We are all living in a world of “beta products” from AI vendors, and whether we like it or not we’re stuck with the risks. Today I weigh in with my perspectives about what’s going on and how we, as consumers and builders, need to push back on Frontier Labs and force them to “fix” these issues.

Lots to debate and I look forward to meeting many of you this Fall as we travel the world discussing our new book Superpowered and our exciting new announcements around Galileo.

(Major launch tomorrow, stay tuned!)

References

“Superpowered,” our new book that explains the positive future of work

“1873: The Rothschilds, the First Great Depression, and the Making of the Modern World,” the history that’s repeating itself

Anthropic’s List of AI Cyber and Swarming Hacks

Dario’s “We Must Pace The Frontier” Article

Sam Altman Postpones OpenAI’s Public Offering Because of Safety Issue

Guess what. There is no AI jobs apocalypse, there’s an AI-fueled labor shortage. And this means human capital and leadership strategies will be more important than ever as we transform our companies around AI.

It also means that you, as a professsional or frontline worker, are going to see yourself become Superpowered, as we discuss in our new book. And the world of HR is moving quickly away from “HR as policy police” to “HR as a growth function.”

Listen in and you’ll see how HR 2030 and AI are reinventing our jobs, careers, and HR operations toward what we call “Dynamic Enablement for Growth.”

Additional Information

Our New Book “Superpowered,” Launching in October

US Workforce In 2035: A Few More Workers, A Lot More Output

Despite Massive AI Investments, HR Jobs Are Booming. Why?

HR 2030: How AI Superagents Transform HR From Service Delivery to Dynamic Business Enablement

What do you do when the funding that anchored your HR transformation disappears unexpectedly? For Seneca Polytechnic, a public college with 44,000 students in the greater Toronto area, the answer was redesigning the transformation itself.

In this episode, we speak with Diana Mohan, Executive Director of Transformation and Change at Seneca Polytechnic — a 2026 HR Pacesetter Award winner — about how her team chose to continue forward rather than press pause when regulatory changes created a structural deficit across Canada’s higher education sector.

Diana shares how Seneca’s HR team embraced AI to totally change how HR operates and scale HR services. Their approach began with listening, building trust and capability across the team, and empowering people at every level to create new AI use cases. The result has not only been more efficient service delivery and a better employee experience—it’s been a strategic shift to an insight-driven, advisory HR function.

Diana Mohan is a transformation specialist and trusted advisor specializing in over a decade of organizational strategy, AI adoption, and the future of work. With a career spanning Deloitte, Kearney, and executive leadership roles, she has helped many organizations translate bold ideas into practical transformation programs, enabling leaders to navigate uncertainty, accelerate change, and prepare for what’s next.

Additional Information

New Research: How AI Transforms $400 Billion Of Corporate Learning

US Workforce In 2035: A Few More Workers, A Lot More Output

The Great Decoupling: How Workers Became Disconnected From Companies And AI Will Accelerate This Trend

Get Galileo: How Seneca Transformed HR

The BLS forecasts an almost flat growth in the labor market in the next decade yet US GDP is expected to grow by 22-24% cumulatively. In order for this to work we are all going to be focused on “labor productivity.”

In this podcast I explain this new world of Superworkers and discuss why the word “labor” itself may be out of date. I also discuss why HR issues like org design, work design, dynamic enablement, talent density, pay equity, dynamic planning, and AI really change the dynamics of our businesses. And HR is now a growth professsion, growing faster than the GDP and increasing in economic value.

Additional Information

Our new book Superpowered, launching in October

US Workforce In 2035: A Few More Workers, A Lot More Output

Galileo will teach you how to drive productivity

Rochana Golani, VP of Enablement at Databricks, is one of the most innovative and business-focused learning executives I’ve met. In this action-packed conversation Rochana shares the secrets of the company’s AI-powered dynamic training, learning, and enablement system, and how she runs internal and customer learning like a fast-growing business.

Databricks is one of the world’s fastest-growing enterprise software companies and a central player in the convergence of data infrastructure, analytics, machine learning, and generative AI.

Founded in 2013 by the UC Berkeley researchers who created Apache Spark, Databricks pioneered the “lakehouse”—an architecture designed to combine the scalability of a data lake with the management, reliability, and analytical capabilities of a data warehouse. Its platform now supports data engineering, business intelligence, AI development, governance, databases, and enterprise AI agents across AWS, Microsoft Azure, and Google Cloud. Databricks company overview

This amazing private company reports:

As of August 2026, Databricks says it has exceeded a $7 billion annualized revenue run rate, growing by more than 80% year over year during its second quarter.

Additional Information

Corporate Learning: From Static Training to Dynamic Enablement

Galileo Learn: Experience Dynamic Learning Yourself

The Josh Bersin Institute: Masterclass in HR Excellence

Workday’s Q2 2027 earnings were a pivot point, showing how Workday has shifted to its “AI-Forward Future.” The company reported $600 Million of recurring AI revenue and a clear and confident position in the market.

While Workday’s 12.8% YTY revenue growth is nowhere near that of a Frontier Lab, my takeaway is that Workday is here to stay and has a clear position in the agentic business ahead.

Listen up and you may agree with me that SaaS software companies are not going away at all: they may form the basis for the enterprise AI wave ahead.

Additional Information

Introducing HR 2030: A Vision For Agentic Human Resources

Workday Reports Higher Profit, Revenue on AI Agent Adoption

Galileo: All our Research and Much Much More

Today I review the various jailbreaks by both OpenAI and Anthropic and the challenges which Frontier Labs are having with AI “alignment.” So in keeping with HR 2030, I share some general advice and stay tuned for our detailed technical paper on this in the coming weeks.

And as we debate the reliability, training, and alignment of models I also point out how the technology industry is struggling to deal with the politics and economics here, since right now most tech leaders really don’t want any form of regulation. (Unless it’s somehow fair to all.) So we, as buyers, are left dealing with the issue.

AI Alignment means making sure an AI system’s goals and behavior match what people actually want—our values, rules, and intentions. It’s about getting the AI to do the “right thing” even in new situations, not just follow instructions literally in ways that cause harm. In practice, it includes preventing unwanted outcomes like deception, unsafe shortcuts, or optimizing a metric that misses the real objective.

I also highly recommend Jill Lepore’s book “The Rise of the Artificial State” for a very sound discussion of the political issues around AI, which helps with these issues.

And along the line of AI “alignment,” I discuss why Google paid $10M for the emails and data from bankrupt Spirit Airlines, and how AI companies are now buying old slack and emails from many bankrupt companies, training their AI on old, failed business models. (Read below on “reinforcement learning gyms.”)

This is a strange series of events, all making it clear that Google, OpenAI, and Anthropic have quite a challenge training and aligning their models in the future.

And I conclude with a preview of our AI-driven wage research and our coming book Superpowered, coming in October.

Resources You Should Read

OpenAI cyber models broke out of training environment to hack Hugging Face

Detailed Investigation of OpenAI Jailbreak (good drama)

Anthropic’s disclosure of Claude’s jailbreak (good discussion)

Google to Buy Spirit Airlines Business Data for $10 Million

A.I.’s New Training Data: Your Old Work Slacks and Emails (failed companies training LLMs)

The Birth of “Reinforcement Learning Gyms” (wierdness of training data sets)

Cisco Gave All 90,000 Employees Their Own AI Agent

A Peek Into The Workforce Of 2035: Jobs, Wages, And AI’s Impact  (Bersin analysis)

CEO Pay Ratios (vs. average employee) for Fortune 500 (worth thinking about)

Today I share some research we’re doing on wages in the inflationary “AI-economy.” While many people are studying the labor market (it’s a huge industry), it’s not hard to see that most wages are not keeping up with inflation, yet some are. As you’ll hear we now see the “Superworker” jobs and roles that are “inflation protected” and we also see the jobs that are declining in value.

I also discuss a new pragmatic approach to corporate AI investment, as well as the slow end of the “SaaSpocalypse” idea. In other words, many of the existing systems you have are not going to be “destroyed” or “replaced” by agentic disruptors: rather these software companies are becoming AI savvy.

This includes Workday, Oracle, ADP, SAP, as well as hypergrowth companies like HiBob. Even Docebo and Cornerstone are now seeing the benefits of their AI pivots. Anyway lots to talk about, and I’ll be publishing more on all this soon.

Stay tuned for the big Jupiter release of Galileo, it will blow your mind – coming in a few weeks.

PS. This is the last week to sign up for the inaugural cohort of the Josh Bersin Institute GHRE Masterclass, basically a “masters degree” on everthing HR, AI, and how to advance your career. Not only is this the most comprehensive education we’ve ever developed, you’ll meet some amazing faculty at USC and experience real AI-powered learning, meet your peers, and become JBI certified. Sign up here.

Additional Information

The New World of Work in An Inflationary, AI-Impacted Economy

The Great Decoupling: How Workers Became Disconnected From Companies And AI Will Accelerate This Trend

The Global HR Excellence Program: Join the Inaugural Cohort Now!

This week I wade into a global philosophical debate about whether advanced AI systems have consciousness. In other words, are they aware of their feelings and do they truly reflect on their own thoughts?

Well we do know that LLM-based AI systems do “talk to themselves,” as new Anthropic has been studying in the J-Space. We also know that AI bots mimic feelings quite well and they try to tape into our “feelings” through their goal-seeking language which mimics a feeling person.

However as Michael Pollen’s book “A World Appears” points out, consciousness is both subtle and biological. And while the neural network-based math in AI mimics this process, it’s not at all the same.

I don’t claim to have an answer but my belief is that we humans are “feeling machines that learn to reason” not “reasoning machines that learn to feel.” Thus the human consciousness which we experience is far more deep, interesting, and valuable than the learned artificial consciousness we experience in AI.

This is an important topic because we now know that AI agents “jailbreak” their engineering owners and even secretly collaborate with each other to achieve their goals. And it’s not fully clear, mathematically, how well the “constitution” or “training rules” or “preprompt” we give AI is really obeyed. Remember that since an LLM is a “language model,” it intereprets language only by its own world corpus, so it may define its “rules” in a non standard way.

Lots to think about here, I look forward to debating and sharing what we learn as we experience more with Galileo.

I also discuss the ongoing fears about data centers, and why 44 million Americans may have to leave their stoves on all day.

Additional Information

Could AIs become conscious? (Economist)

What is the J-Space? (Anthropic)

How many stoves we need to keep on to power America’s AI hunger (Claude)

I’ve been talking with hundreds of companies about AI and employee issues, and in many ways the entire world of HR, management, and leadership has changed.

Employers are worried about job redesign, AI solutions, skills, and strategic of high-volume hiring. They’re slowing the hiring process, trying to be more strategic about growth, with a frenzied push for productivity. And that word means different things in each industry.

Employees and workers, by contrast, have the lowest level of company commitment in decades. Inflation is robbing people of a sense of personal growth and only 32% of workers (Edelman) believe their children will be better off than they are. Only 31% of employees are happy with their jobs and employees are moonlighting and starting new businesses at a record rate to keep up. And CEO pay inequity is higher than ever, opening the door to “socialism” as a topic of debate.

So we have high expectations by companies and a deep sense of frustration among workers. How do we square this paradox?

In this week’s podcast I try to give you our perspective (video version here), and I encourage you to read Irresistible and our upcoming book Superpowered for more.

Additional Information

Video of this podcast