[AI SPRINT] 2026: When AI Use Becomes Normal at Work

Yesterday, I met with the executive team of a global services company struggling with AI adoption. Their diagnosis?

“Employees feel unsafe to use AI and don’t know what to use it for.”

Today, I gave a keynote to an executive team of a regional trucking company facing the same problem. Their diagnosis?

“We made AI feel unsafe for employees the last two years. We spent all our time telling everyone how dangerous it was, and they had to use it in only approved ways.”

Two companies. Two industries. Same problem.

Here’s the line most leaders miss: companies that don’t make AI use normal are already behind, even if they think they’re being responsible.

While many organizations spent the last two years minimizing AI risk, others focused on normalizing AI use. The result is a widening gap. In companies that actively encourage AI, we consistently see 40–45% adoption. In companies that don’t, adoption stalls at 5–10%.

That difference matters. It’s the difference between saving an hour per employee per day and leaving that productivity on the table. It’s the difference between learning how to work with AI now and scrambling later.

What makes this worse is that the productivity is already there. It’s just hidden.

In December, I covered Anthropic’s finding that 69% of employees are not comfortable talking about how they use AI. That means real value is being created quietly, without support, without shared learning, and often without leadership awareness.

This is the real cost of not normalizing AI. You don’t eliminate usage. You eliminate visibility, learning, and leverage.

The trucking company shared a concrete example. A competitor now generates customer quotes using an AI agent in about 30 seconds. For them, it still takes over an hour. That gap didn’t come from better technology. It came from making AI use normal early.

The Tipping Point: Non-Users Are Becoming Outliers

Here’s the uncomfortable truth about 2026: the people not using AI are becoming outliers.

Gallup found that 27% of white-collar workers now use AI regularly at work, nearly double the 15% from 2024. Our own research at Stellis shows higher, around 40% across knowledge workers. Daily AI use sits near 10% and climbing, delivering up to 20% productivity gains.

These aren’t early adopters anymore. These are your peers, your competitors, and increasingly, your own employees.

When leaders don’t use AI themselves, predictable things happen. They approve work they can’t evaluate. They set expectations they can’t measure. They coach on tools they don’t understand. They miss opportunities for AI-driven innovation.

In 2026, that’s not a minor blind spot. It’s a leadership gap.

Your team is moving ahead whether you’re ready or not. The only question is whether they’re doing it with your guidance or in spite of your silence.

The good news: 2026 is when this flips. This is the year organizations unlock the productivity that already exists inside their teams.

And it’s happening faster than most leaders expect.

Microsoft Just Declared AI the Interface for Work

This week, Microsoft renamed its core Office suite to Microsoft 365 Copilot, effectively declaring itself an AI-first company almost a full year earlier than I forecast last August.

This isn’t a feature update. It’s a business model shift—for every business.

Microsoft isn’t betting on people writing better documents. It’s betting on people using AI to get work done. The document is no longer the unit of work. The outcome is.

AI becomes the interface. You don’t start your day opening Word or Excel. You start by asking AI what needs attention, and it orchestrates the tools behind the scenes.

That shift matters because it sets expectations at the platform level. When AI is already on every employee’s desktop, the question stops being whether to adopt AI. It becomes whether your people are ready to use it effectively and safely.

Organizations that prepare their people now, by making AI use normal, expected, and supported, don’t just keep pace. They turn speed into advantage.

Get Started with AI the Right Way in 2026

If you’re reading this and thinking, “We know we need to move, but we’re not sure where to start,” there are two clear paths, depending on your readiness.

Want to understand where you stand?
Next Thursday, January 15, I’m hosting a free webinar: How SMBs Win with AI in 2026. I’ll share what we’re seeing across industries, what’s actually working, and how leaders are preparing their teams. Live Q&A. No sales. Just practical guidance.

Ready to move immediately?
Our 30-day AI Enablement Jumpstart is built for organizations that want to move from intention to execution. In one month, we align leadership, establish guardrails, train staff and managers, and help make AI safe, visible, and supported. Reply if you want to learn more.

The Easy Way to Make AI Stick

At this point, the goal isn’t more AI enthusiasm. It’s consistency.

Across dozens of organizations, we see the same pattern. AI adoption accelerates when leaders stop treating it like a special initiative and start reinforcing three simple signals:

• Normal: Leaders use AI openly in their own work, making it routine rather than risky.

• Expected: Managers are explicit that experimenting, learning, and sharing AI use is part of the job.

• Supported: Good AI use is recognized and reinforced, not second-guessed or punished.

When these signals are present, AI use moves out of the shadows and into everyday workflows, where productivity gains compound instead of disappearing.

Everything that follows is about operationalizing those signals.

What This Means for Your Business in 2026

The shift from “AI is too risky” to “AI is expected” happens this year. That’s uncomfortable for a lot of leaders. Most are trying to catch up while managing risk.

Here’s how to lead it.

1. Make experimentation, learning, and sharing the expectation
If your AI guidance is mostly about restrictions, you’ve made AI feel unsafe. Flip the script. Tell employees explicitly that you expect them to experiment, learn what works, and share those learnings.

Define clear outcomes AI should support, such as faster proposals, better analysis, higher-quality content, and reduced time on routine work. Pair those outcomes with permission to try, fail, and iterate.

2. Train leadership first, then model and reward the behavior
Train your leadership team together. Every manager should be using AI daily before asking their teams to do the same.

More importantly, leaders must model AI use openly and reward experimentation and sharing. Recognition and visibility matter more than formal reviews right now.

3. Pick three workflows for agents and assign owners
Look for workflows with high volume, clear success metrics, and meaningful time drain. That’s where agents deliver ROI fastest. Customer support escalations, sales follow-up, content generation, and operational reporting are good places to start.

Assign owners. Pilot. Measure. Document what works. By Q2, you should have real data and teams that see AI as capability, not risk.

A Clear Next Step

If you take one thing from this, let it be this: AI advantage in 2026 won’t come from tools. It will come from leadership choices.

You can keep AI informal and invisible, or you can make it normal, expected, and supported.

If you want help figuring out where you stand and what to do next:

• Join the free webinar: How SMBs Win with AI in 2026

• Explore a 30-day AI Enablement Jumpstart to build real momentum fast

Either way, this is the year you decide how AI shows up inside your organization.

— Trent

About Trent: Trent Gillespie is an AI Keynote Speaker, CEO of Stellis AI, former Amazon leader, and advisor on operationalizing AI in business. Book Trent to speak to your group or book a call to discuss using AI within your business.

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