I’m sitting at the gate, watching people move like clockwork through the airport—heads down, routines the same, people running on autopilot all looking down at devices with headphones on.

And I can’t stop thinking about work (a common problem for me)

Because what I’m seeing here? It’s exactly how most organizations are approaching AI right now.

They’re moving. But they’re not really changing.

“We’re not automating work. We’re automating dysfunction.”

And we’ve been here before.

What Triggered This? A Conversation With HR

Earlier today, I met with an HR leadership team over Zoom. They had just completed a huge “lift and shift” to the cloud and were disappointed in the results. The system they moved to doesn’t matter, the fact they were disappointed is what worries me.

As part of the process:

Every system was modernized.
Every tool around the system was updated.

But when I asked what had changed in how people actually work, the answer was painfully honest: They said “very little” and I proceeded to ask '“why?” They said…

“It felt easier putting in the technology than changing how people work.”

That sentence has been ringing in my ears ever since, even after a great meeting with another client talking about AI and the “right” way to think about it.

And while this happened in HR, it could’ve been finance, IT, marketing, legal, or customer service. This pattern spans every function.

We keep swapping in new tools without changing behavior, mindset, or structure.

And now we’re doing it again—with AI. I watched someone add AI to a performance management process last week that no one thought added value; now it adds no value faster.

The Cycle We Can’t Seem to Break

1. A business problem shows up and we feel pressure to act fast
     —or we saw something at a trade show (or in our inbox) and just had to try it

2. A tech solution is brought in

3. People keep doing what they’ve always done

4. We wonder why it didn’t transform anything

5. We buy something else, hoping the next one finally works

“The real blocker is never the technology. It’s the people. But people are the part we keep skipping.”

Company A vs. Company B

Let me show you how this plays out:

Company A added an AI chatbot to HR. “We’re transforming our service model!” they said. But nothing else changed.

Employees still waited days for answers. HR was still buried in admin.
They added AI to the mess—but didn’t clean up the mess.

Company B started with a different question:

“How do we want people to feel when they reach out to HR?”

That changed everything.
They reimagined roles.
They rebuilt processes and journeys.
They used AI to handle routine, freeing people to focus on connection, coaching, and care.

Same tool. Totally different outcome.

We’re Moving Faster Than Ever—But in What Direction?

“Change is inevitable. Growth is optional.”
—John C. Maxwell

AI is here. It’s fast. It’s powerful. It’s real.

But if we’re not intentional, it’s going to take us faster in the wrong direction.

“Using AI without rethinking work is like turning on GPS and never setting a destination. You’ll move—but you won’t know where you’re going.”

Velocity is not vision.

Why Change Management Isn’t Enough

Here’s the uncomfortable truth:
We’re still using a change playbook designed for version upgrades—not paradigm shifts.

• Announce the rollout

• Deliver training

• Hope it sticks

That’s not how you lead transformation.

“You can’t manage your way through AI. You have to build the muscle to live inside change. That’s changefulness.”

It’s Not Strategy. It’s Structure.

We’ve siloed transformation into handoffs:

• HR hands off requirements to IT

• IT hands back tools

• No one owns the human experience of change

It’s not that people are change-resistant.
It’s that the system resists them.

“We’re trying to solve 2030 problems with 2010 org charts and 1990s thinking.”

This isn’t just about HR.
It’s about every part of the business that still believes technology creates transformation by itself.

It doesn’t.

The Better Path Forward

Don’t start with the tech.

Start with the work.

• Ask: “How do we want work to work?”

• Design the experience first

• Then build human-machine teaming to deliver it

The companies winning with AI?
They’re not automating.
They’re reimagining.

Let’s Not Waste This Generation of AI

We’re not just facing an opportunity.
We’re facing a decision.

Do we change how we work—how we lead, learn, and deliver?
Or do we keep adding tech on top of broken systems, hoping this one finally works?

“If we don’t change how we work, AI won’t change our outcomes. It’ll just accelerate what’s broken.”

This is the AI generation.

Let’s not be the ones who wasted it.

👇 What You Can Do Right Now

• Share this post with someone who still thinks a new tool is the strategy

• Use the graphics to start a conversation on your team

• Ask yourself: “Are we truly transforming—or just trying to move faster through the same mess?”

About Jason Averbook
Jason Averbook is a globally recognized thought leader, advisor, and keynote speaker focused on the intersection of AI, human potential, and the future of work. He is the Senior Partner and Global Leader of Digital HR Strategy at Mercer, where he helps the world’s largest organizations reimagine how work gets done — not by implementing technology, but by transforming mindsets, skillsets, and cultures to be truly digital.

Over the last two decades, Jason has advised hundreds of Fortune 1000 companies, co-founded and led Leapgen, authored two books on the evolution of HR and workforce technology, and built a reputation as one of the most forward-thinking voices in the industry. His work challenges leaders to stop seeing digital transformation as an IT project and start embracing it as a human strategy.

Through his Substack, Now to Next, Jason shares honest, provocative, and practical insights on what’s changing in the workplace — from generative AI to skills-based orgs to emotional fluency in leadership. His mission is simple: to help people and organizations move from noise to clarity, from fear to possibility, and from now… to next.