Jacob Morgan

We tried to make work happier—and ended up making it hollow. Cultures softened. Leaders hesitated. Performance drifted. After 100+ CHRO interviews, I wrote The 8 Laws of Employee Experience—a blueprint to bring strength and humanity back to work. Learn more about it here: linkedin.com/pulse/my-new-bo…

One of the things I wanted to create with Future of Work Leaders was a place where CHROs and CPOs could have the conversations they usually don’t get to have anywhere else. Most senior people leaders already have plenty of conferences, vendor events, and content coming at them. What’s harder to find is a trusted peer group where the conversation is candid, the people in the room are operating at the same level, and nobody is trying to sell you something, and that's what this community is built around. We now have 40+ CHROs and CPOs learning from each other about the issues shaping the people profession, from AI and workforce transformation to leadership, employee experience, skills, culture, and what the organization of the future is going to require.The real value is having a room full of peers who understand the complexity of the job, can challenge your thinking, share what is actually working, and help you see beyond the walls of your own organization so you can make better decisions about what comes next. Eric Hunn said it best when he described the group as “the place to be to stay on the leading edge of the people profession,” with the real value coming from the focus on the future of HR and the chance to learn directly from other CHROs. That is exactly the kind of community I set out to build. If you are a CHRO or CPO and you want to be part of a serious, future-focused peer group, you can request to join at FutureofWorkLeaders.com

Employee engagement in the U.S. has fallen to its lowest level in 15 years, with just 29% of employees engaged. I don’t think the answer is another perk or program. A bigger issue is whether employees actually understand what is happening around them, what is expected of them, and what all of the change means for their role. In this week’s briefing, I look at why clarity may be one of the most important drivers of engagement right now, along with Microsoft’s voluntary exit offer and the growing question of whether employees should be able to opt out of AI at work. greatleadership.substack.com…

Every company should expect a wave of employees who believe they’re managers. It’s not that they are gaming the system, they’ll sincerely think the title fits, because everything around them suggests it does and that’s the problem. The belief will spread much faster than the work justifies it. Why will this happen? I think as a result of four forces. The work feels like management. Reviewing output, catching errors, deciding what’s good enough: these are things managers do, and AI users now do them all day. In Microsoft’s 2026 Work Trend Index, a May survey of 20,000 AI users, the top-rated human skills were quality control of AI output (50%) and critical thinking (46%), and 86% said they stay responsible for the thinking behind AI’s output. At Anthrpic, one in five employees already describes their job as managing agents. But checking an agent’s work isn’t the same as owning an outcome. Approving every output puts you closer to a user than a leader. It feels like management it still doesn’t pass the test. The organization is telling them so. Agents have employee numbers, logins, profiles, named owners, and performance reviews. In many companies the agents have human names and leaders encourage employees to view agents as co-workers. So when the company treats agents like staff, the person whose name sits next to an agent will naturally see themselves as its boss, which makes sense and it’s why we shouldn’t anthropomorphize agents. Someone can own ten form-filling agents and still be an automation operator. They have leverage that used to require a team. Anthropic reports code commits per engineer running at five times the pace of six months earlier, with lawyers, sales reps, and accounts payable teams also processing more work. The company generates two to four times the revenue per employee that Google and Meta did. Historically, leverage and management came together. If you produced a team’s worth of output, you had a team. Agents break that connection because output can now scale without judgment, coordination, or accountability scaling with it, and those three are what management consists of. Traditional management is less appealing. Gallup reports the average US manager now has 12.1 direct reports, nearly 50% more than in 2013. Agent leadership looks like scope, impact, and ownership without the hardest parts of managing people. That makes it the most attractive “management” job at your company and with the cool title! Each of these points employees toward the same conclusion: I’m a manager now. Without a shared definition, organizations will end up in one of two bad places. They’ll either reward agent counts and drift into agent inflation, or they’ll dismiss every claim and lose the people who really are leading agents. It’s going to be very important to have clarity here. Read the full article: greatleadership.substack.com…

The org chart we’ve used for decades is starting to describe less and less of how work actually gets done. Traditionally, the structure was pretty straightforward. A large base of employees did the work, managers coordinated people in the middle, and leaders made the big decisions at the top. AI agents start changing that shape. BNY is already preparing for a workforce that looks less like a pyramid and more like a diamond. Repetitive processing at the bottom increasingly shifts to digital employees, while analytical, creative, and judgment-heavy work expands in the middle. Leadership still sits at the top making the biggest calls. I think that widening middle is where some of the most important work of the next decade will happen. We’re going to have people who don’t manage large teams, and in some cases don’t manage any people at all, but they’ll be directing agents, coordinating complex workflows, exercising judgment, handling exceptions, and owning consequential outcomes. That work may be invisible on a traditional org chart. It’s also why I think span of control will increasingly become span of accountability. Instead of asking how many people report to someone, leaders will need to look at the people, agent systems, decisions, and outcomes that person is actually responsible for. This isn’t theoretical. In BCG’s 2026 AI at Work study, 47% of respondents said they already spend more time managing and directing AI than doing the work itself. Anthropic employees are writing instructions for agents, reviewing their output, and even creating performance reviews for their teams of Claudes. I go much deeper into this, including my Agent Management Test, Agent Leadership Ladder, future scenarios, and what leaders should start deciding now, in my latest article. Your Best New Managers Have No Direct Reports. Read the full article: greatleadership.substack.com…

We expect leaders to question assumptions, challenge recommendations, and take responsibility for decisions. I wonder how consistently we’re applying those expectations when the recommendation comes from AI. Charter’s AI Pulse research found that executives are about twice as likely as individual contributors to trust AI over their own judgment. About one in five executives regularly or frequently use AI outputs they have doubts about. The report also found that executives fact-check more often than workers, which makes this worth a closer look. Checking whether an answer is factually correct still leaves plenty of room to question whether it’s the right recommendation for your organization. An AI recommendation can miss the history behind a team’s resistance, a promise made to a customer, or the consequences of a decision for people who never entered the prompt. Leaders are responsible for bringing that context into the conversation, especially when an answer sounds convincing and everyone is under pressure to move quickly. As organizations invest in AI training, there should be more attention paid to how executives evaluate its advice. Ask them to explain where they disagree, what information is missing, and why they’re comfortable acting on the recommendation. Their answers will tell you much more about their readiness than how many tools they use.

Waiting is the riskiest career move you can make. I talk to people who are waiting for their manager to tell them what to learn, which tools to try, or what their next role should be. Your employer should invest in your development. You also need to take an active role in deciding where you’re headed. The employees who are preparing themselves for the future bring ideas forward, try things without being asked, and put what they learn into practice. They’re also willing to let go of approaches that have served them well when the work calls for something different. Adaptability, learning agility, and accountability are available to anyone, regardless of title or technical background. With AI, we need to look further ahead. We’re spending a lot of time figuring out how to do today’s work faster, and I’d like to see more people asking what their role might look like in two years. Which responsibilities could disappear? Where will people need more of your judgment, experience, or ability to build relationships? Those questions should influence what you spend time learning today. You don’t need to predict exactly what’s coming to start preparing. Bring an idea to your manager. Try a tool on a real problem. Take on something that stretches you. Give yourself a chance to discover what you’re capable of before a change forces the conversation.

When a company treats agents like staff, the person whose name sits next to an agent will naturally see themselves as its boss, which makes complete sense and it’s also why we shouldn’t anthropomorphize agents. Orgs who treat agents like people are in for a world of hurt.

The best ideas get better when you can pressure-test them with peers who are facing the same challenges. Alicia Zuiker, CPO at TransUnion, described the value of Future of Work Leaders as being able to test ideas alongside other CHROs, stay ahead of emerging trends, challenge her thinking, and lead with greater confidence. Future of Work Leaders is a private, vendor-free community of 40+ CHROs and CPOs who come together to have candid conversations about AI, leadership, talent, employee experience, and the future of work. If you’re a CHRO or CPO looking for a trusted peer group where you can learn, share, and think through what’s coming next, request an invite at FutureOfWorkLeaders.com.

Great managers know more than what someone does, they understand who that person is. It sounds simple, but a lot of management still happens at the surface level. We know someone’s title, responsibilities, performance goals, and maybe a few things from their last review, but it doesn’t tell us much about what actually motivates them, where they want to go, what they’re dealing with outside of work, or where their strengths really are. That’s where the PACT framework comes in. P is for Personal. What matters to this person? What are their values and motivations? A is for Aspirations. Where do they want to go? What are they trying to become or accomplish? C is for Circumstances. What is shaping their life right now? What context are they bringing to work? T is for Talents. What do they do especially well, and are we actually giving them opportunities to use those strengths? You don’t need another survey or complicated system to start doing this. You need better conversations. The more you understand the person behind the role, the better you can lead them, develop them, and create an employee experience that actually fits who they are. I explore the PACT framework and much more in The 8 Laws of Employee Experience. You can get a copy on Amazon at 8EXLAWS.COM.

If entry-level work starts disappearing, where do future leaders get the experience they need? Anthropic’s workforce data shows junior hiring falling while more employees shift toward higher-level, AI-supervisory work. The productivity gains are real, but so is the pipeline problem. I explore what this means for hiring, development, and succession in my latest article, Where Do Future Leaders Come From? linkedin.com/pulse/where-do-…

CHROs are CEOs of people. They must keep employees engaged while also showing value in doing so. These two things must always be connected together. From the research I conducted for my book, The 8 Laws of Employee Experience, I believe that many organizations are doing things because they look good, not because those things do good. Leaders are trapped in tactical execution in terms of filling roles, addressing turnover, and more traditional aspects of HR; they have little room for bold moves or strategic foresight. It’s hard for leaders to think several years into the future when their time and attention is focused on the next quarter. Although a few CHROs spoke about innovative programs, most are focused on keeping up, not getting ahead. Almost all of the CHROs told me that they are going to focus more on the future of work and employee experience in the coming years. They want to create better employee experiences. They want to shift from reactive firefighting to proactive, strategic leadership. The desire for change is there, but will the system allow it?

If AI saves your employees hours but customers still wait just as long, where did the value go? Often, it’s stuck between teams. Someone finishes a task faster, then the work sits in an approval queue or waits for another department to pick it up. Everyone can report better productivity while the overall process barely improves. Fixing that requires decisions about who owns the work, which steps can disappear, and how you’ll measure progress. It also requires an answer to a question that gets overlooked: what will you do with the capacity you free up? Serving customers you previously couldn’t reach or testing ideas you couldn’t afford to explore gives those saved hours a purpose. In my newsletter, I break down how to redesign work around AI, including these four common traps and a practical hiring example. Read the full article at FutureOfWorkNewsletter.com.

CHROs spend their days helping everyone else think through difficult decisions. They need a place to challenge their own thinking, too. That’s why I built Future of Work Leaders, a community of 40+ CHROs and CPOs who come together to discuss how work is changing and what it means for their organizations. Katie Watson, CHRO at WD, put it well: “I always walk away with something I can use.” That’s what I want every member to leave with: a fresh perspective, a better question, or an idea they can put into practice. If you’re a CHRO or CPO looking for these conversations, request to join: futureofworkleaders.com

Everyone keeps asking what we’ll do when AI takes all the work. That's the wrong question. I believe AI is going to have us working MORE, not less. Here’s why... In 1865, an English economist named William Stanley Jevons noticed something that seemed backwards. Steam engines were getting far more efficient with coal. Logic said Britain would burn less of it. Instead, coal use exploded, because cheap power made thousands of new uses worth pursuing. That became known as the Jevons Paradox: make something more efficient, and you often get more of it, not less. It’s happening right now with work. Anthropic recently published a report on how AI has changed work inside its own company: → The AI agents employees direct now log six times the hours of the people directing them → Code commits per engineer are up fivefold in six months → The median employee spends 20% more time in meetings than a year ago → Every time a better model comes out, people immediately hand it harder problems Nobody went home early. They went after bigger things. I see the same thing in my own business. AI hasn’t given me more free time. It’s given me more ideas I can actually act on: things I want to try, ways I want to grow the company, projects that used to sit on a “someday” list because they were too expensive or too slow to attempt. That’s what the “we’ll all be on a beach” crowd keeps missing. AI doesn’t shrink the pile of work. It makes the pile taller. Jensen Huang put it bluntly when asked about companies cutting jobs in the name of AI: “You’re out of imagination. For companies with imagination, you will do more with more.” The constraint on work is no longer time or cost. It’s imagination. But “more” doesn’t have to mean more grinding. It means more ambition per person. The salesperson who managed 50 accounts manages 80. The team that shipped one product a year ships four. The ideas that died in a backlog finally get tested. And there’s an important nuance. Across the industrial era, Americans went from roughly 3,000 working hours a year to about 1,800. Productivity eventually bought us weekends. That didn’t happen on its own. People chose it. The same choice is in front of us now. There will be plenty of work. The question is whether we turn AI’s gains into more output, more time back, or both. Three questions worth asking yourself and your team this week: What’s one idea we shelved because it was “too expensive” that AI now makes possible? What are we doing faster that we shouldn’t be doing at all? Are we measuring people by how busy they look, or by what they create? Because AI will happily keep adding to the pile. Deciding what’s worth doing is still our job. As Peter Drucker put it, “There is nothing so useless as doing efficiently that which should not be done at all.” Are you working more or less since you started using AI? #FutureOfWork #AI #Leadership #Management #HR #HumanResources #CHRO

I think a lot of people still approach their career like someone else is going to tell them what comes next. Do good work, wait for the promotion, wait for your manager to have the career conversation, wait for a new role to open up. That might have worked when careers moved in a more predictable way. I don’t think it works as well anymore. Jobs are changing too quickly. AI is reshaping roles, companies are redesigning work, and the skills that got you into your current role may not be the same ones that get you into your next one. So I think you have to be much more intentional about building what comes next while you’re still doing the job you have now. Learn something new. Try the tools. Pay attention to how your role is changing. Talk to people doing work you might want to move into. Your company can help. Your manager can support you. But ultimately, nobody is going to care about your career as much as you do. Don’t just manage your job. Build your next.

Your employees can be perfectly happy at work and still be planning their exit. Thats something every CHRO and CEO should be paying attention to. According to ISACAs 2026 research on technology professionals: - 76% are satisfied with their current jobs. - 71% are satisfied with their careers. - Yet 65% would consider leaving within the next two years. Think about what that means for how organizations measure employee experience. Weve spent decades investing in engagement surveys, satisfaction scores, and employee feedback. But how much do these metrics actually tell us about whether someone will stay? An employee can enjoy their job, respect their manager, and feel fairly compensated while still believing their best career opportunities exist somewhere else, and I think that’s the blind spot of many organizations.Were good at measuring how employees feel about their jobs today. Were much less effective at understanding how they see their future with us. Career growth, meaningful work, leadership quality, and opportunities to develop new skills all play a role in that equation. The question is whether your employee experience strategies are doing enough to address those longer-term expectations. If 76% of your employees were satisfied, but 65% were open to leaving, would you consider your employee experience strategy successful? Source: ISACA, 2026 Workforce Research

There’s an important distinction showing up in the AI jobs data. Research from Stanford’s Erik Brynjolfsson and others suggests that when AI directly replaces the work junior employees used to do, entry-level employment falls. But when AI is used to assist workers instead of replace them, entry-level employment has held up better and in some cases even grown. I think that matters because “human + AI” can sound like a nice slogan. But we’re starting to see evidence that the way companies deploy AI actually changes the labor outcome. If you use AI to eliminate the work people used to learn from, you may shrink the pipeline. If you use it to make people more capable, you can create a very different result.

make it insightful, not just enumerate We’re entering the phase of AI where the interesting questions are less about access and more about consequences. What happens when AI becomes expensive enough that companies start rationing it? When polished interview answers become easier to manufacture, so employers have to find better ways to see how people actually think? When advanced models uncover more problems than organizations have people available to fix? That’s the thread running through this week’s Future Ready Leadership Weekly Briefing. AI is not simply removing work. It is reshaping where the work, cost, judgment, and accountability sit. Read the full briefing: greatleadership.substack.com…

I think we put way too much pressure on young people to know what they want to do before they’ve actually experienced much of the working world. One teenager I talked about recently wanted experience at a ramen shop in New York, so he went out and put up hundreds of flyers trying to create the opportunity for himself. The point wasn’t that he had already decided this would be his career. The point was to explore, get curious, and learn by actually doing something. We need much more of this. Let young people try blue-collar work, white-collar work, creative work, technical work. Let them shadow people, apprentice, build things, and figure out what they enjoy and what they’re good at. One experience doesn’t have to determine your career. Sometimes its value is simply helping you figure out what you want to try next.

AI is supposed to reduce headcount, but sometimes it does the opposite. Bank of America reportedly brought in around 1,000 contractors to help patch issues uncovered with advanced AI tools, working alongside thousands of existing employees. The technology made finding problems dramatically faster and cheaper. But finding a problem and actually fixing it are two very different things. Someone still has to understand what matters, decide what should be prioritized, make the changes, test them, and deal with whatever breaks next. I think this is an important part of the AI jobs conversation that gets overlooked. When technology makes one activity much cheaper, we often end up doing a lot more of it, which can create more work somewhere else in the system. AI may automate tasks, but that doesn’t automatically mean fewer jobs.