AI and the Future of Work: Artificial Intelligence in the Workplace, Business, Ethics, HR, and IT for AI Enthusiasts, Leaders and Academics

Send us Fan Mail
Maryjo 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 Maryjo “seeks the heat” in messy transformations and what she learned leading HR through turnarounds, spin‑offs, and large‑scale change.
How Kyndryl defined the “Kyndryl 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 Maryjo 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” (organizational 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

Send us Fan Mail
Trond 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:
Subscribe to the AI & The Future of Work Newsletter
Connect with Trond on LinkedIn
AI fun fact article
On How AI Will Transform Tax Filing: Insights from Daniel Marcous, Founder and CTO of April and Former CTO of Waze

Send us Fan Mail
Lev 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
Subscribe to the AI & The Future of Work Newsletter
Connect with Lev on LinkedIn
AI fun fact article: Blue Books Are Making a Campus Comeback via Axios, by Josephine Walker
On what most entrepreneurs get wrong when pitching to VCs.

Send us Fan Mail
Dr. 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 Health

Resources
Subscribe to the AI & The Future of Work Newsletter
Connect with Muthu on LinkedIn
AI fun fact article: Artificial Intelligence in Health Care: The Ethical Frontier via Conexiant
On the future of AI, Silicon Valley and Venture Capital

Send us Fan Mail
Dr. Jaime Lien is the Chief Scientist and a co-founder of Archetype AI, where she is building a foundation model that turns complex sensor data into meaning people can actually act on. A signal processing scientist by training, she earned her PhD working on RF imaging from satellites and later helped develop the first radar embedded in consumer smartphones at Google, before leaving with four colleagues to start Archetype AI. 
Recorded live from the floor of HumanX 2026, this lightning round explores how AI can read the rich, non-human signals all around us and translate them for the people who rely on them.
Jaime and host Dan Turchin dig into how machines distill signal from noise, why a reasoning and communication model matters more than a straight-to-action one, and why keeping a human in the loop is a requirement, not a feature, when the stakes are physical.
What You'll Learn
How AI separates meaningful signal from noise across the sensors already around us
Why Archetype builds a reasoning and communication model, not a straight-to-action one
Why keeping a human in the loop is treated as a requirement, not an optional feature
How interpretability and explainability have to be designed in from the start, not added later
Why discovering something new about the physical world matters more than automation alone
🎙️ Part of our HumanX 2026 compilation series. Listen to the full compilation here: https://www.buzzsprout.com/520474/episodes/19363520
Resources
Subscribe to the AI & The Future of Work Newsletter.
Connect with Jaime on LinkedIn.