The Josh Bersin Company

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

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

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

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.

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

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

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

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!