, including The Platinum Workforce, which explores how to train and hire for the twenty-first century’s industrial transitions.
In this episode, Trond draws on decades of interdisciplinary work on emerging technologies, systemic risk, and workforce transitions to argue that system awareness, not traditional knowledge, will determine who thrives in an AI-defined economy.
In this conversation, we discuss:
- Why Trond says knowledge has become superfluous, and what that claim means for how we define expertise in an AI era.
- Why cutting junior hires to cash in on AI efficiencies bakes a failure mode into your organization.
- What “system awareness” looks like in practice, and how it changes the way leaders think about skills and careers.
- Why socio-technical thinking matters, and how treating humans and machines as mutually constitutive systems reshapes AI design and governance.
- Why humanity is unprepared to operate at gigascale, and what megaproject research suggests about the cost of that gap.
- How The Platinum Workforce maps twelve durable skill domains, from socio-technical capabilities to maker and maintenance skills, that will outlast multiple AI waves.
Explore this conversation:
00:00 Intro and AI Fun Fact: Pew Research Americans More Concerned Than Excited About AI
04:22 Introducing Trond Undheim, Futurist and Author of The Platinum Workforce
05:09 Why the Workforce Is the Single Biggest Lever for Human Survival
09:08 System Awareness: The Only Knowledge That Matters in the AI Era
15:06 Socio-technical Systems: Co-Evolution of Humans and Technology
17:54 Human Agency Over Technology: Who Really Sets the Rules
23:24 The Human Skills AI Cannot Replace: Making, Maintaining and Place Maximizing
31:12 Workforce Preparation for the AI Era: Training Juniors and Experimentation
34:08 Macro Challenges: Giga-Scale Projects and Management at Scale
45:33 The Augmented Workforce: What AI Integration Must Look Like in 10 Years
54:39 Where to Connect with Trond Undheim and Learn More About The Platinum Workforce
Resources:
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Episode Number : 395
Lev Gonick, CIO at Arizona State University, argues that AI is not disrupting higher education. It is accelerating a disruption that was already decades in the making. He shares what data from 200,000 daily AI users is actually revealing about the future of learning.
Show moreShow lessLev Gonick is the CIO at Arizona State University, one of the largest and fastest-growing universities in the United States, with over 200,000 students across campuses in Phoenix, Los Angeles, Washington, and 35 partner institutions around the world. He won an ORBIE Award in 2023 as a top large Enterprise CIO, was named a Top 50 Educational Technology Influencer by EdScoop in 2022, and holds a PhD in International Political Economy from York University.
Before joining ASU, he was one of the rare CIOs who came from the classroom, having spent the first decade of his career as a teacher and researcher before pioneering online learning in the 1990s, long before it became an industry.
In this episode, Lev draws on more than 40 years at the intersection of technology and education to make the case that AI is not the disruptor of higher education, it is the accelerant, and that the institutions treating it that way are already building what everyone else is still debating.
In this conversation, we discuss:
- Why AI is not the disruptor of higher education, and what has actually been driving the disruption for decades
- How ASU went from survival mode during the 2009 financial crisis to building the largest online learning operation in the country, and why the same instinct is now driving its AI strategy
- What ASU’s data from 200,000 students using AI daily actually reveals about which skills will endure and which ones will not
- How the role of university faculty is fundamentally changing in the AI era, and why the hardest question has nothing to do with cheating
- What the “Agentic self” means for creatives, and how a unique course taught by Will.i.am is helping students protect and amplify their creative futures.
- How the traditional responsibilities of the Chief Information Officer are expanding beyond basic operations to actively shaping institutional strategy and innovation.
Explore this conversation:
00:00 Intro and AI Fun Fact: Blue Books vs AI Rethinking Academic Integrity
04:25 Introducing Lev Gonick, CIO at Arizona State University
05:17 From Classroom Teacher to Academic Disruptor at ASU
08:16 ASU Principled Innovation and the Design Build Approach to AI
13:23 Co-Creating with Industry: AWS Zoom and the GSV Summit at ASU
17:35 Soft Skills Are Smart Skills: Rethinking AI Literacy in Higher Ed
23:25 Rethinking Assessment: What Faculty Must Adapt to in the AI Era
27:01 Why a College Degree Still Matters in the Age of AI
30:37 From YouTube to ASU: Meeting Learners Where They Are
34:22 Disrupt or Be Disrupted: ASU Mission to Reach 300000 Students
35:57 From Operator to Strategist: The New Playbook for the Modern CIO
40:26 Connect with Lev Gonick and Arizona State University
RESOURCES
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Episode Number : 394
Dr. Muthu Alagappan, CEO of Counsel Health, argues that a patient’s zip code should never determine the quality of their care. He shares how semi-autonomous AI is democratizing access to personalized medical advice from real physicians.
Show moreShow lessDr. Muthu Alagappan is the Founder and CEO of Counsel Health, the company automating access to high-quality, personalized medical advice from doctors. Counsel recently closed a $25M Series A led by Andreessen Horowitz and Google Ventures, following an $11M seed round that included A16Z, Asymmetric Capital Partners, Floodgate Fund, and Pear VC.
He holds an MD from Stanford Medicine and a B.S. in Biomechanical Engineering from Stanford, and was among the earliest AI researchers to publish on clinical applications of machine intelligence.
In this episode, Muthu draws on 15 years at the intersection of AI research and frontline clinical medicine to explore the shift toward semi-autonomous care.
In this conversation, we discuss:
- How AI addresses the limitations of traditional primary care by offering a highly personalized, knowledgeable, and always available medical experience.
- Why patients might leapfrog clinicians in their willingness to adopt AI for medical advice, and how this shift challenges the traditional identity of physicians.
- What semi-autonomous care actually looks like in practice, and how Counsel Health uses a clinician cockpit to augment human compassion with real-time machine intelligence.
- How to leverage population-level patterns without compromising patient privacy.
- Why the double standard applied to AI is misplaced, and why Muthu argues we should hold AI to a much higher benchmark than human doctors simply.
- What the future of global healthcare could look like when cognitive medical expertise is fully democratized, ensuring that a patient’s zip code no longer dictates the quality of care they receive.
Explore the Conversation
00:00 Intro & AI Fun Fact: Big Data Limitations and Bias in Clinical AI
03:52 Meet Dr. Muthu Alagappan: From Stanford AI Researcher to Counsel Health CEO
06:51 Why Primary Care Falls Short: The Case for AI-Augmented Medicine
09:05 Human Doctors Are Human: How Patients Are Adopting AI Medical Advice
12:20 Patient Privacy and Population Health: Learning Without Training on Data
14:17 Inside the Clinician Cockpit: Real-Time AI Support for Doctors
16:17 Why Counsel Health Employs Its Own Physicians: Messaging-Based Care
19:00 From Semi-Autonomous to Fully Autonomous Care: Healthcare’s Next Era
24:19 AI Ethics in Medicine: Safety Standards, Model Values, and Data Ownership
27:22 The AI Double Standard: Why Machines Deserve a Higher Benchmark Than Doctors
31:07 Founder Lessons: Building a Category-Defining Healthcare AI Company
33:53 Rewriting the Commencement Address: Medicine as Lifelong Learning
35:37 Where to Connect with Dr. Muthu Alagappan and Counsel HealthResources
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Episode Number : SE 26
Four leaders from Honeycomb, FieldAI, Archetype AI, and Zoom share how they build AI that explains itself, signals uncertainty, and keeps human judgment at the center [recorded live on the HumanX 2026 show floor].
Show moreShow lessIn this special compilation episode of AI and the Future of Work, we are bringing you four conversations recorded live on the show floor at HumanX 2026. This is the second and final compilation of our three-part HumanX Live series.
Our first compilation explored how AI amplifies the human potential it can never replace. This one turns to the technical side, and to a question that gets harder the more these systems touch our lives: how do you build AI you can actually trust not to fail when it matters most?
As technology reaches further into the moments that count (the systems that monitor our health, drive our cars, and work alongside us on the job), these four builders share how they design for accountability, safety, and harmony between people and machines.
What You’ll Learn
- Why reading code is no longer enough, and how observing real outcomes (not system metrics alone) is the only way to know whether AI is actually serving the people who depend on it
- What “AI values” are, and why companies will soon need shared norms for how people disclose, review, and engage with work produced by agentic systems
- How robots earn trust on a job site by measuring their own uncertainty, asking questions, and communicating their intentions before they act
- Why the most valuable place for automation is the dirty, dull, and dangerous work humans were never meant to do, and what that means for keeping people safe
- Why physical AI should be built first as a reasoning and communication model that can explain its thinking to people, rather than one that jumps straight to action
- How “harness engineering” moves teams beyond prompt and context engineering, and why orchestrating several frontier models together can outperform any single one
Featured Guests
- Christine Yen, CEO and Co-Founder of Honeycomb. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362645
- Dr. Ali Agha, CEO and Co-Founder of FieldAI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362711
- Dr. Jaime Lien, Co-Founder & Chief Scientist of Archetype AI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363341
- XD Huang, Chief Technology Officer of Zoom. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363454
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Episode Number : 393
Dan Roth is the Editor in Chief and a Vice President at LinkedIn, where he has led the
Show moreShow lessDan Roth is the Editor in Chief and a Vice President at LinkedIn, where he has led the world’s largest professional editorial operation since 2011. Business Insider once called him the most powerful business journalist on the internet, and over more than a decade he has helped turn LinkedIn from a networking site into a global media platform, building out its editorial team, top voices, and Influencer Program. He also hosts the popular This Is Working podcast.
Over 15 years watching professionals navigate every major shift in the workplace, from the rise of social media to the agentic AI era, Dan has developed a clear and counterintuitive view of what actually drives a durable career. In this episode, he draws on LinkedIn’s data from over a billion members to make the case that the skills employers are hunting for right now are not the ones most professionals are building, and that the gap between what AI can produce and what humans can offer is closing faster than anyone is prepared for.
In this conversation, we discuss:
- Why AI has commoditized knowledge itself, and what professionals actually come to LinkedIn for that no chatbot can give them
- What separates content that spreads beyond your network from content that stays stuck inside it, and what LinkedIn’s systems are really looking for
- Why AI is a great tool for getting your voice out, and the exact moment it starts working against you instead
- The mindset Dan drills into his team about passion and failure, and the one thing he says you are never allowed to get wrong
- How a mission-driven company resists the pull to chase clicks and ad revenue, and what Dan’s old-world instincts taught him to unlearn
- The two categories of skills surging in demand right now, and why the second list is the one most people overlook
Resources:
- Subscribe to the AI & The Future of Work Newsletter
- Connect with Daniel on LinkedIn
- AI fun fact article
- On How AI is making networks smart
- Other episode mentioned in the show: 315: Tony Stubblebine, CEO of Medium, On Human Curation, Subscription-Driven Quality, and Fixing the Internet
LIVE EVENT:
See how leading enterprises are using agentic AI to give employees back 4–6 productive hours every week. Join PeopleReign CEO Dan Turchin for a live demo on June 25, 2026.
Register here: https://go.peoplereign.io/live-demo-how-agentic-ai-is-being-used-by-global-enterprises
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Episode Number : 392
Sophia Kianni is the co-founder and CEO of Phia, an AI shopping agent with more than 1.4 million
Show moreShow lessSophia Kianni is the co-founder and CEO of Phia, an AI shopping agent with more than 1.4 million users that has raised over $43 million from an investor list that includes Kris Jenner, Sara Blakely, and Hailey Bieber. Sophia and her co-founder built the company out of their Stanford dorm room on a single thesis: in the future, every consumer will have a personal AI shopping assistant.
Sophia is also the co-host of The Burnouts, a podcast with more than 600,000 followers and over 200 million downloads. Earlier in her career, she founded Climate Cardinals, the world’s largest youth-led climate nonprofit with more than 20,000 volunteers, and became the youngest United Nations advisor in U.S. history.
In this episode, Sophia draws on her experience building high-velocity ventures before the age of 25 to challenge how founders think about feedback, team culture, content creation, experimentation, and workflow efficiency. She also makes a compelling argument for how AI should be used at work: removing friction from the parts of a workflow that drain time and energy without adding value.
In this conversation, we discuss:- Why the intersection of social and shopping looked like a solved problem to most founders, and the gap that Sophia and her co-founder saw inside their Stanford dorm room
- How Sophia thinks about team building as company building, and the specific qualities she screens for before resumes, credentials, or experience
- How a consumer-first mindset and relentless customer feedback help Phia iterate faster and build a product users love
- Why building close to your user is still the most underrated advantage in AI, and what most founders miss when they try to scale it
- Why Phia and The Burnouts built data-oriented content engines that operate like scientific labs, testing hooks, fonts, retention curves, and B-roll as measurable variables rather than relying on creative instincts alone
- How Sophia uses AI tools like Adobe Firefly to increase workflow efficiency by removing friction from repetitive tasks, not to replace creative work, but to protect it
- The framework Sophia uses to decide whose feedback shapes her decisions and whose she treats as noise
Resources -
Episode Number : SE 25
Four founders from Scribe, Operative Games, Dataiku, and Zensai make the case for what AI cannot replace: human judgment, creativity, and the drive to do work that matters. Recorded live on the HumanX 2026 show floor.
Show moreShow lessIn this special compilation episode of AI and the Future of Work, we are bringing you four conversations recorded live on the show floor at HumanX 2026. This is the second episode of our three-part HumanX Live series.
In an era dominated by headlines about displacement and disruption, these four founders share a grounded optimism about what AI cannot replace: human judgment, creativity, and the drive to do work that matters.
Each of these leaders is building in a different space, but they arrived at the same conviction. The companies and people poised to win in the AI era are not the ones moving fastest to automate. They are the ones who understand what humans are uniquely built to do, and build systems that make space for it.
What You’ll Learn
- Why most organizations cannot answer a basic question: how does work actually get done here, and why that gap is now a strategic liability
- How AI-powered learning can shift employee development from a compliance obligation to a genuine driver of engagement
- Why storytelling will remain a human craft, and what the Pixar transition teaches us about navigating creative disruption
- The case for asynchronous AI collaboration, where systems work overnight and humans return to exercise judgment
- Why optimism about the human worker is not naive, and what the data actually shows
- How to balance AI use cases that replace humans with those that create new value and grow the economy
Featured Guests
- Jennifer Smith, CEO & Co-founder of Scribe. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257070
- Robin Daniels, Chief Business Officer at Zensai. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257107
- Jon Snoddy, CEO of Operative Games. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257113
- Florian Douetteau, CEO of Dataiku. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257131
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Episode Number : 391
Andrew Palmer is a long-time editor and columnist at The Economist, where he writes the widely read Bartleby
Show moreShow lessAndrew Palmer is a long-time editor and columnist at The Economist, where he writes the widely read Bartleby column on work and life. He also hosts Boss Class, one of The Economist’s most popular podcasts, whose most recent season explored generative AI in the workplace, a topic Andrew approached not just as a journalist, but as a self-described unsophisticated user determined to get smarter by doing.
In this episode, Andrew draws on his reporting and interviews with leaders across industries to offer an outside-in view of where AI adoption actually stands, and why the gap between the hype and the reality is not a sign of failure, but of how complex change really is.
In this conversation, we discuss:
- Why AI adoption faces three distinct barriers (behavioral, technical, and organizational) and why solving one without the others leaves productivity gains stranded.
- Why structural reskilling frameworks (like Denmark’s flexicurity model and Singapore’s voucher-based lifelong learning system) offer a more credible response to AI disruption than waiting for policy to catch up.
- Why Johnson & Johnson’s “let a thousand flowers bloom” approach to AI experimentation produced a Pareto effect (15% of projects generating 85% of value) and what they changed as a result.
- How the AI productivity boom is real at the individual level but not yet showing up in aggregate data, and why Andrew believes that gap is a question of time, not technology.
- Why enlightened corporate leadership requires transparency about potential job disruption and a commitment to adjacent career planning rather than performative optimism.
- What work in 2036 might look like, and why Andrew’s most unsettling prediction has nothing to do with jobs, and everything to do with privacy.
Explore this conversation:
00:00 Introduction to AI and the Future of Work episode 391
01:14 AI fun fact: AI legislative speed versus technological advancement
03:51 Meet Andrew Palmer The Economist Bartleby Column Boss Class
06:14 Digital Doppelganger and AI Personality Traits
07:57 AI Adoption Barriers Behavioral Technical and Organizational
11:01 AI Impact at Work Startups vs Large Organizations
14:15 Leadership Humility and AI Uncertainty in the Workplace
17:41 AI Experimentation at Scale Lessons from Johnson and Johnson
24:26 AI vs SaaS Productivity Data and the Speed of Adoption
27:35 Balancing AI Automation with Human Meaning at Work
31:26 AI Policy Reskilling and Lifelong Learning for the Future
36:03 Work in 2036 AI Monitoring Privacy and Constant Surveillance
38:47 Who Really Controls AI and What That Means for Workers
44:08 Connect with Andrew Palmer and Boss Class The Economist
Resources:
- Subscribe to the AI & The Future of Work Newsletter
- Connect with Andrew on LinkedIn
- AI fun fact article
- On How Arvind Jain Is Shaping the Future of Enterprise Search
- Another episode mentioned in the interview: How we can take back control from Big Tech with Tom Wheeler, former FCC Chairman, CEO, VC, and author of Techlash.
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Episode Number : 390
Arnnon Geshuri is Chief People Officer at Snowflake, where he leads culture development, talent strategy, and organizational design
Show moreShow lessArnnon Geshuri is Chief People Officer at Snowflake, where he leads culture development, talent strategy, and organizational design at one of the world’s leading data cloud companies. His career spans decades of scaling high-growth technology organizations, including leadership roles at Google, Livongo Health, and Tesla, where he oversaw its growth from a 400-person startup to a 35,000-person transportation juggernaut.
Throughout his career, he has consistently chosen companies that demand a people function as innovative, as creative, and as forward-thinking as the business itself. And across every role, he has focused on one core idea: the people function must evolve as fast as the business itself, grounded in data, experimentation, and trust.
In this episode, Arnnon draws on that experience to challenge how leaders think about AI in the workplace, arguing that the real opportunity is not automation alone, but redefining how humans contribute, decide, and grow inside modern organizations.
In this conversation, we discuss:- Why the people function must speak the language of data and analytics to influence engineering-led organizations and earn credibility in high-growth, technical environments
- The shift from transactional HR to a strategic role focused on connection, education, and rebuilding trust after workforce disruption and disconnection during COVID
- How Snowflake frames AI adoption by automating repetitive work, augmenting creative tasks, and preserving human judgment in decisions that require empathy and context
- Why employees adopt AI faster when leaders encourage curiosity, remove fear of experimentation, and make tools accessible through simple interfaces like natural language
- The risks of over-automating decisions like hiring and performance reviews, and why removing human accountability breaks trust inside organizations
- How building a culture of experimentation, measurement, and iteration allows people leaders to scale organizations without relying on intuition alone
Explore the Conversation
00:00 Intro & Fun Fact: How AI manipulation threatens autonomy
05:06 Meet Arnnon Geshuri: CPO at Snowflake, from Google, Tesla, and Livongo Health
10:24 The Evolution of HR: From Transactions to Amplifying Humanity
13:37 Snowflake’s AI Framework: Automate, Augment, and Preserve Human Judgment
21:44 Driving AI Adoption: AI for Everybody and a Culture of Experimentation
26:26 Data Privacy and Trust: Building Guardrails for Enterprise AI
28:36 AI in Hiring: Mitigating Bias to Rescue Human Connection
32:28 Setting AI Boundaries: Why Algorithms Should Never Conduct Performance Reviews
34:16 Scaling Culture in Hyper-Growth: The Power of People Analytics
41:33 The AI Ride-Along Prediction and What Comes Next
43:15 Where to Connect with Arnnon Geshuri and Snowflake
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Episode Number : SE 24
Stefan Weitz, Co-founder and CEO of HumanX, explains why surviving the AI era means treating technology as an evolving tool and why the most powerful thing a leader can say today is “I do not know.”
Show moreShow lessIn this special episode of AI and the Future of Work, we are bringing you an exclusive conversation recorded live on the show floor at the HumanX 2026 event. This full interview kicks off a special three-part series, with the upcoming two episodes releasing in a compilation format. To start things off, we are sharing our uncut conversation with the man who made this entire gathering possible.
Stefan Weitz is the Co-founder and CEO of HumanX, an organization and premier event dedicated to cutting through the AI hype to find practical, world-changing applications. He joined Microsoft in 1996, working alongside leaders like Bill Gates and Steve Ballmer on iconic product launches and foundational tech like Bing and Windows.
In this live episode, Stefan draws on his extensive product development background to explain why our survival in the AI era depends on treating technology as an evolving tool and why the most powerful thing a leader can say today is “I do not know”.
In this conversation, we discuss:
- Why relying on focus groups and lean product development is the wrong approach for building breakthrough AI hardware and software.
- The reason established tech giants risk losing the AI race if they rely solely on distribution over building superior products.
- How AI differs fundamentally from all previous human tools and why its ability to learn creates unprecedented exponential growth.
- Why the speed of current technological adaptation threatens to outpace our natural ability to transition roles and find new purpose.
- The danger of anthropomorphizing artificial intelligence and why framing it as human creates unnecessary fear and resistance.
- How saying “I do not know” has become the most powerful leadership tool in a non-deterministic technology landscape.
Resources:
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Episode Number : SE 23
Microsoft’s 2026 Work Trend Index reveals a striking gap: your employees are already ahead of you on AI. Matt Firestone, General Manager for Microsoft 365 Copilot and Agents, unpacks what trillions of signals say about how work is actually changing.
Show moreShow lessYour employees are already ahead of you on AI. The data is in and the question is no longer whether this is happening, but what leaders choose to do about it.
That is one of the key findings from Microsoft’s 2026 Work Trend Index, and it is the starting point for this week’s special episode. PeopleReign CEO Dan Turchin sits down with Matt Firestone, General Manager at Microsoft leading product marketing for Microsoft 365 Copilot and Agents, to unpack what trillions of anonymized signals across the Microsoft 365 ecosystem reveal about how AI is actually changing work right now.
What pairing telemetry with survey responses and in-house research reveals about the gap between where employees actually are and where their organizations think they are is striking. And the numbers on how organizations reward, or fail to reward, the people already doing this work will make most leaders uncomfortable. The bottleneck, it turns out, isn’t where most people expect it.
In this conversation, we discuss:
- Why the job of a leader has shifted from designing transformation strategy to changing systems and culture
- How the report reframes agentic AI collaboration, not as a threat to human agency, but as an expansion of it
- What “frontier firms” and “frontier professionals” actually means, and why it’s a mental model and rallying cry, not a marketing term
- How building in the open, leaders experimenting visibly and removing the stigma of getting things wrong, is one of the most quantifiably impactful things a manager can do
- Why agent adoption on the Microsoft 365 ecosystem is growing at a rate that will surprise even the optimists
Explore this conversation:
00:00 Intro
01:14 Inside Microsoft’s 2026 Work Trend Index
02:22 Telemetry, Not Just Surveys: What the Data Reveal
03:09 Employees Are Ahead of Their Managers on Agentic AI
04:37 The Transformation Paradox and Broken Reward Systems
06:15 More Agentic AI, More Human Agency: The 49% Finding
09:28 How Leaders Should Respond: Build in the Open
11:26 Safety, Trust, and Responsible AI at Microsoft Scale
13:36 Building a Manager Equity Dashboard in 25 Minutes with Copilot
17:31 What Frontier Firms and Frontier Professionals Actually Do
20:04 AI, Toil, and the Fear of Becoming Obsolete
22:52 The 1 Billion Agents Prediction and What Comes Next
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Episode Number : SE 22
Six bestselling authors and former guests return to explore what AI cannot automate: trust, vulnerability, and meaning. The future of work is not about competing with algorithms. It is about discovering what makes us irreplaceably human.
Show moreShow lessIn this special April compilation episode of AI and the Future of Work, we’re bringing back six great former guests who published popular books about how AI is redefining humans at work.
The future of work isn’t about competing with algorithms. It’s about how we use technology to increase our capacity for trust, express our vulnerability, and discover meaning.
This episode brings together insights from authors who explore how AI is reshaping work and what it means for individuals and organizations.
What You’ll Learn- Why delegating routine tasks to AI frees us to explore our human superpowers like empathy, rational thinking, and compassion.
- How the future of knowledge work lies in navigating ambiguity and expressing entirely new ideas.
- Why leaders must move beyond monitoring and productivity theater to build cultures of trust and give teams the space to experiment.
- How the traditional, contract-based employment model is failing the next generation and what replaces it.
- Why the era of the “superhuman” leader is over, and how showing your human side earns loyalty in times of disruption.
- How the AI revolution is sparking a massive work quake, and why only you can write your own story and decide what gives you meaning.
Featured Guests
- Bernard Marr, Futurist and Bestselling Author of Generative AI in Practice – Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/15441666]
- Atif Rafiq, Former Fortune 500 Executive and Author of Decision Sprint – Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/14507445]
- Brian Elliott, Executive Advisor and bestselling author of “How the Future Works”. – Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/17282891]
- Josh Drean, Co-founder of the Work3 Institute and Co-author of Employment is Dead – Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/16473644]
- Linda Rottenberg, CEO and Co-founder of Endeavor, and Author of Crazy is a Compliment – Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/8356582]
- Bruce Feiler, Bestselling Author of The Search: Finding Meaningful Work in a Post-Career World – Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/14158168]
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Episode Number : 384
Jake Saper is a General Partner at Emergence Capital, one of the most iconic venture firms in enterprise
Show moreShow lessJake Saper is a General Partner at Emergence Capital, one of the most iconic venture firms in enterprise software, with a portfolio that includes Zoom, Gusto, Veeva, and Together AI. Emergence has backed some of the most category-defining B2B companies of the last two decades, and Jake has spent nearly 12 years at the center of that deal flow.
What sets Jake apart is a life lived on both sides of the creativity question: he backs the companies building AI but also performs across genres from blues to metal as a working musician.
In this episode, Jake brings that rare combination of investor rigor and artist instinct to one of the hardest questions AI is forcing us to face, and whether you leave reassured or unsettled may depend entirely on how much of your identity is wrapped up in the work you create.
In this conversation, we discuss:
- How AI will democratize the creation of art but commoditize its execution, ultimately causing the value of live, dynamic human performances to skyrocket.
- The stunning acceleration of startup growth, with top-quartile B2B software companies now scaling from zero to $1 million in ARR in just four months.
- How the flood of AI-generated content is turning attention into the real bottleneck, and why curation and point of view become the new competitive advantage.
- Why Jake believes the market will self-regulate the anthropomorphization of AI agents in the workplace, and where that logic has a hard limit.
- What Geoffrey Hinton said about building AI “like a mother,” why it was both comforting and deeply unsatisfying, and what it reveals about AGI risk.
- Why Jake argues disclosure matters during this transition period, but what he actually wants people to ask about art as AI becomes a normal creative tool.
Explore this conversation:
00:00 Why AI Makes It Easier to Build a Demo and Harder to Build a Moat
05:25 From Cell Towers to Venture Capital: Jake Saper’s Path to Emergence
08:53 How AI Is Compressing Startup Growth: From 18 Months to 4 Months to $1M ARR
18:05 What Art Actually Is: Compressed Human Experience and the Act of Making Meaning Shareable
23:30 How AI Can Unlock Latent Creativity in People Who Don’t Think of Themselves as Creators
26:55 Why Disclosure Matters When Trust and Authenticity Are at Stake
30:19 Navigating a Post-Truth Era: When Everything Looks Synthetic, What Do We Believe?
32:14 Why the Value of Live Performance Is About to Skyrocket
35:58 As Soulless Entities Multiply, Soul-to-Soul Human Connection Becomes More Valuable
40:38 What Geoffrey Hinton Said About Building AI “Like a Mother” and Why It Was Unsatisfying
43:04 Why the Most Enduring Art Has Always Been About Transfer, Not AuthorshipResources:
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Episode Number : 383
Daniel Lereya is Chief Product and Technology Officer at monday.com, the AI work platform trusted by 60% of
Show moreShow lessDaniel Lereya is Chief Product and Technology Officer at monday.com, the AI work platform trusted by 60% of the Fortune 500 and valued at approximately $8 billion. He joined the company when it had 30 people and $4.5M ARR, and has since grown his team from 5 to nearly 900 people as monday.com crossed $1 billion in ARR.
In this episode, Daniel draws on nearly a decade of scaling one of the world’s most adopted work platforms to share what it actually takes to rebuild product thinking from scratch when AI changes everything you thought you knew.
In this conversation, we discuss:
- Why the instincts that made monday.com successful are the exact ones Daniel says had to be dismantled to build AI-first products.
- What the critical difference is between building a demo that impresses and an agent that actually works in production, and where most teams get it wrong.
- Why Daniel believes wrapping AI inside rigid workflows produces better results than giving agents full discretion, and what monday.com learned the hard way.
- What happened when 2,000 of 3,000 monday.com employees started building their own apps in just two weeks, and what it revealed about the future of who gets to build software.
- Why Daniel argues that when an AI agent makes a mistake, the real question leaders should be asking has nothing to do with the technology.
- Why the biggest barrier to AI adoption is not the technology itself, and what Daniel says companies must stop waiting for before they start.
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Episode Number : 382
Lisa Davis is a technology executive who has served as CIO and tech leader for some of the
Show moreShow lessLisa Davis is a technology executive who has served as CIO and tech leader for some of the world’s most complex organizations, including Intel, Blue Shield of California, the U.S. Marshals Service, and the Department of Defense.
She is now focused on shaping the next generation of leaders and advocating for women and diverse talent in STEM through her board work, executive coaching, and her forthcoming book, The Only Woman in the Room: How to Win in a Workplace Still Built for Men.
In this episode, Lisa draws on 30+ years leading technology at the highest levels of government and enterprise to make the case that the future of AI depends on who gets to build it, and as long as women remain locked out of those rooms, we are getting it dangerously wrong.
In this conversation, we discuss:
- Why women’s representation in STEM has fallen from 34% in the mid-1980s to 22% today, and why that decline is a crisis for the future of AI, not just the workplace.
- Why the real risk isn’t the technology itself but the leadership teams making AI decisions without diverse voices at the table.
- The structural systems that were never designed for women to thrive, and why redesigning them is a business imperative, not a social favor.
- Why current corporate layoffs are being falsely attributed to AI, and what leaders need to start saying out loud.
- Why girls begin dropping out of math and science as early as middle school, how cultural norms around “bossiness” suppress leadership potential, and what parents and organizations can do to intervene earlier.
- What Lisa says women who finally reach the executive table must do differently, and why most don’t.
Resources:
- Subscribe to the AI & The Future of Work Newsletter
- Connect with Lisa on LinkedIn or visit her website to learn more about her book.
- AI fun fact article
- On how to navigate life transitions with Bruce Feiler, award-winning author and popular TEDx speaker
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Episode Number : 381
James Cham is a Partner at Bloomberg Beta, the venture capital firm recognized by CB Insights as the
Show moreShow lessJames Cham is a Partner at Bloomberg Beta, the venture capital firm recognized by CB Insights as the #2 investor in AI. He has spent years backing the companies quietly building the infrastructure of tomorrow’s economy, including Orbital Insight, Primer, Domino Data Labs, and AppZen.
A Harvard CS graduate and MIT MBA, James brings a rare combination of technical depth, philosophical seriousness, and long-horizon investing perspective to every conversation.
In this episode, he challenges some of the most popular assumptions in enterprise AI adoption (including the idea that keeping humans in the loop is always the right answer) and makes a compelling case for why the moral and economic decisions we make right now will shape the nature of work for the next hundred years.
In this conversation, we discuss:
- Why the people who benefit from AI models, not those impacted by them, should bear full legal and moral responsibility for the harms they cause
- Why comparing AI to a flawless “Platonic ideal” is a mistake, and how the mathematical consistency of models is a massive advantage over noisy, unpredictable human decision-making
- The case for pulling humans out of the loop and why romanticizing your role in the process is exactly how organizations miss the real opportunity
- Why corporate America’s “gold star” approach to AI adoption, tracking how many employees used AI once this week, is a dangerous distraction from what heavy users are already doing
- How ancient wisdom and the biblical concept of creation in Genesis can help us navigate the moral responsibilities of building new technologies
- James’s three massive investment theses, including the untapped market for AI tools with high emotional intelligence and why developers spending over $50 a day on tokens are already living in the future
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