Jacob Morgan

New Book: Futurist, 6X Author, & Speaker

#EmployeeExperience #FutureofWork #Leadership

[Jacob Morgan @jacobm]

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: https://t.co/Q19fYto4a1

[Jacob Morgan @jacobm]

For two years I told young workers to take the in-office role, show up when their peers wouldn't, and build their networks while everyone else was home complaining about commutes. I got a lot of angry emails for it. Now the Federal Reserve has the data.

The @NewYorkFed's latest research found that remote and hybrid arrangements, not AI, are the primary driver of higher unemployment among workers in their 20s. Researchers estimate 64% of the rise in younger workers' unemployment since the pandemic comes down to remote work. The March jobless rate for workers aged 22 to 27 hit 7.2%, up from 6.1% before the pandemic.

The reason is straightforward. Early-career workers build capability through proximity to people who already have it. You watch how a seasoned leader handles a difficult conversation. You hear how a manager thinks through a decision out loud. You pick up judgment, institutional knowledge, and professional norms through thousands of small moments that a Zoom grid cannot reproduce. Senior workers who went remote were fine. They already had everything they needed. Junior workers did not.

The playbook for someone in their 20s right now should be the opposite of what it was in 2020. Take the in-office role. Be around people who know things you don't. Build the network, absorb the institutional knowledge, and negotiate flexibility once you've earned it, not as a condition of showing up.

Organizations that figured this out early are quietly building a talent advantage. The ones that stayed fully remote are sitting on a development gap that will take years to close.

[Jacob Morgan @jacobm]

AI isn’t just a technology story. It’s a stress test for how organizations build talent, trust, and judgment.

This week’s briefing connects remote work, data center backlash, @Uber's HR cuts, @AnthropicAI's warning, and my conversation with DJ Casto.

Full briefing on Substack. https://t.co/8OWK9MYeLs

[Jacob Morgan @jacobm]

I did a video a few days on on data centers, breaking down what they are, what they do, and dispelling myths. The comments I get, are just crazy. Full video is here: https://t.co/c5ulg3RCsm

[Jacob Morgan @jacobm]

This is the kind of AI data leaders should pay attention to, but the chart is only half the story.

@AnthropicAI tested whether Claude could look at a real internal research session, stop at the moment where a human researcher took a wrong turn, and suggest the better next move. In the latest version shown here, Claude beat the human researcher 64% of the time. That matters because this is the kind of work people usually describe as judgment, taste, discernment, and knowing what to try next.

The technical progress is real. The numbers are real. An AI system getting better at next-step research decisions should make every leader sit up a little straighter.

What bothers me is the messaging around it.

The same companies showing this kind of progress are also warning that AI may be moving too fast and that governments may need to slow things down or regulate more heavily. Some of that concern may be valid, but leaders still need to look at the incentives behind the warning.

Heavy regulation does not land evenly. The companies that already have the money, compute, customers, legal teams, and infrastructure can adapt. The startups, open-source builders, and smaller competitors usually cannot. So when one of the biggest players says the industry may need stricter rules, the question is not only whether the technology is powerful. The question is who gets protected once the rules arrive.

That is why this whole conversation feels so messy. The technology is real, the acceleration is real, and the positive impact can be real, but the constant swing from hype to panic to reassurance to warning makes it harder to know what to trust.

The data deserves attention, but the messaging deserves skepticism.

That's what I get in today's episode of Future Ready Today: https://t.co/2vFP31Divp

[Jacob Morgan @jacobm]

@Microsoft just showed us a version of workplace AI that will sound incredibly useful to a lot of executives, and deeply uncomfortable to a lot of employees. That tension is the point.

At Build 2026, Microsoft unveiled Project Solara, a platform for agent-first devices. The centerpiece is a wearable AI badge roughly the size of a standard office ID card. It clips onto your clothing or hangs on a lanyard, and comes with a screen, camera, and fingerprint scanner. Instead of constantly prompting AI, the device understands what is happening around you and acts on your behalf.

The business case is easy to understand. The badge can pull context from your calendar, emails, meetings, and physical surroundings. Before you walk into a meeting, it can already know who you are meeting with, what the context is, what you need to know, and what should happen next.

For knowledge workers who spend a large part of the week managing email, searching for information, rebuilding context, and moving between calls and devices, even a small reduction in that friction could be meaningful. For retail, logistics, manufacturing, and field work, the use case is clearer because people often need information while their hands are occupied.

But this is where leaders need to slow down. The productivity promise is not really the camera. It is the ambient intelligence. The badge is always there, absorbing context, learning from the environment, and potentially turning everyday work into data. That may make work faster, but it also changes how people behave when they know the device is present.

The effect is called the chilling effect. When people believe they are being observed or recorded, they become more guarded, formal, and risk averse. They stop floating half-formed ideas, disagreeing out loud, and saying what they actually think. They start saying what will look acceptable in an official record.

We saw a version of this with open offices. The promise was more collaboration, energy, and spontaneous interaction. But @Harvard research found that open offices reduced face-to-face interaction by around 70% as people put on headphones and moved into digital channels to recreate privacy. The design choice meant to increase connection produced withdrawal.

Ambient AI could create a similar paradox. A company may get more context, automation, and productivity, while also getting less candor, trust, and fewer real conversations. That is not just a technology issue.

The question is not whether an AI badge can make work faster, it probably can. The question is what conversations and behaviors leaders want people to feel safe having, and how they protect those as work gets smarter.

The future of work will not just be shaped by what AI can do. It will also be shaped by what people still feel safe enough to say.

I unpacked this on today’s podcast episode. https://t.co/pg3kxU7PQR

[Jacob Morgan @jacobm]

If you fail to understand and invest in your people, even the greatest strategy will fall apart.

[Jacob Morgan @jacobm]

Everything you've heard about data centers is probably wrong. I say that based on the data. And I think it matters more than most people realize.

New data centers poison the water? The newest facilities from Oracle and Microsoft use closed-loop cooling — water fills the system once during construction and circulates forever, never evaporating, never touching the local supply. Microsoft has already improved its water efficiency by 39% on its existing fleet before these new systems even fully come online.

Data centers are destroying the power grid? Tech companies are currently the largest single buyers of clean energy on the planet. Amazon, Microsoft, and Google held over 40 gigawatts of contracted renewable capacity by the end of 2025. And they are directly funding the first serious private investment in nuclear power America has seen in decades — Google with Kairos Power, Microsoft restarting Three Mile Island, Meta partnering with Oklo for 16 small modular reactors in Ohio, Amazon backing nuclear programs across the country. Data centers aren't just consuming the grid. They're rebuilding it.

Data centers kill jobs? Construction spending hit $77.7 billion in 2025 — a 190% year-over-year increase. Tradespeople wages are up 30%. Virginia alone gets 74,000 jobs and $9.1 billion in annual GDP from its data center industry. And according to S&P Global, data center and AI investment accounted for 80% of all US private economic growth in the first half of 2025. Harvard economist Jason Furman put it even more starkly: strip out data center investment entirely, and the rest of the American economy grew at 0.1% annualized. Essentially zero. Data centers aren't killing jobs. Right now, they are the economy.

Taxpayers are subsidizing Big Tech? These are sales tax exemptions on equipment, not cash payments or handouts. Virginia deferred $1.6 billion in sales taxes and received $2.1 billion back in other tax revenues, plus $9.1 billion in annual economic output. That's not a giveaway. That's a return on investment.

And here's what almost never gets said in this debate: data centers are the backbone of the American economy in ways most people never see. Every bank transaction, every hospital record, every supply chain, every e-commerce purchase, every payroll system — all of it runs through these buildings. When you swipe your card, check your 401k, order something online, or your doctor pulls up your records, a data center made that possible in milliseconds. This isn't future potential. This is the infrastructure your daily financial and economic life already depends on, right now, today.

None of this means every data center project should be waved through without scrutiny. Smart siting, honest community engagement, and responsible grid planning all matter — and getting those things right is exactly how you build infrastructure that lasts and earns public trust. But the wave of fear and misinformation driving opposition right now is doing real, measurable damage to America's AI infrastructure at the exact moment we can least afford it.

Here's the number I want you to sit with. In late 2024, Chinese AI models accounted for 1% of global AI workloads. By the end of 2025, that number was 30%. Every data center project that gets cancelled or blocked in America doesn't stop AI development. It moves it somewhere else — to a country that doesn't share our values, our privacy laws, or our interest in your freedom.

I broke all of this down — with sources — in today's episode of Future Ready.

https://t.co/YTNwRXuHjS

[Jacob Morgan @jacobm]

Thrilled to welcome Melkeya McDuffie, SVP and Chief People Officer at @Group1Auto, to our Future of Work Leaders community.

Melkeya is a master at aligning human capital with aggressive business growth and profitability.

From large-scale HR transformations to high-impact talent forecasting, she brings the kind of operational rigor that turns workforce strategy into a competitive advantage.

Her track record of driving massive cost savings while building sustainable, growth-ready cultures is exactly the caliber of insight our group thrives on.

This is why top-tier leaders join us. We skip the fluff to share the high-stakes playbooks that actually drive enterprise value.

If you’re a leader ready to sharpen your strategy alongside peers like Melkeya, you belong here.

Join us by requesting an invite here: https://t.co/KKgpiDdzx1

[Jacob Morgan @jacobm]

Remote work may be breaking the career ladder in ways most organizations still don't want to talk about.

New research from the @NewYorkFed points to a much more uncomfortable issue. Remote and hybrid arrangements may be a major driver of higher unemployment among workers in their 20s, with researchers estimating that 64% of the rise in younger-worker unemployment since the pandemic is attributable to the rise of remote work.

Experienced workers can usually function well in remote environments because they already have the invisible infrastructure of work. Younger workers do not have that yet.

Historically, development happened through proximity. You picked up the norms, shortcuts, standards, and judgment of the organization through hundreds of small moments that were never written into an onboarding plan. Those moments are very hard to recreate with a calendar invite.

A company can be productive and still be bad at developing young talent. A remote policy can make experienced employees happier while making early-career employees easier to overlook.

Different career stages require different systems. Senior employees may need autonomy, flexibility, and focus. Early-career employees need exposure, feedback, repetition, mentorship, sponsorship, and a real chance to be seen by people who can help them grow.

Most organizations still design work policies as if everyone is in the same stage of development. That is the mistake.

The future of work is not remote or office. It is intentional or accidental. Right now, too many companies are accidentally weakening the career ladder while telling themselves they are simply offering flexibility.

I unpack the Fed research and what it means for early-career talent in today's Future Ready Today episode here: https://t.co/p4xoqaYk0z

[Jacob Morgan @jacobm]

Ron Vachris runs a $421 billion organization and he is not cutting workers because of AI. That fact alone is worth sitting with, because most of the coverage in this space is pointing the other direction.

Vachris was at the @EconClubChi and was direct about the philosophy: "We've not displaced people because the business is growing at a faster rate." He went further, saying AI would not be making buying decisions and would not replace the judgment of skilled buyers or evaluators. He called it "extremely good in an assistive nature." Not a replacement. A support.

What is easy to miss here is that @Costco is not anti-technology. They use AI in pharmacy, accounting, gas stations, and IT. Vachris is not making a values statement about human dignity. He is making a strategic argument about competitive advantage. The organizations that understand that distinction are building something different from the ones cutting headcount to fund AI deployment.

He was asked what the biggest threat to Costco was. Not AI. Not @amazon . Not @Walmart. His answer: "The biggest threat to our company is us losing our way." That is the answer of a CEO who has thought carefully about what actually creates durable advantage in his business, and it is not a cheaper headcount ratio.

The carousel breaks down both paths. The real question is not which one works in the short term. Both do. The question is what each one looks like three years from now.

[Jacob Morgan @jacobm]

https://t.co/h9wvJPhIQd

[Jacob Morgan @jacobm]

There is a reason organizations default to measuring AI usage instead of AI value. Usage is easy to count. Value requires agreeing on what success looks like before spending begins, and that conversation is uncomfortable to have with a leadership team that has already committed to a number.

@Uber is the clearest example of what that avoidance costs. 95% of 5,000 engineers using AI tools monthly. $2,000 per month per heavy user. The entire 2026 AI budget gone by April.

Their internal leaderboards rewarded token consumption, which meant every engineer had every incentive to use the tools as aggressively as possible. Their COO's summary: there was no clear link between that usage and improvements in actual products. The organization had built a system that made activity look like progress.

The @RANDCorporation data shows how far this gap extends. 2,400 enterprise AI initiatives studied. 80% failed to deliver their intended business value. The variable that separated a 4% success rate from an 85% success rate had nothing to do with the tools. Organizations that formally reported AI value to leadership achieved high value at 85%. Organizations still in informal pilots with no outcome tracking achieved it at 4%.

The infrastructure around the work matters more than the work itself. That is the pattern that keeps showing up. And it will keep showing up until leadership teams decide that "we are using AI" and "AI is producing value" are two different claims that require two different answers.

[Jacob Morgan @jacobm]

https://t.co/RCr9PDRR82

[Jacob Morgan @jacobm]

Even with Claude Opus 4.8, I get responses back like this with Japanese characters in them:
"Over years of研究 and working with leaders across industries." A few small mistakes like this in an enterprise can be quite costly when applied to large-scale agentic usage.

[Jacob Morgan @jacobm]

A lot of AI layoffs are not a technology story. They are a budgeting story.

AI did not replace the work. The AI bill got big, the productivity gains did not show up fast enough, and headcount became the easiest lever to pull.

That is a very different story from the one we keep hearing. "AI made us more efficient, so we need fewer people" sounds strategic. What actually happened in most cases is messier. Companies bought the tools, opened access to everyone, pushed usage across the business, and called it transformation. What they rarely did was redesign workflows, rethink operating models, or build real discipline around where AI creates value and where it just creates cost.

This is why so many leaders are asking the wrong question. The question is not how fast you can push AI into every corner of the company. It is whether you are using it with enough discipline that it actually improves the business — instead of just inflating a new layer of spend. More AI usage does not automatically mean more AI value. Sometimes it just means a larger invoice with a more impressive story attached to it.

That is what makes @Costco worth paying attention to. They are not rejecting AI. They are rejecting the lazy assumption that AI strategy has to start with replacing people. They seem to understand something a lot of companies are missing: the real advantage is not automation. It is knowing where human judgment still matters, protecting it, and using AI to strengthen it rather than as an excuse to cut around it.

If your AI strategy starts with headcount reduction before it starts with workflow redesign, you are not building a future-ready company. You are shifting costs around and calling it innovation.

[Jacob Morgan @jacobm]

Learning is something that cannot be delegated. - Marc Borggreven, Global Human Capital Leader at @PwC

[Jacob Morgan @jacobm]

One of the main reasons recent college graduates are struggling to find jobs isn't the economy, and it isn't AI. It's that they're graduating unprepared for the workforce and I don't see anyone talking about this.

The average grade given to students at American colleges is now an "A."

Harvard's median graduating GPA last year was 3.83. More than 60% of all grades at Harvard were A's, up from 25% just twenty years ago. This month, Harvard's own faculty voted to cap A grades at 20% per class. Their internal report called the grading system a "race to the bottom."

The ACT which is the standardized test that measures whether students are actually ready for college-level work just hit a 30-year low. The average score for the class of 2024 was 19.4 out of 36. And 43% of students met none of the four basic college readiness benchmarks. Not one. And this is despite the test now being shorter and easier than it was in previous years.

So we have students graduating with 3.7 GPAs who couldn't demonstrate a coin-flip probability of earning a B in a first-year college course on an independent exam. The grade and the reality are completely disconnected.

And then they enter the workforce and wonder why it's so hard.

We have a disastrous situation of over confident grads being met with the reality of employers who tell them they aren't qualified. When we aren't honest with people about their performance they don't realize that they have a gap they need to close.

A Gallup survey found that 93% of current college students feel confident their degree is preparing them for work. Only 54% of employers agree.

That 39-point gap is the gap between what the transcript says and what the person can actually do.

I don't think students are to blame here. They were told they were excellent. They were given A's. Nobody told them the truth. And now they're walking into interviews with real confidence and real gaps and the hiring manager is the first person in four years to give them an honest assessment.

That's a failure of the system, not the student.

If you're a recent graduate, you can't wait for someone to hand you the honest feedback your education didn't. You have to go get it by taking on projects that expose your gaps, ask for hard feedback, build skills in public, treat the early years of your career as the education your tuition should have bought.

And if you're a leader hiring right now, the GPA on the resume tells you almost nothing.

I do a deep dive on this in today's Future-Ready Today podcast episode which you can listen to here: https://t.co/X8ns0pNe3T

[Jacob Morgan @jacobm]

https://t.co/itsE60hBrs

[Jacob Morgan @jacobm]

A year ago, the loudest voices in AI told every executive the same thing: act now or your company won't survive.

@DarioAmodei, CEO of @AnthropicAI, said AI would eliminate 50% of all white-collar jobs within five years. Sam Altman of @OpenAI said entire job categories would be totally, completely gone.

And it worked exactly as designed.

When CEOs make those kinds of predictions publicly, every CIO, CHRO, CFO, and board member hears the same alarm go off simultaneously.

Fear doesn't just inform decisions, it short-circuits them. Nobody negotiates when they think they're already behind.
Contracts got signed, budgets moved fast, and that urgency turned into revenue, which turned into valuation.

Anthropic went from $9 billion to $30 billion in months. OpenAI hit $852 billion. Together, the doom narrative helped produce somewhere between one and two trillion dollars in private market valuation.

Then this week, both Altman and Amodei started sounding noticeably more optimistic.

Altman said he's "delighted to be wrong." Amodei now says automation may actually expand the work people do. Not because the technology changed, but because the audience did.

You can't take a company public by telling pension funds, mutual funds, and retail investors that your product will destabilize society. So the narrative flipped. Doom got them the valuation. Optimism sells the IPO.

The truth is, neither story was told to help you make better decisions about your workforce or your career. Both were told to serve a financial outcome at the right moment.

So which narrative has been quietly shaping your AI strategy, and does your answer to that change anything?

I've put 3 questions every leader should sit with before their next AI decision on the last slide. Swipe through and let me know your honest take.