Why AI success depends on team-level adoption

New research suggests that artificial intelligence (AI) adoption isn’t just uneven between companies. It’s uneven within them.

According to Employment Hero’s 2025 report, 73% of senior managers in the UK use AI tools monthly. Among entry-level staff, that number drops to just 32%.

This shows how quickly leaders are moving from interest to application. But it also tells us something else: we’re reaching the point where adoption needs to shift from individual use to shared benefit.

If you’re running a small business and you’re one of the only people experimenting with tools like ChatGPT or Copilot, you’ve already done the hardest part: getting started.

What helps next is making what’s already working feel accessible across the team.

Why team-level adoption unlocks better wins

Quick wins with AI are valuable. They show what’s possible, prove ROI, and help people build confidence.

But here’s what we’ve seen: early wins multiply when they’re shared. They land harder, last longer, and lead to real momentum when they’re picked up across roles.

Think of it like fitness. One person getting stronger is great. But if the whole team builds stamina, you can take on bigger challenges.

The real power of artificial intelligence adoption isn’t in what one person can do alone. AI adopters who have already seen ROI are the ones focused on deliberate changes in how people, processes, and technology work together.

That’s when AI shifts from interesting to business-changing.

Signs your team is stuck at “top-only” adoption

When you’re close to the tools, it’s easy to assume others will pick them up naturally. But if AI usage stalls at the leadership level, small but telling signs start to show.

Sometimes, it’s a knowledge gap. The CRM’s AI assistant is right there, but only a few people know what it does. Other times, it’s confidence. People don’t want to be the only ones asking how a feature works, so they quietly skip it.

You become the go-to for anything AI-related by default. And when you’re not around, things slow down.

None of these means your team is resistant. But they do suggest the knowledge isn’t spreading yet, which could signal the early stages of an AI skills gap.

Why does this "AI advantage gap" exist

The term “AI advantage gap” sounds dramatic, but the reasons behind it are very human. In most teams, AI is either a strategic curiosity for leaders or a handy tool for teams with obvious use cases (finance, marketing, and data analysis).

For everyone else? AI can feel distant because:

• They haven’t seen it applied to the tasks they handle every day.

• They’re unsure which tools are “allowed” or encouraged.

• They assume AI means coding or deep technical skills.

It’s easy to mistake “not interested” for “not aware.” The AI skills gap shows up because the opportunity hasn’t been made obvious, safe, or accessible. Closing the gap starts with making AI visible, relevant, and safe to try, so every team member can see themselves using it.

How to make AI feel part of the day-to-day

Let’s put the slide decks and training modules aside for a second.

If you’re trying to help your team get more comfortable using AI at work, the answer is to create a work environment where AI feels like something they’re allowed to play with.

Here are a few small shifts we’ve seen help:

1. Make it part of everyday conversations

When AI only shows up in strategy decks or leadership circles, it stays abstract. But when it shows up in the little moments, it becomes something more approachable.

Imagine a Tuesday team meeting where someone casually mentions that they used Notion AI to clean up a rambling update before sharing it with a client. No deep dive. No explainer. Just a passing mention.

That kind of visibility normalises AI, not as “another thing to learn”, but as something real people already use for real tasks.

2. Let people “borrow your brain”

Most teams don’t get value from AI tools on Day 1. It often takes a few nudges or examples before people figure out where it fits into their work.

If you’ve already figured out prompts that save you time, or ways to turn messy inputs into useful drafts, share them.

These prompts don’t have to be too polished. In fact, it’s better if you’re transparent that they aren’t because it makes them more approachable. Invite them to steal from it, tweak it, or add their own. That’s how team knowledge compounds.

3. Talk about the outcome, not the tech

Sometimes what holds people back is the way we talk about it.

If it’s framed as “natural language processing” or “generative models,” it can sound like something reserved for specialists. But if it’s described as a support tool to accommodate customer inquiries, or a built-in assistant to tidy up a report, it suddenly feels relevant to anyone.

That shift in language lowers the barrier. It invites people in without making them feel like they need to understand the tech to benefit from it.

From isolated use to shared capability

Artificial intelligence adoption doesn’t depend on everyone becoming a tech expert. It depends on creating the kind of environment where trying something new feels normal, useful, and safe.

When team-level adoption starts to take hold, you’ll notice the shift. Small experiments become shared habits. Curiosity replaces hesitation. The work gets lighter, and the wins stretch further.

And the best part? You don’t have to lead every AI conversation. It becomes one that the team feels allowed to have.

The AI advantage gap doesn’t have to widen. Not in a team like yours. At Adapt, we help small businesses make AI feel natural across roles, tools, and teams. If you’re looking to move from early tests to everyday wins, we’d love to help.