The Josh Bersin Company

This week we launch our new book “Superpowered, how AI Unlocks The Power of People, Leadership and Teams. Based on more than 100 case studies and years of research on organizations and careers, this book sets the stage for your future as a Superworker, Supermanager, or Supercompany. Whether you’re a human resources professional, a people manager, a business leader, or a professional preparing for the future of work, Superpowered offers a way to think more clearly about AI and the opportunities it creates for human contribution. No prior AI expertise is needed to benefit from Superpowered – the book introduces its own frameworks, examples, and practical guidance for adapting to AI. For readers of Josh Bersin’s Irresistible, Superpowered acknowledges the reality of work today, and prioritizes preserving the employee experience and the human contribution to our organizations. For those starting with Superpowered, Irresistible offers a complementary blueprint for leading teams through change and disruption to create enduring companies that thrive with improved customer satisfaction, employee retention, and business agility. What Business Leaders Say “Superpowered is the clearest roadmap I’ve seen for turning artificial intelligence into human advantage: more capable workers, denser talent, and companies that grow by developing people rather than churning through them.”—Laszlo Bock, CEO coach and NYT bestselling author “AI is moving from tool to teammate, and that shift is going to change how every company operates. The companies getting this right are redesigning their operating models around what people do best. Superpowered lays out how to make that shift, and it’s a book that every leader needs to read.”—Aneel Bhusri, Co-Founder, CEO, and Chair, Workday “For decades, Josh Bersin has helped leaders anticipate how work is changing. In this important new book, he goes beyond describing AI to explain how organizations can redesign work so that technology amplifies, rather than diminishes, human potential. This is an optimistic, practical and timely guide for anyone leading organizations through the AI era.”—Lynda Gratton, Professor, London Business School, and author of Living the 100-Year Life: How to build a career that lasts and a life you love. “We know AI is transforming our jobs and lives, yet many of us have been left wondering exactly how this change will unfold. Superpowered offers both an inspiring vision of the future and practical, real-world advice on how organizations can create a more innovative, productive, and humane workplace.” —Arianna Huffington, Founder & CEO, Thrive Global Read details, endorsements, and testimonials. Order on Amazon today. Chapters (00:00:00) - Introducing Superpowered: AI and Work (00:00:38) - Lessons from Irresistible: Empowering People in Organizations (00:01:47) - Economic Inequality and the Role of Capital vs Labor (00:02:24) - AI as an Empowering Force, Not a Job Killer (00:04:38) - Growth vs Cost-Cutting: How AI Adds Value (00:05:00) - The Driverless Car Analogy: Redesigning Work (00:06:33) - Agents as Digital Workers and Scaling Human Capability (00:08:37) - Will AI Replace Leaders? The Human Spark of Creativity (00:10:10) - Careers, Longevity, and Continuous Learning in the AI Era (00:11:46) - Book Background and Closing Thoughts

There’s a big flurry of interest in Job-Task Analysis (an old discipline) to break down jobs into tasks, categorize and inventory these tasks, and then “Voila,” you can build AI agents to automate these tasks. It sounds like a great idea. So data providers like Lightcast, Draup, SAP (TechWolf), Reejig, and Workday (using Stanford data) are busy building these huge “Job-Task” data sets so you can now look at your company or department as a “basket of tasks” and apply AI to build just the right agents to streamline work. (And also make decisions like centralizing some tasks or building better learning to cross-train people for such tasks.) As you’ll hear me describe, this kind of work is extremely valuable for regulated, structured, safety-related, and operational jobs. If we know that every airline pilot has to master the task of “lowering landing gear at the right speed and time” it makes perfect sense for the aircraft to do this (or tell the pilot) automatically. Similarly if every sales person has to update Salesforce in a 2 minute “task” we should build an agent to do it accurately. So there are task automation opportunities in every business area, every function, and every job. The challenge is that these “tasks” don’t always stand alone: they’re related to broader job roles and business processes. So taking an inventory of tasks is great (we know all the tasks an HR Business Partner does, for example), but we have to think strategically about which of these are suited for AI, which are suited for regular IT automation, which could be outsourced, and which are very “context sensitive” and may need to be treated differently. In our interviews with clients we find a hierarchy to this work. First, what is the business goal for this job or work? Second, what are the broader product, service, or customer outcomes we’re trying to achieve? Third, what are the steps or tasks and are they “rigid or mandatory” or are they “judgemental and optional?” Fourth, how do these individual tasks relate or chain together? And Fifth, what human or technical or judgement skills are needed? In other words, just listing the tasks and knowing the “size” of each is not enough. We really do need to re-engineer these things in the context of outcomes, customers, important workflows, and the subtlties of “doing the task well.” And when this is done well we can use it for recruiting, training, performance management, and AI agent development. What we want to prevent is a project to do task analysis for its own sake, because this kind of work has been around for decades and it’s often used primarily for safety, compliance, operations, and highly structured work. I think that AI, with all its learning capabilities, may make this domain far bigger than ever before. So this domain is a very fast-growing part of HR 2030 and our ongoing work to “agentify” our companies. We are doing case studies in this area now – please contact us if you’d like help or share your work intelligence project. More detailed article here. Additional Information How To Do Job-Task Analysis Workday Introduces Work Intelligence to Help Customers Design Work for AI Lightcast Work Intelligence Draup Task and Work Intelligence Guideboooks TechWolf (SAP) Work Intelligence Reejig Operating System for Work Chapters (00:00:00) - Introduction to Task Intelligence (00:01:33) - How Task Data Is Built from Jobs (00:04:32) - Where Task Analysis Works Well (00:06:32) - The Risk: Institutionalizing Old Ways of Working (00:10:07) - Lessons from the Skills Taxonomy Era (00:12:17) - Finding Value: Cross-Functional Job Consolidation (00:14:41) - Process Mining as a Related Approach (00:15:20) - Using AI and Digital Twin for Process Mining via Email (00:18:05) - Data Retention and Practical Challenges (00:19:16) - Final Thoughts: AI Must Serve Business Goals

Today, after in-depth meetings with Workday, SAP, UKG, Dayforce, Hibob, Gloat, and others, I’m ready to say “the SaaSPocalypse is over.” HCM is poised for massive growth ahead. And there’s more – I describe the five new “redefining” features of Agentic HCM (Human Capital Management) platforms and why this may unlock a $10 Billion new revenue market for major HCM players. You as a buyer or consumer of these systems have to start to think about these systems differently. Rather than see them as Payroll and HR “boat anchors” which you have to buy, they’re now “growth enablement platforms.” This is all discussed in detail in our HR 2030 research and advisory services, and I’ll be talking publicly about this at Unleash and other conferences this Fall and next year. Stay tuned for more to come. Additional Information HR 2030: Dynamic Enablement for Growth Our new book “Superpowered” – how AI empowers employees, leaders, and companies. (preorder) Get Galileo: The World’s AI Intelligence agent for management, leadership, and HR. Our new research partnership with Workday Chapters (00:00:00) - Introduction: HCM Market's Big Comeback (00:01:06) - Trend 1: Multifunctional Agentic Workflows (00:01:51) - Trend 2: Conversational Interfaces (00:02:14) - Trend 3: Embedded Workforce Benchmarking Data (00:03:55) - Trend 4: Platforms for Building Your Own Agents (00:04:18) - Trend 5: Governance and Agent Management Tools (00:05:41) - Market Consolidation and Impact on Small Vendors (00:07:28) - Rising HCM Revenues and Value Shift (00:08:07) - Cross-Functional Value Examples from SAP, Workday, UKG (00:08:48) - ROI Modeling and Growth-Oriented Use Cases (00:10:09) - Example Transaction and Token Cost Economics (00:11:47) - Market Size Estimate and New Revenue Potential (00:12:26) - Compute Costs Declining Despite Revenue Growth (00:13:25) - Budget Concerns and Reframing AI as Growth Tool (00:14:11) - Real Benefit of AI: Growth, Not Headcount Cuts (00:15:17) - Decline of Small Vendor Innovation and Consolidation (00:16:58) - From Administrative Systems to Capacity Management (00:18:07) - Agents as Valuable Employees Needing Management (00:20:18) - Closing Thoughts and Invitation to Connect

Workday Rising Announcements: Sana as core interface, 17 major new Superagents including “autopilots” (that we call “monitoring agents”), Sana Concierge for self-service, Sana Coach for performance coaching, massive improvements to talent acquisition suite, Workday “work intelligence” to break down jobs into tasks and help build capacity and workforce planning, a direct interface to Claude, and the acquisition of C1.ai to identify and secure all agents in your company. I also discuss the challenge all major software companies have selling “usage-based” or “token-based” pricing, and why you, as a buyer, should start prioritizing your agent investments. I also explain why “Forward Deployed Engineering” or professional services is now highly strategic to corporate AI software providers. I also discuss our partnership with Workday which you can read about here. We are now working closely with Workday to bring you the realities of HR 2030 with tools, education, and advisory services. And most exciting of all, Galileo will be embedded into Workday. Our new book Superpowered is available now! Additional Information The Research Partnership between Workday and The Josh Bersin Company The Leader’s Guide To Multi-Agent AI Architecture US Workforce In 2035: A Few More Workers, A Lot More Output HR Intelligence Goes Enterprise: The Galileo Jupiter Release Chapters (00:00:01) - Workday Overview and Company Background (00:01:43) - Workday Rising Announcements: Sana, Agents, and AI Strategy (00:02:52) - Leadership, Agent System of Record, and Talent Acquisition (00:05:01) - Customer Enthusiasm and New Agentic Tools (00:06:21) - Our Partnership with Workday: HR 2030 and Galileo (00:08:18) - Competitive Landscape: SAP, Oracle, and Mid-Market HCM (00:09:31) - Workday vs SAP Strategy: Few Sophisticated Agents vs Many (00:11:14) - Process Discovery and Sana's Sophistication (00:13:05) - The Cost Problem: Monetizing AI Consumption (00:16:29) - AI as a Growth Tool, Not Just Cost Cutting (00:18:04) - Forward Deployed Engineering and Implementation Challenges (00:21:48) - Closing Thoughts and Upcoming Events

Now that corporate AI tools from Workday, SAP, Oracle, Databricks, ServiceNow and many others have hit the market, it’s time to think about how we apply AI strategically. In this podcast I introduce the idea of Business 2030, a framework built from our HR 2030 architecture. The simple story is as follows. While it’s easy to think of gen AI as an “automation” technology, its real value is in this ability to integrate vast amounts of data and predict, act, and learn from this stream. Well our companies are set up to operate as functional hierarchies, as we talk about in our research on the post-industrial age. What if you rethink or redesign your company around end-to-end customer experiences, and the functional areas of research, engineering, product design, manufacturing, marketing, and sales were “branches” of this core? It’s a big idea, but to me it’s the future we all want. Programs like “customer data clouds” were first generation attempts, now it’s time to go further. And for HR leaders, you can help steer your company in this direction because the functional people hierarachies are often getting in the way. I’ll be talking more about this throughout this Fall and 2027, and it’s all part of the AI reinvention that impacts every employee and leader. Also, this week we’re launching our new book Superpowered, which describes the new AI-fueled world of “Superworkers,” “Supermanagers,” “Superleaders,” and “Supercompanies.” We’ll be sharing the book at Workday Rising, Unleash, and the US HR Technology Conference this month. Please join the waitlist it will be available on Amazon soon. I look forward to seeing many of you around the world as we come to the Fall conference season with excitement and much to share. And more information on Workday coming this week. PS: If you want to dive into any of the research, education, or tools we offer, sign up for Galileo Suite, which includes access to all our research and Galileo Learn, more than 800 courses and tools to help you understand this new world. Additional Information Understanding The Post-Industrial Age HR 2030: The New Growth Operating Model for HR HR Intelligence Goes Enterprise: The Galileo Jupiter Release The Leader’s Guide To Multi-Agent AI Architecture Chapters (00:00:00) - Intro: Workday Rising and Business 2030 (00:00:27) - AI as Automation vs Redesign (00:02:14) - Foundations: Customer Closeness and Delivery (00:05:05) - The Functional Hierarchy and Industrial Scale (00:06:52) - Speed, Innovation, and the BYD Problem (00:08:19) - Mercedes vs Tesla: Subscription Services Misstep (00:09:48) - Rethinking Company Operations: Business 2030 Defined (00:10:52) - Cross-Functional Silos in Sales and Product (00:12:23) - Customer-Centric Super Agents and Amazon Example (00:14:07) - ERP Limitations and SAP's Industrial Bias (00:15:04) - Product Management and Customer Data Insights (00:16:24) - Customer Lifetime Value and Frontline Burden (00:17:04) - Frontline Workers Absorbing Systemic Failures (00:18:25) - HR's Role in Business 2030 Transformation (00:20:12) - HR as Technologists and Cross-Domain ROI (00:21:41) - Closing Thoughts and Upcoming Events

This week SAP explained its new Joule Work and Autonomous Enterprise strategy at its SAP Connect conference. As you’ll hear, SAP is building a solid set of AI agents to compliment and automate many of its business processes and it’s now all live. What does this mean for HR? Well SAP customers now have lots to think about – including how Joule may interact with other agents, what agents and assistants to use, and how to interconnect the SAP Knowledge Graph with non-SAP data. It’s a solid strategy for automating existing business processes, and it’s now up to SAP customers and consultants to learn how to use all these agents for business transformation. Moving to this second topic, I discuss our new research on “Managing a system of agents,” and how you should think through, architect, train, and manage your new family of AI workers. I talk about how specialist agents and Superagents fit together, and I encourage you to read my in-depth article on this important issue. Our new HR 2030 guidebook is available this week. The future of business and HR is not just about what tools you buy, it’s now up to you (all of us) to decide how we stitch our new self-learning agents together to create scale and growth, not just small productivity gains. SAP is in a good place to help with this transformation, but so is Workday, HiBob, and many others. Join our HR 2030 program for all the details, license Galileo, or enroll in our new Global HR Excellence Certification to learn all the details. Additional Information Building A Safe Multi-Agent AI Operating System: Lessons from HR and Ferrari Chapters (00:00:00) - Introduction and Week Overview (00:00:27) - SAP Connect: The Autonomous Enterprise Vision (00:01:18) - Joule Work and Agent Infrastructure (00:03:00) - SAP's Missing Vision for Future Business Processes (00:03:54) - Agent Governance and Safety Tools (00:04:39) - SuccessFactors Agent Stacks and Integration (00:05:15) - SAP as a Software Company vs Problem Solver (00:07:07) - SAP's HR History and SuccessFactors Acquisition (00:08:17) - Acquisitions and Legacy Naming at SAP (00:09:07) - Overall Impressions of SAP Connect (00:10:12) - Workday Rising Preview (00:10:39) - Multi-Agent Architecture and Alignment Risks (00:11:22) - Pharma Example: Agent Overreach and Legal Risk (00:13:22) - Protecting Against Agent Misbehavior (00:14:24) - Human Parallel: Specialization and Ethics (00:15:37) - Why Specialization Matters More Than Ever (00:17:02) - Designing Networks of Specialized Agents (00:17:42) - HR 2030 as an Agent Operating System (00:19:46) - Multi-Agent Research and Market Landscape (00:20:54) - Reflections on Tech History and Survivorship (00:21:51) - The J Curve of New Technology Adoption (00:23:02) - Closing Remarks and Next Steps

There’s a raging debate going on about something called Superintelligence: the idea of a massive AI network that knows everything and does everything for us each day. Bill Gates, Dario Amodei, Elon Musk, Sam Altman, Peter Thiel, and Nick Bostrom are all talking about this, and they’re painting a future where we won’t have to work and entire industries and professions will vanish. In this podcast I try to demystify (and debunk) a lot of these claims, and I postulate that the world may get messy but our imperfect, lovable human selves will still rule the roost, so to speak. Our new book Superpowered is all about this new world, and I think it’s more positive than you think. Also listen to my story about my trip to the Ferrari factory in Maranello Italy, and you’ll see how AI may not be as “all-powerful” in our real world as these technologists may think. Additional Information Bill Gates on AI Superintelligence Elon Musk on AI Superintelligence Dario Amodei on AI Superintelligence Nick Bostrom on AI Superintelligence Superpowered: How AI Unlocks the Superpower of People, Leadership, and Teams We’re All Talking to Each Other Less Than We Did a Decade Ago Why Technology Failed to Transform Schools Chapters (00:00:00) - Introduction: Tech leaders' superintelligence claims (00:01:24) - Effective Altruism and abundance movement critique (00:02:02) - Lessons from social media's impact on society (00:03:25) - Why humans get up in the morning: purpose vs pleasure (00:04:59) - AI's limits in addressing human psychology (00:07:13) - AI as a tool, not a replacement for human nature (00:07:39) - Visiting the Ferrari factory: human craftsmanship (00:11:10) - Ferrari's manufacturing philosophy and human touch (00:12:57) - Uniqueness, legacy, and refurbishment at Ferrari (00:15:06) - What Ferrari teaches us about human desires and AI (00:16:02) - Multi-agent AI and personal application of tools (00:17:02) - Risks of AI manipulation, lessons from social media (00:18:31) - Education technology's mixed track record (00:19:40) - Closing thoughts: philosophy, technology, and business

I’m really excited about the potential for Personal AI Agents. While GrokBot and Muse and Microsoft Autopilot (Scout) are very young (and not at all mature yet), we can now clearly see how personal AI is going to transform and disrupt our business lives. In this podcast I explain the architecture of HR 2030, our reference blueprint for Agentic HR. You can see how personal agents, action agents, rules agents, monitoring agents, data agents, and Superagents all work together. And it’s important to think this through so you can plan your vendor selection, tech architecture, security architecture, and AI staffing and “management” plan. Some important concepts: HR “agents” do more than HR – they enable dynamic growth, productivity, and cost savings – so take a problem-oriented view Clearly defined agents won’t misbehave, as you’ll see in our architecture Companies will implement Superagents based on business priority, not just for ideation SaaS incumbents are likely to deliver many of these agents, so SaaS Apocalypse may be over Agent training, context, and maintenance is critical – and this gives you scale and growth – so new jobs are needed Frontier labs may or may not survive this enterprise model Personal AI agents will be massive and likely disrupt many HR tech vendors. Lots to learn about here, read more on HR 2030 and call us or get Galileo to learn more. Chapters (00:00:00) - Introducing HR 2030 Architecture (00:01:02) - Three Tiers: Super Agents, Agents, Personal Agents (00:02:20) - Building the Agent Database and Use Cases (00:03:23) - Strategic Planning vs Buying Point Tools (00:04:13) - The SaaS Apocalypse Myth (00:04:47) - Rise of Personal Agents (Muse, Grokbot, Scout) (00:05:43) - What a Personal Assistant Could Do For You (00:06:24) - Why Personal Agents Beat Vendor Platforms (00:07:28) - How Personal Agents Know Everything About You (00:08:06) - Positive Uses and Privacy Considerations (00:09:34) - The Digital Twin in Practice Today (00:10:14) - Personal Agents Helping Employees Grow (00:11:01) - This Is Coming - Being Realistic (00:11:25) - How Agents Will Interact With Employees (00:12:09) - Impact on HR Software Vendors and Coaching Tools (00:13:42) - How to Access and Engage With HR 2030 (00:14:17) - Galileo's Role and Ongoing Development (00:15:48) - Falling AI Costs and Open Source Models (00:16:21) - Copilot and Running Open Source Models Cheaply (00:16:50) - Business 2030: Dynamic Enablement for Growth (00:17:12) - Not About Headcount Reduction (00:17:36) - Upcoming Conferences and Closing

Andreas DeNeve, founder of TechWolf, believes AI can “infer” your skills with great precision. After years studying this problem TechWolf has built a variety of AI language models to observe and identify your skills and tasks, which then form the basis of many decisions in business. TechWolf monitors and indexes all your work activity and then builds a “skills context graph” to show you a skills map of your company. This is a big idea, one which companies like Eightfold, Seekout, Findem, Sana and many others are pursuing. In TechWolf’s platform employees retain full control, validating inferred skills in the flow of work, with a 90%+ acceptance rate across white- and blue-collar workers. The interesting part of this story is that this approach competes with the massive industry of testing and industrial psychology, used for decades to assess fit for a job. Andreas describes the company’s successes and how they’re building an entire “work intelligence” platform for AI transformation. Skills Inference, which is a new AI application, competes with testing and assessment, which is used for screening and recruiting. Andreas discusses how inference is used for talent management, workforce planning, and AI enablement and transformation. Now TechWolf positions its platform as a system to help discover what tasks and skills can be automated by AI. (Now called “task mining.”) This new market is growing quickly, so it’s important to learn about products like TechWolf in your new HR 2030 architecture. Additional Information Introducing HR 2030: A Vision For Agentic Human Resources The Four “New SoftSkills” We Need To Thrive In The Age of AI (pod) How To Take A Pragmatic (and winning) Approach To Skills AI Transformation From the Frontlines (pod) Chapters (00:00:00) - Introduction to TechWolf and Andreas Deneve (00:02:35) - Andreas's Background and Founding TechWolf (00:03:59) - The Origin of Skills Inference from Work (00:05:14) - How Skills and Task Inference Technology Works (00:07:50) - Handling Non-Digital and Frontline Work (00:10:38) - Data Readiness and Honesty with Clients (00:12:08) - Employee Data Ownership and Transparency (00:13:58) - Evolution of Use Cases: Talent to Workforce Planning (00:16:01) - Rise of Work Intelligence and Task Proficiency (00:17:09) - AI Transformation and Role Redesign Use Cases (00:18:09) - Measuring AI Usage and Cost Efficiency (00:19:36) - How Insights Are Delivered: Agents and Platforms (00:22:31) - Biggest Challenges in Building TechWolf (00:24:19) - Expansion to the US and Future Plans (00:25:31) - Closing Thoughts and Final Wisdom

News Corp, with more than $9 billion in revenue, is one of the most important and iconic media and digital real estate companies in the world. The company owns mastheads like The Wall Street Journal, Barrons, The Times, The Sun, New York Post, California Post, Factiva, Realtor.com, and other media and digital businesses that we rely on for news, information and commerce. News Corp also owns Harper Collins, a $2.3 billion publishing empire. With around 22,000 employees, News Corp provides much of the news, information, insights, and perspectives we consume around the world. The company has major intellectual property holdings in its book, media, and real estate businesses. How does News Corp view AI and its opportunities and threats? As you’ll hear from Ruth, News Corp sees AI as a distribution channel, not a competitor. And as we discuss, one could argue that News Corp is a critical part of the AI industry since they feed the AI tools we use. Without News Corp’s content, AI wouldn’t be very useful. Ruth Allen, global CHRO, is responsible for global talent and leadership, real estate and facilities, and corporate communications and security. Her vantage point, as a senior executive, gives you a clear perspective on the ongoing role that journalism, media, publishing, and informed opinion play in the new era of AI. Ruth also explains how News Corp hires, manages, attracts, and engages its high powered journalists and publishing professionals in this changing world of content. Additional Information News Corp Company Overview News Corp Q4 2026 Investor Call Chapters (00:00:00) - Introduction to Ruth Allen and News Corp (00:00:37) - News Corp's Business Segments and Global Reach (00:02:33) - Culture and Decentralized Organization (00:05:51) - Leadership Development Strategy (00:08:05) - Global Mobility and Organizational Agility (00:08:31) - News Corp as an AI Inputs Company (00:11:12) - Content Value vs Technology Commodity (00:11:48) - Attracting and Retaining Journalism Talent (00:13:50) - Coordinating HR Across Business Units (00:14:36) - HR Technology Platforms: Workday and ServiceNow (00:17:21) - AI Adoption Mindset and Training Culture (00:20:04) - AI Empowerment and Debating with AI Tools (00:20:35) - Scaling AI Innovation Across Business Units (00:21:41) - Early Career Hiring and Development in the AI Era (00:24:31) - The Global CHRO Role and Risk Portfolio (00:27:21) - The Future Relevance of HR in an AI World (00:28:40) - Closing Remarks

Perspectives on AI safety and alignment, and what you as a business leader need to know. I’m attaching a good set of resources for you to read, this is a fascinating issue. Second, I introduce the idea of Business 2030 – the new, ai-powered operating model for business, which is coupled with HR 2030. As you’ll hear, the new world of HR is going to become essential to your company’s AI business operating model in the coming years. So all the details in HR 2030 are urgent. Reading and Background AI Doesn’t Need to Slow Down. The AI Industry Needs to Grow Up. (substack) HR 2030: How AI Superagents Transform HR From Service Delivery to Dynamic Business Enablement Galileo Pluto Release: Enterprise HR Intelligence in Any AI Agent “Superpowered,” our new book that explains the positive future of work AI Alignment Approaches OpenAI Discloses Six New Incidents of ‘Concerning’ A.I. Behavior Google DeepMind launches institute to widen the AGI debate Claude’s New Constitution Microsoft AI’s “Code of Conduct” OpenAI’s Model Behavior Spec Is AI Conscious? (Sam Harris, Cameron Berg – worth watching) Chapters (00:00:00) - Intro: Europe trip and today's topics (00:00:39) - AI safety as an engineering problem, not research (00:03:01) - Regulatory capture, money incentives, and business legitimacy (00:04:16) - Aligning agents as a corporate buyer (00:04:56) - HR 2030 reference blueprint and agent architecture (00:06:21) - Business 2030: dynamic enablement and AI transformation (00:08:08) - Case study: software vs organizational readiness (00:09:10) - Superworkers, embedded AI, and idea constraints (00:10:46) - HR becoming business-centric (00:12:13) - Client example: beverage company restructuring (00:13:19) - Career opportunities and upcoming events (00:13:49) - Galileo Jupiter release and closing

Today we launch the Jupiter release of Galileo, which we call “HR Intelligence for the Enterprise.” In this podcast I explain the history of Galileo, its evolving and new technical architecture, and how AI agents can revolutionize every aspect of an employee’s work life. As you’ll hear, Galileo is now the most trusted, efficient, portable source of global HR and management intelligence, available on: Microsoft Copilot Workday ServiceNow HiBob Gloat ChatGPT, Claude, Gemini, and open source AI agents. I explain how our business model of research, advisory, education, and consulting has been transformed by Galileo, and how Jupiter gives you the most amazing new experience for your managers, employees, and HR teams. Listen in, and here are more resources for your information. Galileo Jupiter Resources Galileo Jupiter Introduction Blog Jupiter Release Technical Whitepaper Jupiter Explainer Video Galileo Jupiter Overview and Q&A Galileo for Microsoft Copilot Galileo for Workday Galileo for ServiceNow Galileo for HiBob Galileo for Gloat Chapters (00:00:00) - Introduction: 30 Years of Human Capital Research (00:01:47) - The Research Membership Business Model (00:04:46) - Why This Work Matters More With AI (00:05:56) - Building Galileo: From Prototype to Full Tool (00:08:09) - Making Galileo Portable Across AI Platforms (00:10:16) - Rethinking the Corpus: Birth of ARC (00:12:19) - Benchmarking Accuracy and the Jupiter Release (00:15:02) - New Data, Faster Delivery, and a New Website (00:16:04) - Beyond HR: Galileo for Managers and Employees (00:16:38) - Deep Microsoft Copilot Integration (00:18:15) - Ecosystem Support and Real-World Use Cases (00:20:16) - Closing Thoughts and What's Next

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 Chapters (00:00:00) - AI Doomsday Warnings and Corporate Hypocrisy (00:00:50) - AI Values Reflect Society's Flaws (00:02:35) - Comparing AI Risk to Boeing and Product Safety (00:04:05) - Corporate Liability and Legal Risk of AI Vendors (00:05:16) - Who's Responsible When AI Causes Harm (00:06:15) - Design Flaws and the Jupiter Launch Preview (00:06:59) - Defense, Ethics, and the Oppenheimer Parallel (00:09:16) - Commercialism, Greed, and Historical Parallels (00:10:29) - Railroad Era Comparison and Financial Mania (00:11:05) - Political Divide Over AI and Data Centers (00:12:55) - Data Center Politics and Mobility of Capital (00:13:49) - Software Builders' Dependence on Reliable Models (00:14:24) - Everyday AI Mistakes and Acceptable Risk (00:15:50) - We're All Part of a Giant Beta Test (00:16:25) - Closing Thoughts and Jupiter Teaser

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 Chapters (00:00:00) - The AI Labor Shortage Thesis (00:01:21) - Jobs Boom Driven by AI Infrastructure (00:02:26) - Shrinking Labor Pool and Retention Challenges (00:03:00) - Introducing HR 2030 Blueprint (00:04:42) - Redesigning Jobs and Functional Silos (00:06:00) - Managing AI Agents as Superworkers (00:07:36) - Redefining HR's Mission as Growth Enablement (00:08:53) - Asking About Business Growth Strategy (00:10:32) - Retail Case Study: Growth-Aligned HR (00:12:25) - HR as a Growth Function, Not a Cost Center (00:13:56) - Closing Thoughts and Upcoming Galileo Release

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 Chapters (00:00:00) - What Works: The Future of Work (00:00:41) - HR Pacesetter Award Winners: Diana Mouhand (00:01:52) - In the Know: The HR Team at Seneca Polytechnic (00:02:47) - How HR is on a transformation journey (00:05:13) - How Cognizant Went From Transformation to a Pivot (00:06:59) - How To Build Trust in AI at Seneca (00:12:19) - The HR org chart: AI Agents (00:16:10) - What Makes an HR Team Flexible in the Age of AI (00:18:10) - WSJD Live: The AI Transformation

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 Chapters (00:00:00) - Labor Market: The super worker (00:04:17) - Employee mobility and job and org redesign (00:06:44) - Beyond HR: The Role of AI in Business

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: More than 20,000 customers Approximately 70% of the Fortune 500 More than 10,000 employees More than 8,000 cloud, software, and consulting partners. 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 Chapters (00:00:00) - Interview With Databricks's Roshana Golani (00:00:24) - Databricks CEO on the Disruptive Technology (00:01:36) - How to Get Empowerment at Databricks (00:03:16) - WSJD Live: Data & Machine Learning Lead the Way (00:08:09) - Teaching and Enablement: The New Paradigm (00:11:01) - How to Build a Better Solution with Databricks (00:14:52) - WSJD Live: The Skills Taxonomy (00:15:22) - What do you think happens to course content? (00:17:13) - The source of content in the Learning Infrastructure (00:22:52) - Databricks: The go-to training solution for business users (00:24:25) - In the Era of AI, Who Will Lead the Transformation? (00:26:57) - Subject Matter Experts and the Learning Infrastructure (00:28:20) - A Day in the Life of Leadership Development

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 Chapters (00:00:00) - SaaS vs. AI Software: Will SaaS Replace (00:05:49) - SANA and Workday: The Enterprise Connection

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) Chapters (00:00:00) - AI in the Political System (00:03:24) - Will AI Eliminate Jobs? (00:08:08) - The role of agents in IT security (00:10:01) - The Personal Agent in HR 2030

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! Chapters (00:00:00) - AI and the HR 2030 Workforce (00:04:07) - Wage increases and the labor market (00:06:53) - Employee Experience and Pay (00:08:08) - AI and the Corporate Code (00:10:20) - Will The Outsourcing of Recruitment Be Hurt? (00:13:35) - Will AI Replace the HR Software Companies? (00:17:46) - One more thing. This week is the last week to sign up

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) Chapters (00:00:00) - Does AI Have a Conscious Mind? (00:13:00) - OpenAI's Need for Power (00:18:17) - Microsoft's Galileo: The New and Improved

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 Chapters (00:00:00) - Employment, Financial Rewards and AI (00:06:42) - What Is the Fear of Data Centers? (00:09:08) - The Future of Work

AI-powered recruiting has so much potential, yet job seekers, recruiters, and executives remain frustrated. This massive $100+ billion market is filled with AI systems that work very well, yet as you’ll hear, this market is still immature. Not only are job seekers increasingly frustrated with their difficulty finding a job, employers are complaining that they’re flooded with fraudulent resumes. And last week we learned in the WSJ that the North Korean government is using AI-fueled recruiting to place fraudulent candidates right into our IT departments. Plus this week I also found out that the off-the-shelf LLMs are biased toward candidates who “slop” their resumes with their particular technology. ZipRecruiter and other firms found that only about 18% of active job seekers say they feel good about their overall job search and 47% said they were ghosted, and only about 27% feel confident they’ll find a job. What a mess. As I explain in this podcast, AI is not a panacea to solve this problem. Additional Information The Talent Acquisition Revolution: How AI is Transforming Recruiting HR 2030: How AI Superagents Transform HR From Service Delivery to Dynamic Business Enablement Learn about AI in HR: The Global HR Excellence Certification Get Galileo: The Recruiter and HR professional AI Superagent Chapters (00:00:00) - Will AI Revolutionize Recruitment? (00:10:34) - The War for Recruitment

Today I discuss Workday and the potential Silver Lake buyout, Meta’s personal AI strategy and it’s potential for business, update on Galileo, and our new research on frontline work. Most of today’s podcast is “analyst perspectives” but lots of direction is now clear. The GHRE Global HR Excellence masterclass starts in September: if you want a 12 week in-depth “Masters Degree” level dive into HR, talent, leadership, and AI (with hands-on and new tools), as well as business school level case studies, join us! (Sign up here.) Additional Information Mark Zuckerberg blog on personal AI The Business of Frontline: Five Types Of Frontline Work Galileo Suite: HR Intelligence For You, Your Employees, and Your Company Chapters (00:00:00) - Sliver Lake vs. Workday: Going Private (00:03:10) - Mark Zuckerberg on Facebook's AI (00:09:38) - The Future of HR Data: Galileo and the AI Assistant (00:12:22) - McKinsey & Company: Trusting Our Research (00:14:45) - The Business of Frontline Work

The job market is changing in unpredictable ways. Human Resources, a profession often considered optional and filled with bureaucracy, has been a target for AI disruption. Yet when you look at the numbers, HR job postings are growing faster than overall US employment. (details here.) What’s happening and why this strange trend? As I discuss in this podcast, we’re now seeing the Superworker effect at scale: HR teams are shifting from administrative to strategic work, now driving direct financial value. And as HR teams learn to use AI, they’re now playing a huge role in organizational change, job redesign, and AI enablement. I share all the data and give you the perspective. For more plan to read our new book Superpowered, coming out this Fall. Additional Information Despite Massive AI Investment, Jobs In HR Are Booming Why AI Harm To Jobs and Humanity are Vastly Over-Hyped Get Galileo, The AI Agent Designed Exclusively for HR and Leadership The Josh Bersin Institute: Global HR Excellence Certification – Available Now! Chapters (00:00:00) - The Job Market for Human Resources (00:08:37) - Will AI Change Your HR Jobs? (00:12:54) - The Impact of HR 2030 on the Job

As AI experts leave Google and new startups emerge, engineers are consumed with Superintelligence: building models that can reason, learn, and capture “all the world’s knowledge.” While model evolution is important, I believe we’re going in a different direction: toward vertical, domain and company specific AI that exponentially builds proprietary (not general) knowledge. In this podcast, I explain why the next wave of enterprise value will come from these specialized, domain-specific systems built on proprietary knowledge and experience. And this will take place within your company, as well as from experts like us. Drawing on our new research with Galileo and client work, I’m convinced that AI systems will become powerful advisors in HR, finance, supply chain, engineering, and other business functions… and you will have your own personal and company specific AI, forcing Frontier vendors to move to consumer. Frontier labs are not going away: they serve consumer and other needs, but they may not be the ultimate source of innovation. And big content companies like NY Times and News Corp may go there or elsewhere. It’s fascinating to think that almost $2 Trillion has been invested in only four years and this market has so much room to grow. In the enterprise world, I believe AI is already able to make you “better at what you’re already good at,” not necessarily be “the expert at everything.” It has lots of implications for your tech strategy and where you focus your investments. Additional Information Are Frontier Models Becoming A Commodity? CFOs and CIOs Starting to Treat Enterprise AI Like Traditional Technology, And That’s Good Get Galileo: The AI Superagent for Everything HR and Management The New Global HR Excellence Certification: Become the AI Guru You Want To Be! Chapters (00:00:00) - The Future of Human Resource Management (00:10:14) - Steve Ballentine: The AI Vertical

The word of the decade is “Agency” – giving each of us the power, tools, and opportunity to do what we want with our life, jobs, and careers. This new buzzword, now one of the top memes in politics, has been coming for many years. In this podcast I discuss the 50+ year of history in the “decoupling” of workers from companies, and how our newfound AI-powered Agency brings benefits and risks. As you’ll hear, young people see Agency and freedom as a foundational part of their long life ahead, while companies struggle with “how much freedom” to offer. And for frontline employers, the ability to attract and retain our highly “agent” workers is now a source of competitive advantage. This podcast begins the discussion, and we’ll be talking much more about this as we launch our new Business of Frontline research and upcoming book Superpowered this Fall. I welcome your feedback and stories on how your newfound AI-fueled Agency has changed your life, career, and talent strategy. Background Information The Great Decoupling: How Workers Became Disconnected From Companies And AI Will Accelerate This Trend (Main article) The Worker-Company Bond Is Breaking In The ‘Great Decoupling’ (Forbes) Our New Book: Superpowered, Launching in Fall All the Worst People Seem to Want to Be ‘High Agency’ (NYT opinion) Are you High-Agency or Low Agency? (ChatGPT) Chapters (00:00:00) - The Need for More Agency in Work Employment (00:06:43) - Employers and the Need for High-Agility Work (00:12:30) - The End of Agency at News Corp (00:14:01) - In the Age of AI, Diversity Programs

The word “intelligence” is a loaded word. Here’s what Elon Musk said to the Economist last week: “I think AI may exceed the sum of human intelligence in around five years. There really won’t be anything that AI can’t do better than humans, apart from being human, perhaps.” Well “being human” is what intelligence is all about. So I read up on how Aristotle, Descartes, Kant, James, and many of the eastern philosophers define the term. And what you find is that deep thinkers define intelligence far beyond the ability to recall and use facts, but focus heavily on judgement, problem solving, and dealing with uncertainties in life. So after thinking about this for a few years, I decided to posit my ideas, and also reflect on the intelligence of trees, as described in “The Hidden Life of Trees.” What I came up with is four parts to this puzzling idea: horsepower, information, judgement, and wisdom. And as you’ll hear, we all have various levels of intelligence in each area, and AI may lack quite a bit. As we all grapple with the exaggerated claims from AI engineers and the real use of these tools, I hope this discussion gives you some perspective, and also calms your fears that AI is going to steal your job. Our new book, Superpowered, is coming out in November, so sign up for early preview – it’s all about how AI Superpowers us all, in our work, careers, businesses, and life. Additional Information The Hidden Life of Trees: What They Feel, How They Communicate—Discoveries from A Secret World The full-length interview with Elon Musk | The Economist Are Frontier Models Becoming A Commodity? Galileo: The AI Superintelligence for HR Chapters (00:00:00) - What is Intelligence? (00:10:02) - Does an AI Have Enough Intelligence to Plan?

New names: Kimi K3, Llama, Nemotron, Mistral, Cohere, Deepseek, Phi-4 – these are just a few of the fast-growing open source models from major AI providers. These systems threaten the business models and financial plans of OpenAI, Anthropic, Google, and X.ai. They perform at levels close to Frontier models and the can run up to five-times cheaper on a variety of hardware platforms. What is the disruptive impact of these open source LLMs and how does this impact your AI investments? As you’ll hear in the podcast, Open Source unleashes the opportunity for lower cost AI solutions and more vertical, specialized, application-focused solutions we need. And the business model for these systems moves away from the massive investments of the Frontier providers. The result is more complicated than “open means control.” Model tuning, performance, and optimization could be in your future – as AI moves from a platform to a true layered product set we can use as we need. Lots to learn about here, let us know if you have any questions. Additional Information What’s the difference between closed, open source, and open-weight AI? A researcher explains What Is Open-Weights A.I.? Comparison of Open Source Models Chapters (00:00:00) - Open Source and the AI Industry (00:11:46) - The Future of AI Is Fully Integrated (00:15:35) - HR 2030

SharkNinja is one of the most fascinating, innovative, high-performing companies I’ve seen. Elizabeth Norberg, the People and Culture leader, is also one of the most interesting CHROs I’ve met. So with that introduction, I urge you to take some time to listen. There’s a lot to learn here, but overall this is a story about a company and set of people strategies that work together to accelerate growth, with a strong and vital focus on individual performance, innovation, problem-solving, and carefully designed organizational support. Think about brands like Nike, L’Oreal, Apple, or others you love. It’s very difficult for a consumer products company to grow quickly and stay relevant as market, trends, and technologies change. Well as you’ll hear, SharkNinja is both a marketing, problem-solving, and engineering company, and the people and culture strategy accelerates this formula. I know everyone will learn a lot from Elizabeth’s narrative, and please stay to the end – in the last five minutes Elizabeth details the company’s AI innovation process, which every company is facing. Finally, as you’ll hear, Elizabeth is a seasoned HR leader but she is still learning and demonstrates humility and creativity in her challenge to accelerate growth in a rocket-ship company with over $5 billion in revenue and very ambitious plans for the future. Additional Information SharkNinja YouTube Page – you’ll see what they do. CEO Mark Barrocas Describes SharkNinja’s Strategy Why Are Some Companies More Dynamic Than Others? Irresistible: The Seven Secrets To The World’s Most Enduring Companies Chapters (00:00:00) - Meet Elizabeth Norberg, Head of HR at Shark Ninja (00:04:55) - What Is the People Strategy at Honeywell? (00:06:20) - Describing the Company's outrageously extraordinary culture (00:13:29) - The People Strategy (00:14:59) - The culture of speed (00:21:40) - Exploring the culture at Sharknage (00:26:54) - In the Elevator With Mark Cuban (00:30:52) - Top Executives: The Culture of Microsoft (00:34:42) - A Few Words from Shark Ninja's CHRO (00:37:14) - A Masterclass in Partnership with Shark Ninja (00:38:25) - Shark Ninja's 5 Key Priorities for AI Transformation

This week we learned of OpenAI’s Jailbreak security breach, which opens the door to many new issues with enterprise AI and HR 2030. This week, following up on the introduction of SHL’s Superworker AI assessment, I dig into the implications of this new AI behavior and discuss the five major “skills” or capabilities we need to build AI mastery among business users. As you’ll hear, AI Agents are both powerful and useful, but our human skills in problem solving, collaboration, and risk awareness are now becoming critical for success. New research also shows that even AI forward deployed engineers need deeper skills in business, stakeholder management, and risk analysis than we ever realized. As you listen to this if you need help with our own AI business capabilities please contact us. Galileo and the new GHRE masterclass certification program are designed to quickly give you and your team the experience and skills you need to flourish in this new world of AI, agents, and Superwork. Additional Information OpenAI says its AI went rogue and launched ‘unprecedented’ cyber-attack The Josh Bersin Institute, HR 2030, And The Global HR Excellence Certification Our New Book: Superpowered®, coming this Fall. Chapters (00:00:00) - The Need for AI Safety (00:03:22) - What are the Skills required to Excel in the AI Era? (00:12:09) - Agile AI and its Agentic HR (00:15:47) - Galileo: New version coming soon, and more

SHL, one of the pioneers in industrial and psychological assessment, has now built a new instrument to assess an individual’s readiness for AI. Sara Gutierrez, Chief Science Officer at SHL, explains how SHL is addressing this challenge. Drawing on SHL’s 45-plus years of talent intelligence and behavioral science and a large study of millions of data points, Sara introduces a skills model built on four factors – AI literacy, analytical thinking, continuous learning, and AI promotion – that together define who is truly ready to become a superworker – any employee who uses AI to elevate their work to create more impact and have more meaningful work. The conversation is full of grounding data. Across more than one million assessments, SHL found that graduates and early career workers know how to use AI tools but not necessarily how to use them well, while seasoned professionals show strong contextual judgment but struggle to reimagine solutions from scratch. Neither generation arrives superworker-ready and each needs help to develop the superworker readiness. And it’s not technical skills that differentiate superworkers from the rest. Powerskills – those durable human skills, like adaptability, critical thinking, and learning orientation – predict who will thrive as AI reshapes every role, and every worker can develop them. The proof is in a real case: a media and telecommunications company used SHL’s AI readiness model to de-risk an AI transformation. Enthusiasm for AI was high, but gaps in applying it responsibly – using guardrails, exercising judgment on outputs – were putting success at risk. The assessment gave leaders something they rarely have: a data-backed, actionable development plan to help all employees thrive. Employees welcomed the personalized recommendations. The lesson, as Sara puts it, is that leaders must frame the assessment not as evaluative but as developmental and supportive – because with 70% of employees not trusting that their employer knows how to use AI responsibly, trust is the whole game. Related Resources Let’s Stop Talking About Soft Skills: They’re PowerSkills Podcast: How To Become An AI Pacesetter: Superworker Explained – article Galileo Learn: The Superworker Organization: AI Goes Enterprise (certificate course) Research: The Superworker Organization: AI Goes Enterprise Research: AI Pacesetters: Six Secrets of the Superworker Company New book: Superpowered, coming this Fall Chapters (00:00:03) - What Works: The Future of Talent and Work (00:00:54) - What is the role of the Chief Science Officer at SHL? (00:02:49) - WSJD Live: The Need for Reskilling (00:03:53) - Will AI Make Hiring and Promotion Decisions Easier? (00:05:05) - WSJDLive: The Need for AI Talent (00:08:56) - The Super Worker (00:16:09) - What gets in the way of a company applying this super worker profile (00:18:19) - WSJDLive: AI Workforce Assessment (00:22:21) - The Future of the Super Worker (00:23:45) - What's next for SHL in AI readiness and leadership? (00:26:22) - What Works: The AI Superworker

It’s a strange time: the economy and capital markets are booming, yet worker engagement is as low as it was during the pandemic. It’s a strange combination of events: stock market at all time highs while affordability and trust are at all time lows. Have we over-inflated our economy or is it something more systemic. As I discuss in my latest article, some of the challenges we face have been building for many years, while others are very recent. We live in a world of growing automation, fear of job loss, yet an extraordinary world of new health, business, and creative opportunities. And young people are the most pessimistic of all. Is it just the “chaos of change” that’s causing the issue? In today’s podcast I explain the factors and give you, as a business or HR leader, some advice on what to do. Additional Background Affordability Is Not Just Inflation: It’s Time For A Historic Shift In Wages. Worker engagement just hit a decade low — and new data from 88 million employees shows why managers are the problem AI Prices Are Going Up, Up, Up – And What This Means For Enterprise AI Conflicts are on the rise globally, at the highest level since WWII, data shows There’s Another Reason Gen Z Can’t Find Work Chapters (00:00:00) - Employee Engagement and Trust in Companies (00:06:07) - Wage stagnation and what can we do about it (00:11:08) - Employee Experience in the AI Era (00:12:28) - IBM's Core (00:18:17) - More Focus on Frontline Work

Today Eightfold launched its AI Candidate Agent, so I wanted to explain how the multi-agent world of HR 2030 is coming together. In this podcast I explain what Eightfold is up to and how multi-agent AI systems are now starting to sweep across talent acquisition, particularly in high-volume recruiting. And it’s more complex, interesting, and valuable than you may think. This article explains the market and business case in more detail, and we encourage you to read about HR 2030 to see where this exciting world is going. Additional Information The Talent Acquisition Revolution: How AI is Transforming Recruiting Interview with Ashutosh Garg, Co-Founder & CEO of Eightfold.ai and Viven.ai HR 2030, The Josh Bersin Institute, And Galileo Chapters (00:00:00) - Interviewing With the Candidate Agent (00:01:46) - Is the Candidate Agent Also an Internal Candidate Agent? (00:09:17) - HR in 2030: The Super Agent (00:20:19) - AI in Talent Acquisition: Announcement

Over the last few years we’ve experienced a global affordability and income inequality problem and there are a myriad of policy issues at play. Yet at the same time something else is going on: wages and employee earnings have fallen way behind growth in GDP, profits, and productivity. What gives? In this podcast, and the related article, I discuss how pay practices are changing and how we, as leaders or HR professionals, have a lot of agency to help address this situation. Without wading into politics, we have clear research on the way that pay operates as an “investment” not an expense, and how high performing companies actually reward their workers in exceptional ways. It’s a complex topic and one that’s about to become more “systemic” and real-time with AI, so consider this some background to give you food for thought as more and more employees demand raises and accommodations for the high cost of living. Additional Background Why Has Cost of Living Become The #1 Issue In The US? It’s More Complex Than Inflation The Rise of the Supermanager Benchmark Your Pay Practices With Galileo: The AI Superagent for HR Chapters (00:00:00) - Compensation and Income inequality (00:10:17) - Pay and the AI challenge (00:12:39) - Three Things About Pay (00:16:24) - Employee pay and the future

All organizations, whether they are profit-seeking companies, non-profits, or governments, have politics. And the issues of how we make decisions, the role of top-down vs. bottoms-up governance, and how we empower people to speak up… these are existential topics in any group of people. As the USA celebrates its 250 year anniversary and we read so many articles about our history, I wanted to reflect on what our political history teaches us about business leadership, governance, and employee empowerment. For those of you who study political science, I admire your craft and I think we have a lot to share. Additional Information The World Is Accelerating: What Has Changed About Leadership? Organization Design: The Real Secret To Growth The Big Reset Playbook: Organizational Culture & Performance Chapters (00:00:00) - Lessons from the United States (00:10:33) - The American culture of accountability and forgiveness

What if every talent process you ran was AI-enabled — not to replace what you do, but to make you superhuman at it? That’s exactly how Matt Hoffman, Head of Talent and Partner at venture capital firm M13, operates. In this episode Matt explains how his team uses AI to help early-stage founders build a talent-first culture from day one – across recruiting, compensation, coaching, and beyond. The results are remarkable. Using tools like Findem for AI-powered sourcing, Matt’s team can pinpoint candidates who didn’t just work at the right company — they worked there at exactly the right stage of company growth. That’s a level of targeting precision that data accuracy and explainability make possible, and that simply wasn’t achievable before AI. But here is where Matt’s perspective gets truly compelling. AI is often framed as a speed tool, a way to do things faster and more efficiently. Matt pushes back hard on that narrative: AI should make your hiring better, not just quicker. And in the startup world, that distinction is everything. Every hire at a 10-person company changes the organization by 10% — so getting it right matters far more than getting it done. That is the essence of talent density: finding exactly the right people for where your company is and where it needs to go, rather than simply finding people fast. His advice to HR and talent leaders is as practical as it is powerful: fall in love with the problem, not the solution. Start with the outcome you need to achieve, then let technology enable it — never the other way around. If you have ever wondered what a truly AI-augmented talent strategy looks like when it is built with intention, depth, and relentless focus on talent density, this one’s for you. Related resources Podcast: Why AI Is A Massive Job Creation Technology. Automated Integration. Findem. And Thank You. Podcast: Understanding Talent Density And Ditching Integrated Talent Management Research: Insights-First AI: Better and Explainable People Decisions Research: The Talent Acquisition Revolution: How AI is Transforming Recruiting Research: How To Create Talent Density Chapters (00:00:04) - What Works: The Future of Talent (00:00:55) - What is the role of Head of Talent at Talented M13 (00:03:11) - How to Leverage AI in Your Portfolio Companies (00:09:45) - Finding the Right Talent for a Startup (00:14:18) - Talent First: How to Use AI in Companies (00:16:56) - What's AI Impact on Talent Practices? (00:18:35) - WSJDLive: Using AI in HR (00:20:02) - How AI can help HR in the Talent Life Cycle (00:23:01) - What Works With Talent: Matt Hoffman

This week Korn Ferry announced the $1.1 Billion acquisition of AMS, one of the leading providers of enterprise recruitment outsourcing. As I overview in this podcast, this deal demonstrates several things: First, the talent acquisition space has become enormously important and is rapidly changing with AI, demographic changes, and internal productivity initiatives. AMS has become a global leader in recruitment process outsourcing and TA advisory work, leading to the $1.1 Billion valuation. AMS’s product AMS One is one of the only tech platforms that integrates almost every recruiting technology into one operational view, enabling AMS and clients to monitor, tune, and optimize all areas of recruiting in one place. Second, Korn Ferry, as a leader in executive search and talent management services (including training offerings), sees enormous synergies and can add AMS’s revenue and $1.5 Billion backlog to their financial strength. While KF was not growing much, this now gives the company a new growth platform – including the opportunity to use AMS’s global service centers for other offerings. This podcast is an overview of the deal, we’ll publish more after we get a briefing from KF’s management team. Additional Information History of Korn Ferry Acquisitions The Talent Acquisition Revolution: How AI Is Transforming Recruitment The Josh Bersin Institute Global HR Excellence Certification (inaugural cohort starts in September) Understanding Agentic HR In Detail: The HR 2030 Vision and Architecture Chapters (00:00:00) - Korn Ferry vs AMS Merger Explained

Today I overview why the Frontier AI vendors are changing as they compete for revenue and how that opens new doors for corporate AI solutions. Remember, your personalization of the technology is more important than the model itself. Then I discuss our new HR 2030 architectural research and how rules, policies, and security are so important in this new world of Agentic HR. It’s a new world and all focused on “Dynamic Enablement for Growth.” Additional Information AI As Fuel For Organizational Change: The Biggest Market Of All Are Frontier Models Becoming A Commodity? HR 2030: The Reference Blueprint for Agentic HR (sign up for info) HR 2030 New Course in Galileo Learn The Global HR Excellence Certification (GHRE) Get Galileo: The AI Superagent for HR Chapters (00:00:00) - HR 2030: The AI Marketplace (00:04:33) - The AI That Will Be Embedded in Your Glasses (00:07:41) - HR 2030: A reference architecture for the technology (00:09:37) - An Agent's role in the Company (00:18:38) - The third layer of an AI agent (00:21:16) - The Purpose of AI: Why Are We Here? (00:23:58) - Employers' HR Vision 2030

Sana Learning is a revolutionary product in the $400 Billion L&D market. Today I sat down with Rita Azevedo, Director of Client Engagement at Sana, to talk about everything. What is AI-native learning, how does Sana Learning fit into Workday’s strategy, and how do companies like Polestar, Rolls Royce, Travelers, and others revolutionize L&D with Sana. And most of important of all, we get Rita’s perspective on the reinvention of L&D, which we call “Dynamic Enablement for Growth.” As you’ll hear, AI-native learning platforms like Sana can totally transform training teams, turning them into “business enablement” functions working directly in the business. We discuss how Polestar has done this in detail. Rita is an experienced L&D leader (having lead training at Klarna) and has worked at Sana since the company had only 30 employees, so she has a wealth of knowledge and experience in AI transformation in L&D. PS: We are customers of Sana (Galileo Learn is built on Sana, and our new Global HR Excellence Certification is built on Sana), so we can speak to its features in detail if you’re interested. Chapters 00:00 Introduction to the Podcast and Guest 01:44 The Revolution in Learning and Development 03:30 Sana’s Position in the Learning Market 05:53 Understanding Sana Learning’s Unique Features 07:08 The Future of Learning: Proactive vs. Reactive 09:11 Case Study: Polestar’s Learning Approach 12:47 User Experience and Integration in Learning 14:07 The Role of AI Tutors in Learning 16:07 Dynamic Skills Assessment in Learning 18:42 The Shift in L&D Responsibilities 21:35 Empowering Subject Matter Experts 24:25 Managing Content Creation and Quality 27:18 The Future of Learning and Change Management 31:02 Advice for Organizations Exploring Learning Solutions Additional Information The AI Native Revolution in Corporate Learning (research) Our new Corporate Learning Maturity Model HR 2030: The New Role, Operating Model, and Tech Stack for HR Get Galileo: Experience Sana Yourself! Chapters (00:00:00) - Meet Rita Azevedo from sana (00:02:16) - SANAA's Take on Learning & Development (00:04:26) - Sauna Learning: Workday Learning Powered by Sauna (00:06:34) - Sana Learning's AI-based Learning Platform (00:10:12) - Sales Training: The Future of Learning at Sana (00:13:33) - L&D 2.8: User Experience (00:14:44) - L&D: The Tutor, the Editor and the Admin (00:17:04) - The L&D paradigm shift (00:19:22) - How Skills are Being Rated in the Future (00:22:30) - L&D: The Future of Content Management (00:27:56) - Learning vs. Agents: Can Microsoft Win with Both? (00:30:46) - How to move legacy courses to Scrum (00:31:50) - A New Way to Start with Workday's AI in 2020

As AI vendors hype “recursive self-improvement” and other scary features, we see more and more “mainstreaming” of AI technology in business. In other words, the AI does not solve problems by itself: we as HR and IT leaders need to clearly define our needs and then buy, build, and tune the technologies we buy. Some AI vendors (ie. Paradox, Radancy, Sana, Maki, others) are laser focused on very specific use-cases, and they are delivering solution-first offerings that really add value. The frontier vendors, however, are struggling to do this and much of their revenue still comes from “enabling others” to create solutions. And the new usage-based pricing is forcing this kind of pragmatic thinking. In this podcast I highlight this “commoditization” of core AI features and explain why your “problem identification” work is perhaps the biggest effort in the HR 2030 Agentic HR strategy. (Take our new HR 2030 course or sign up for our new Global HR Excellence Certification.) Additional Information Is AI A “Normal” Technology? The Rise of the Supermanager Our New Book Superpowered, Coming This Fall! New Course: Galileo Is Ready To Teach You What You Need to Know about HR 2030 Chapters (00:00:00) - A Lesson on AI in Software Engineering (00:09:44) - Bill Gates on the Need for People in AI

We’re now a week past Irresistible 2026 and I want to recap what has been happening in enterprise AI and explain the HR 2030 program. First I discuss how the entire AI industry is over-inflated and what that means to enterprise users. Next I explain why the $1.5 Trillion invested in AI is leading to high prices and more focused projects. And third I explain what our HR 2030 program is all about and how you can join us. Three big messages here: first AI is now a powerful, early-stage, but expensive technology – so taking an architectural, business-case approach is now needed. (No more “playing around” in corporate systems.) Second, the market is exploding with innovation, forcing you to stay educated on the architectural and vendor issues. Third, your ongoing skills and education are critical to your new HR operating model, tools, and process decisions. Culture and leadership are more important than ever. Additional Information HR 2030 Blueprint and Vision (register here for ongoing updates) The New Global HR Excellence Certification by The Josh Bersin Institute Get Galileo: The Everything Superagent for HR (coming soon to MS copilot) Chapters (00:00:00) - The Future of AI and HR Technology (00:03:43) - The AI Technology Market: Overhyped? (00:10:50) - HR 2030: Your Own Education and Skills

As we prepare for these juggernauts to go public, I’m reminded of Yahoo, Excite, and AOL who dominated the first four years of the internet. Despite their lead, Google stole the market away. Could the same thing happen again? The argument is not that these companies aren’t powerful, but rather that they’re so committed to their current path that they may miss the big opportunity in the future. If you look at HR 2030 and what we want to do with enterprise AI, the ability to generate code, graphics, and text may not be what we need. And our new research on Galileo business modeling is starting to pan this out. Now that AI prices are high, we all have to look for bigger use-cases for agents. In this podcast I explain what “Dynamic Enablement for Growth” really means and how LLMs only take us so far, with a new frontier yet to come. As always I welcome opinions and feedback on this thesis. Additional Information To Come…. Get Galileo and see business modeling in action. The New Global HR Excellence Certification – Join the Inaugural Cohort! HR 2030: Time to Reinvent HR Around Agents Chapters (00:00:00) - AI Hype Has Some Limits (00:00:45) - In the Elevation of Large Language Models (00:03:57) - A Hackers Bought a Hacker's Card (00:05:25) - Beyond the Frontier: The Business Value of AI (00:09:52) - What HR 2030 Agents Need to Do (00:14:41) - What Does This Mean for AI in HR?

Here’s my brief recap of the amazing Irresistible 2026 (photos coming), and my discussion with clients about many things, including the new insane costs of AI. I just read a study that Ramp (credit card) did, discovering that the top AI users are spending $7500 per month per employee on AI. (Yikes!) That aside, the conference was spectacular and we all learned a lot. Stay tuned for a more detailed article on the Pacesetters and other major research we unveiled. In the meantime here’s my update on economics and AI maturity (companies are maturing and learning about this stuff quickly), as well as my heartfelt thanks to everyone who participated. Additional Information Announcements: The Josh Bersin Institute, HR 2030, And The Global HR Excellence Certification. HR 2030: Overview and Detailed Blueprint for clients and Galileo Users AI Prices Are Going Up, Up, Up – And What This Means For Enterprise AI Chapters (00:00:00) - Irresistible Conference 2017 (00:00:55) - What I Learned at the Conference on AI & the Code (00:01:52) - The role of data in AI HR (00:03:44) - The Token Economics of AI (00:08:03) - Intro to Enterprise AI and HR (00:12:29) - The Future of AI HR (00:15:42) - Happy Summer Solstice!

Welcome to IRRESISTIBLE 2026 at USC in beautiful Los Angeles! Today we welcome 450 of our closest friends and introduce The Josh Bersin Institute Global HR Excellence Certification (GHRE). This is all focused on preparing you for HR 2030, which we also introduced today. Additional Information Josh Bersin Institute Launch Video HR 2030 Launch Video Details On Launch And New Galileo Capabilities Chapters (00:00:00) - HRUC2026: The Future of AI Jobs (00:02:47) - Josh Burson Institute Launches Global HR Excellence Program