What your team actually thinks about AI

We spend a lot of time talking to business owners about AI. But some of the most useful conversations we have are with their teams. The people who actually do the work. The ones who'll be using whatever we build.

What they tell us is often very different from what they tell their boss.

This isn't because they're being dishonest. It's because the power dynamic makes certain things hard to say. "I'm worried this will make me redundant" is not something most people feel comfortable saying in a team meeting. Neither is "I think this is a waste of money" or "I already tried something like this and nobody listened."

After working with dozens of SMEs on AI projects, here's what we've found teams actually think. It's more nuanced than you might expect.

The five reactions you'll find in every team

1. The quiet worrier

This person is scared but won't say so. They nod along in meetings, maybe even sound positive. But privately they're anxious. They've seen the headlines. They know their role involves a lot of the repetitive work that AI is supposed to handle. They're wondering whether they should start looking for something else.

According to the TUC's research on AI at work, nearly half of UK workers have concerns about AI affecting their job security. In SMEs, where roles tend to be less specialised, that worry can be even more acute.

How to help them: Be specific about what AI will and won't do. "We're automating the invoice data entry, not your job. You'll still be doing supplier relationships, payment queries, and monthly reconciliations." Specificity kills anxiety.

2. The frustrated enthusiast

This person has already tried using AI tools on their own. They've been using ChatGPT to draft emails, or they've experimented with automation tools for their personal workflow. They're frustrated because the business hasn't caught up. They see the potential and they're impatient.

These people are gold. They're your early adopters, your champions, your proof that the team isn't universally resistant. Find them and involve them from day one.

3. The sceptic

This person has seen technology projects fail before. Maybe the last CRM implementation was a disaster. Maybe someone promised a new system would "change everything" and it didn't. They're not against AI specifically. They're against hype, broken promises, and wasted time.

The sceptic is actually your quality control. Listen to them. Their objections often reveal genuine process problems that need solving before automation can work. CIPD guidance on technology adoption confirms that scepticism often reflects past experience rather than resistance to change.

4. The unaware

Some team members genuinely don't know what AI is beyond what they see in films. They picture robots. They picture HAL 9000. They have no frame of reference for "AI reads your invoices and types the numbers into Sage."

Don't laugh at this. It's not ignorance. It's a failure of communication from the technology industry. The gap between what AI actually does in a business context and what most people think AI does is enormous.

5. The protector

This person has built their role around being the expert in a particular process. They're the one who knows all the supplier codes. The one who can reconcile the accounts faster than anyone. They see AI as a direct threat to their status and expertise.

This reaction is completely understandable. Their expertise is real and valuable. The key is helping them see that AI handles the mechanical parts of what they do, freeing them to use their expertise on the judgment-heavy parts that a machine can't replicate.

What teams actually want

Across all these reactions, there are three things that every team consistently wants:

Honesty

Don't oversell it. Don't pretend it's going to be painless. Don't promise that nobody's role will change. Instead, be straight: "Some of what you do today will be done by AI. The time you get back will go towards [specific thing]. That's better for you and better for the business."

Teams can smell corporate spin from a mile away. According to the OECD's research on AI and the workforce, trust is the single most important factor in successful technology adoption at work. Trust comes from honesty, not from enthusiasm.

Involvement

The worst thing you can do is announce an AI project as a done deal. "We've decided to automate X, it starts next month." Even if the decision is made, the way you involve people in the implementation matters enormously.

Ask them about the current process. What works? What doesn't? What would they change if they could? This does two things: it gives you better information for the project, and it gives the team ownership. They're not having something done to them. They're helping shape it.

Training

This one's simple but often overlooked. If you're changing how someone does their job, you need to show them how the new way works. Not just a one-hour demo on launch day. Proper training, with practice time and someone to ask when things go wrong.

We build training into every project because it's not optional. A tool that nobody knows how to use is worse than no tool at all.

How to find out what your team actually thinks

You probably can't just ask in a meeting. The power dynamic is too strong. Here are some approaches that work better:

Anonymous survey

Keep it short. Three to five questions. "How do you feel about AI being used in your role?" "What parts of your job do you find most repetitive?" "What concerns do you have?" You'll be surprised by the honesty.

One-to-one conversations

Not with the business owner. With someone the team trusts, ideally a manager or team leader who's already on board. Or with us. We often run discovery sessions with team members as part of our initial assessment.

Observation

Sometimes you learn more by watching than by asking. Spend a morning sitting with your operations team. Watch what they actually do, minute by minute. You'll spot inefficiencies and frustrations that nobody thinks to mention because they've just accepted them as normal.

Using this to your advantage

Understanding your team's actual feelings about AI isn't just a nice-to-have. It directly affects whether your AI project succeeds.

The businesses that get the best results from AI are the ones that bring their teams along. Not by forcing enthusiasm, but by addressing concerns honestly, involving people in the process, and making sure the first project delivers something that the team genuinely values.

We've seen businesses where the team went from "we're not sure about this" to "can we do more?" within a couple of months. That shift doesn't happen by accident. It happens because someone took the time to listen.

If you're thinking about bringing AI into your business and you're not sure how your team will react, that's completely normal. It's also solvable.

Get your free AI opportunity report and we'll help you identify not just what to automate, but how to bring your team along for the journey.