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Today I summarize my keynote from Unleash Paris this week, where I draw a line between generative AI’s birth in November of 2022 and the Railroad Era of 1873. Not only are the parallels uncannily similar, it points out that AI’s takeover of our economy has impacted employment, politics, and our teetering stock and bond market. I recommend you read two books after you listen to this. The first is 1873: The First Great Recession, which describes the global financial disaster brought on by the railroad boom. The second is our new book Superpowered: How AI Unlocks The Power of People, Leadership, and Teams. These two books will teach you what is likely to happen in our confusing new AI era, and how you should proceed. I also describe why the economics of AI are about to change, how NVIDIA has become a monopolist, and why there is no such thing as an “AI transformation,” rather a “Business transformation.” And I explain HR 2030 and how to think about your AI architecture before you rush out and buy dozens of new agents. Finally I also explain the four big use-cases for AI in HR, so you can stay focused in your investments. PS: Galileo is now available integrated with Workday, HiBob, Ema, Microsoft Copilot, Gloat, and ServiceNow. New executive compensation benchmarking data from Equilar is now added! Additional Reading Material Time to re-frame HR as an integrated OS? Josh Bersin makes his case Workday and Josh Bersin Company Partner on HR 2030 Education and Research Despite Massive AI Investments, HR Jobs Are Booming. Why? Introducing The Leader’s Guide To Multi-Agent AI Architecture Galileo Jupiter Release goes Enterprise Chapters (00:00:00) - Back from Europe: Unleashed Conference Recap(00:00:49) - The AI Buildout Boom and the Railroad Parallel(00:03:19) - AI Costs, Nvidia's Dominance, and Market Growth(00:04:44) - Inflation, Energy Crisis, and Worker Unrest(00:05:57) - Wage Stagnation, Labor Share, and Employee Engagement(00:07:55) - HR's Confusion and Vendor Landscape (Workday, SAP, Oracle, etc.)(00:09:24) - Wall Street Pressure and Buying AI the Right Way(00:10:05) - AI as Growth Driver, Not Cost Cutter(00:10:24) - Productivity Needs and GDP Growth Math(00:11:49) - Building AI as an Enterprise Architecture(00:12:42) - Build vs Buy and Managing AI Agents(00:14:08) - Big Vendors' Advantage and Data Ownership(00:15:09) - Framing AI as Business Projects, Not Tech Projects(00:15:51) - The J Curve and Vendor Market Shakeout(00:17:00) - HR 2030 Resources and European Riots Context(00:17:54) - Frontier Vendor Hype vs Market Reality(00:19:02) - Four High-ROI HR AI Project Areas(00:20:06) - Learning, L&D, and Galileo Learn(00:21:06) - Redesigning HR Business Partner Roles(00:22:12) - Other Opportunities: Onboarding, Payroll, Compensation(00:23:22) - Skepticism Toward AI Hype Figures(00:24:31) - Data Center Overbuild and Economic Outlook(00:24:58) - Superpowered Vision: Wages, Growth, and HR 2030(00:25:51) - Europe's Pragmatic AI Approach and Closing Thoughts

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