[AI SPRINT] How hard should leaders push on AI?

This week: Join us Friday, what the AI artist Astra Blue means for leaders, and how to prepare your organization for AI.

Have you heard of Astra Blue AI?

I hadn’t, until yesterday. It’s a new AI pop artist, and worth checking out. The songs are catchy, the videos are polished, and the message is pointed: AI is coming for your job.

I don’t know what to call it. Art? An AI influencer? A campaign by someone with an agenda? There’s no clear human behind it, so there’s no one to ask.

But I keep coming back to one thing. Someone used AI to make a very good argument against AI.

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That’s the situation leaders are in right now, in one song.

It demonstrates AI capabilities are real. Building something this polished took a team and a budget not long ago.

The fear is real too. People are hearing their own worries set to a beat, and it resonates because it isn’t made up. Companies are announcing layoffs and naming AI as the reason.

Leaders are being forced to choose which one of those truths they represent: the capability, or the fear.

The gap is getting wider

I expected AI adoption to get easier over time. Instead, it’s often getting harder.

Leaders are seeing more evidence every month that AI works. Their boards are asking whether they’re keeping up. Their tech teams are shipping faster than ever. Sales cycles are getting shorter. Quality is improving.

Staff are seeing something different. Across the organizations I work with, the pattern looks roughly like this:

  • 10 to 20% are leading. They’ve figured out how AI fits their work and they’re running with it.

  • 20 to 30% use it reluctantly for small tasks, usually without the support to go further.

  • 50 to 60% are holding back. Most of them are quietly avoiding it: skipping the training, not opening the tools. A smaller group is actively pushing back, sometimes against colleagues who use it, or leadership.

Call it a K-shaped adoption curve. One group is accelerating, and the other is pushing the breaks.

The important part is that the people holding back aren’t irrational. They see leadership celebrating productivity gains and they don’t see where those gains go. If you were in their position, you’d hesitate too.

So how hard should you push?

My answer: hard. Building AI skill across your organization isn’t optional anymore. But pushing harder doesn’t work if you do it in the wrong order.

As I often speak about, effective AI adoption happens when AI use is Safe, Supported, Expected, and Rewarded. In that order. Most organizations skip straight to Expected, and that’s where resistance turns into resentment.

Safe. People won’t experiment with something they think will replace them. Generic reassurance doesn’t help, because your staff have heard it before. Make commitments you can actually keep, and that they can check:

“No role will be eliminated because of AI in the next 12 months. If AI changes your role, we’ll retrain and redeploy you first.”

“When AI frees up capacity on your team, your team has a say in what that time goes toward.”

“Every quarter, we’ll share what AI saved us and where that capacity went.”

If you can’t honestly make commitments like these, don’t make vague ones instead. A broken promise on job security will cost you this initiative and the next one.

Safe also means listening. Create real channels for concerns about roles, quality, the environment, fairness, and take them seriously. Some of those concerns will improve your rollout. Treat listening as part of the plan, not something you do once the plan is finished.

Supported. Train people on the tools, but more importantly, show them what good looks like in their specific role. A customer service rep and a finance analyst need different examples. Then keep updating that, because the tools change every few months.

Expected. Once people feel safe and supported, make it clear this is part of the job:

“We expect everyone to use AI to improve their work, not just make it faster.”

That second half matters. Speed alone tells people you’re measuring them for replacement. Better work tells them you’re investing in them.

Rewarded. Finally, connect it to how people grow:

“Starting in 2027, our performance standards will include how well you find ways to use AI to improve your own work, improve our business, and share what you’ve learned with others.”

“How well you use AI to advance our goals will be part of how we evaluate promotions.”

Put Rewarded before Safe, and you’re threatening people. Put it after, and you’re giving them an opportunity.

Back to Astra Blue

There will be more content like it, and much of it will be better. You can’t keep your staff from seeing it, and you shouldn’t try.

What you can do is make sure your organization’s experience of AI is different from the story in the song. That depends on what you do first, not how hard you push.

Join us this Friday

If this issue hit close to home, bring your questions to this Friday’s AI SPRINT monthly recap, October 23, noon Pacific. It’s open to all leaders. We’ll cover:

  • AI agents. What’s changed this month, and what you should be doing now to prepare your organization for them.

  • ChatGPT’s Dot. What it is, what it can do, and what it means for how your team works. I’ve been testing mine for the past few weeks and will share what I’ve learned.

  • Adoption research. More of what we’re seeing across organizations about who is adopting AI, who isn’t, and what’s actually closing the gap.

  • Open Q&A and discussion, as always.

Plus: For association leaders

Right after the recap, we’re launching our first industry cohort, built specifically for association leaders. RSVP right now to get it on your calendar. Associations face their own version of the adoption challenge: small staffs, volunteer leadership, and members who expect you to have answers about AI for their industry too.

At the launch, we’ll share our new research on AI adoption in associations, based on our analysis of 22 associations’ AI efforts this year.

Trent Gillespie is CEO of Stellis AI and a keynote speaker helping business leaders understand and operationalize AI in their companies. He spent almost nine years leading global innovation efforts at Amazon before leaving to help other companies build the capabilities they need to compete. Book Trent to speak to your group or book a call to discuss using AI within your business.

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