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75% of AI Strategies Are for Show. Is Yours?
A former Lululemon CIO just said the quiet part out loud — and Steve thinks every executive needs to hear it.
This week, Steve digs into Julie Averill's New York Times opinion piece on what's actually happening with AI inside real companies. Averill spent eight years as CIO at Lululemon and thirty years in tech before that, so this isn't sideline commentary. It's someone who took the vendor meetings, ran the pilots, and felt the board pressure.
Steve unpacks her two big ideas: AI wishing — treating the technology like a magic wand that lets you skip the hard work of fixing messy data and broken systems — and AI washing, where companies under pressure describe what they hope will happen as if it already had. The numbers are sobering: 95% of enterprise generative AI pilots never delivered results, 75% of executives admit their AI strategy is more for show, and roughly a third of hiring managers who cut a role because of AI have already rehired for it.
Plus: why layoffs announced in the name of AI efficiency are often just moving work onto the people who stay, why 44% of Gen Z workers say they're actively sabotaging their company's AI rollout, and the autopilot analogy Steve keeps coming back to — AI holds the course, but people know where you're going and why.
Two questions to take into your week: What did that vendor actually ask about your business? And have you redesigned the work before cutting the role?
Links:
Amazon Just Proved Nobody Has AI Figured Out
Business Insider dropped a story this week that might be the most important workplace story of 2026 — and it's not about what Amazon is building with AI. It's about what they're being forced to tear down.
Amazon is winding down its flagship AI models, shutting its long-term AI research lab, and laying off some of the most sought-after technical talent in the company — the same team they created a special pay scale just to hire. All of this, less than three years after CEO Andy Jassy stood on stage and championed the very strategy they're now unwinding.
Steve breaks down why this matters far beyond Amazon: if one of the best-funded, most talent-rich companies on the planet is still rewriting its AI playbook in real time, then no one — not you, not your competitors, not the "experts" — actually has this figured out. This episode is about why feeling behind on AI is the wrong frame, why recalibrating your strategy is a sign of strength (not failure), and what leaders should actually do when the ground keeps shifting under their feet.
🎧 10 minutes. One hard truth: behind only means something when somebody else is ahead.
There's a question I ask before I take on any new client: does leadership already know what's broken, or are they hoping I'll discover it so they don't have to say it out loud themselves? If the answer is the second one, I walk.
This week I connect that standard to something quietly telling: OpenAI and Anthropic, the two companies insisting AI is about to remake white-collar work, needed to walk into real organizations and make hard calls about how work actually gets done. They didn't hand that job to a model. They partnered with McKinsey, BCG, Deloitte, and Accenture. Humans they trust.
I break down the three questions I use to decide when trust is actually in the room versus when I'm being paid to paper over the fact that it isn't. And I make the case that walking away from paid work is a privilege — which is exactly why it matters more, not less, for those of us who can actually afford to do it.
Is there a line you've actually walked away from money over, or just one you tell yourself you'd hold?
The AI Jobs Story Nobody Is Telling
Everyone is afraid AI is coming for the jobs. But what if we've been afraid of the wrong number?
New research from the Federal Reserve Bank of Atlanta, the Bank of England, and the Bundesbank surveyed nearly 6,000 senior executives across four economies — and found that more than 90% reported no impact on employment from AI over the past three years. These aren't skeptics. Nearly 70% of them are already using the technology.
So why does the narrative keep running ahead of the data?
In this episode, Steve Cadigan unpacks what the research actually says, why central banks are the right source to trust, and what the real jobs crisis looks like — a projected shortfall of 800 million jobs for young people entering the workforce over the next decade.
The question isn't whether to fear AI. It's whether leaders are going to play defense or offense with it — and whether anyone is going to raise their hand on the job creation challenge that's already here.
For two years, we've blamed AI for the disappearance of entry-level jobs. But what if that story was never true?
In this solo episode, Steve digs into new research from the Federal Reserve Bank of New York — a source with nothing to sell — that ties roughly 64% of rising unemployment among young grads not to AI, but to remote work. The finding that stopped him cold: when teams spread out, the everyday coaching that turns a 23-year-old into a capable professional didn't move to another channel. It just disappeared.
Steve unpacks why nobody noticed, how a thousand small rational decisions quietly pulled up the on-ramp for early-career workers, and why "AI does that work now" became a more flattering story than "we couldn't figure out how to develop people from a distance." Then he goes one layer deeper — past remote work to the short-termism driving companies to mortgage the next decade for this quarter's numbers.
The good news? If we pulled mentorship out, we're also the ones who can put it back. Here's how.
🎧 ~10 minutes. Got thoughts? Find Steve on LinkedIn — he wants to hear from you.
A new PwC analysis of nearly a billion job postings found something hard to ignore: when a role asks for AI skills, it pays about 56% more than the identical role that doesn't — and that premium has doubled in a single year, up from 25%.
In this episode of Workquake Weekly, Steve Cadigan unpacks what that number actually means (and what gets misread about it), why the AI skills shortage is real, and the three paths companies take when they feel the pressure to "do something" about AI: tell people to figure it out, train and develop their own, or hire AI talent while quietly shrinking everyone else.
Backed by the data — Gloat's 144% jump in AI postings, roughly three open AI roles for every qualified person, and ManpowerGroup finding 72% of employers across 41 countries can't find the skills they need — Steve makes the case that the durable answer isn't a skill at all. It's a talent strategy built on constant learning.
The takeaway, straight from the Workquake thesis: AI capacity can be bought. Human capacity has to be built. Only one of those compounds.
If this got you thinking, share it with a colleague — especially the one rewriting their workforce plan right now — and find Steve on LinkedIn to tell him what you're seeing out there.
The Megamanager Era: What Happens When We Stretch Managers Too Thin
The average U.S. manager now has 12.1 direct reports — up nearly 50% in just twelve years. Meta is running new teams at 50-to-1. Nvidia's Jensen Huang famously keeps 60 people reporting directly to him. The "flatter is better" playbook is rolling downhill from CEOs to first-line managers, and in this episode of Workquake Weekly, Steve Cadigan unpacks what that's actually costing us.
Drawing on his nearly four decades in HR — including building LinkedIn's people function during its hypergrowth years — Steve makes the case that the first-line manager isn't overhead. It's infrastructure. They're the layer that catches the quiet drowner on a Tuesday, invests real time in a new hire, and has the hard performance conversation while there's still time to help. That's the connective tissue of an organization. And it's the first thing that disappears when you double a manager's span.
The data backs him up. Gallup reports manager engagement fell nine points between 2022 and 2025, and for the first time in decades of tracking, managers no longer hold an engagement edge over the people they lead. Korn Ferry found 41% of companies thinned management layers in 2025 alone. The Optimism Company found 75% of managers report extreme burnout, with more than one in four planning to leave within the year. Gartner found 69% of HR leaders say their managers don't have the skills to lead through change — and that's before full AI integration even lands.
Steve also pushes back on the AI assumption driving much of the flattening: yes, AI absorbs coordination work, but it doesn't absorb relational work — the judgment, trust, and read on a person that only builds over time. That still takes a human with room to do it. And at the exact moment we're doubling managers' spans, leadership development investment is at an all-time low.
In this episode:
If you're a CHRO, people leader, founder, or first-line manager navigating restructuring, AI-driven cost pressure, or expanding spans of control, this episode is for you.
Connect with Steve: Find Steve Cadigan on LinkedIn — he reads everything.
Enjoyed the episode? Rate Workquake Weekly on your podcast platform of choice and share it with a colleague — especially the leader who just flattened their org.
#FutureOfWork #Leadership #Management #HR #EmployeeEngagement #WorkplaceCulture #AIatWork #Workquake
Three headlines from this week in work, and the pattern connecting them.
Steve breaks down: why dropping degree requirements barely moved the needle on who actually gets hired (fewer than 1 in 700 hires affected), why 55% of HR leaders regret their AI-driven layoffs and one in three companies are now spending more on rehiring than they ever saved, and why a 40% collapse in entry-level tech hiring is quietly mortgaging the leadership pipeline of 2035.
The thread tying it together: companies are making decisions that look smart this quarter but will look like obvious mistakes a decade from now.
10 minutes. No fluff. Find Steve on LinkedIn to keep the conversation going.
Loyalty Is a Broken Contract… And It’s Time to Stop Pretending Otherwise
What if the biggest misunderstanding in the workplace today isn’t about AI, remote work, or even talent shortages… but about loyalty?
In this episode of Workquake Weekly, Steve Cadigan challenges one of the most deeply held assumptions in leadership: that employees should be loyal to organizations, even as the terms of employment have fundamentally changed.
From companies reducing entry-level roles in anticipation of AI, to return-to-office mandates pushing top performers out the door, the signals are everywhere. The traditional “loyalty in exchange for security” contract no longer reflects reality. And yet, many organizations are still operating as if it does.
Steve unpacks what he calls the “Employer Loyalty Paradox” and explores why this disconnect continues to persist… even when both employers and employees know the old model is broken.
Drawing on his experience as LinkedIn’s first Chief HR Officer, Steve shares the story behind the “Tour of Duty” approach… a more transparent, growth-focused model that reframes the employer-employee relationship around mutual value, not false promises.
You’ll hear why:
Retention may no longer be the best measure of success
Growth and employability are becoming the real currency of work
Organizations that embrace shorter tenures can actually create more value
The future of work depends on honesty, not nostalgia
This episode is a call for leaders to rethink what they’re really offering… and what employees are actually agreeing to.
Because the problem isn’t that loyalty is gone.
It’s that the contract behind it hasn’t caught up.
And the organizations willing to rewrite that contract… are the ones that will win.
Tune in for a candid, practical, and optimistic take on what comes next.
Oracle cut 30,000 people last week. At 6 AM. Via email.
No manager conversation. No handoff. Just: you're done, your access is revoked.
Steve has been through dozens of staff reductions in his career — and this one hit differently. Not because of the number, but because of what the process communicated. In this episode, he breaks down why the Oracle move is a leadership failure dressed up as a technology decision, what every major tech shift has taught us about the human cost of "deploy first, figure people out later" — and why the organizations that will win with AI are asking a completely different question than everyone else.
The research is clear. The logic is there. So why aren't more executive teams listening?
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