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…

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.

Leaders need to learn when not to react. Not every trend deserves immediate change or action. It’s up to you and your leadership team to decide if a particular trend requires immediate change or careful observation, or if it’s something you can resist and ignore. Being able to say no to things is a leadership skill. Don’t be scared to push back. When you’re examining the trends mentioned earlier in the chapter or are looking at others, assess each one using these three responses: • Adapt - This trend is real and aligned with our values. We need to respond now. • Pause - This trend is emerging. We’ll monitor it but won’t act yet. • Push back - This trend doesn’t align with our strategy or values, so we’re opting out. I worked with a company recently that was considering using AI resume screeners for all new candidates. The leaders asked me my opinion of these tools, and we went through a very quick exercise to determine if they should adapt to the trend, observe it, or push back against it. Ultimately, the leaders decided to push back on this trend as they realized there were too many legal and ethical issues with AI resume screeners, especially since the way the screeners operate is still a bit of a black box. They decided that a human-led resume review was more aligned with their values. A future-ready organization isn’t shaped by chasing trends. Yes, it’s important to know what the trends are, but ultimately the real competitive advantage here is discernment. You need to take a step back and keep asking yourself “Does this make sense for us?” In a world full of change, the ability to reflect instead of just react is going to set your organization apart

Three very different companies. Three very different industries. But the CHROs and CPOs leading them are wrestling with many of the same questions around AI, culture, leadership, talent, and how work is changing. That’s the value of Future of Work Leaders. It gives senior people leaders a private place to compare what they’re seeing, learn from peers outside their own industry, and have the conversations that are difficult to have anywhere else. Leaders from LEGO, PwC, Patagonia, and 30+ other organizations are already part of the community. If you’re a CHRO or CPO looking for thoughtful, peer-to-peer conversations without vendors, pitches, or fluff, you can request an invite at FutureOfWorkLeaders.com.

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We’ve spent years telling leaders they need to be more vulnerable. I agree, but vulnerability by itself isn’t enough. If people only see vulnerability, eventually they may start questioning whether you’re actually capable of doing the job. Go too far in the other direction and focus only on competence, and you can come across like a robot. People may respect what you can do without feeling any real connection to you. The sweet spot is having both. Your people need to see that you’re human, that you struggle, make mistakes, and don’t always have the answer. They also need confidence that you can make decisions, perform, and help move them forward. Great leadership requires vulnerability and competence at the same time.

So worried about AI taking over the world, meanwhile an employee dropped a nanny cam in a conference room. Was it inside of a teddy bear and placed on a mantel by any chance?

AI agents are supposed to make work easier, but for some employees they are becoming another thing to manage. This week’s Future Ready Leadership Weekly Briefing looks at what happens when AI creates more supervision, Anthropic starts setting boundaries around how people interact with Claude, and a $20 billion revenue gap shows how easy it is for AI metrics to be misunderstood. The bigger issue is not just what AI can do. It is how companies design jobs, measure value, and set expectations as these systems become part of everyday work. Read the full briefing at Future of Work Newsletter greatleadership.substack.com…

AI is already summarizing feedback and drafting performance reviews for managers. The harder question is how much say it should get in who gets promoted, paid more, or let go. Used well, it helps. A manager gets a synthesis of a full year of feedback instead of the last three weeks they happen to remember. Documentation actually gets done. But a tool that routes meeting invites and a tool that shapes a termination decision shouldnt have the same authority. Thats why I think organizations need an AI Decision-Rights Ladder: Level 1, Execute: AI acts autonomously (scheduling, routing, comms, compliance logging) Level 2, Summarize: AI aggregates & presents info (feedback synthesis, engagement data, notes) Level 3, Recommend: AI suggests; human decides (dev paths, succession candidates, skills gaps) Level 4, Flag Risk: AI detects anomalies & escalates (retention risk, comp bias, performance gaps) Level 5, Defer: AI informs; human owns the decision (terminations, PIPs, comp changes, promotions) The higher the stakes for a persons career, the more human judgment must remain central. If HR doesnt decide where each tool sits on this ladder, a vendors default settings will. Where would you put performance ratings?

Worth reading

What happens when AI infrastructure, robotics, and shifting career economics all start moving at once? That’s the bigger story behind this week’s Future Ready Leadership Weekly Briefing. I look at where automation is becoming realistic, why traditional assumptions about college and career paths are starting to break down, and what the market is signaling about where technology investment is headed next. Read the full briefing at Future of Work Newsletter: substack.com/@greatleadershi…

You can have the certification, take the course, and put “AI expert” on your resume, but at the end of the day I’m much more interested in what you can actually do. A credential might get you considered. Capability is what gets you hired. I would rather see someone who has spent six months actually building with AI agents, experimenting, solving problems, and showing real outcomes than someone who simply completed a course and has a certificate to prove it. I think this is where hiring is headed more broadly. Degrees and certifications will still matter in some roles, but as technology changes faster, demonstrated capability is going to become a much stronger signal. Show me what you built, what you learned, and what you can actually do with the tools.