There are two sides to the employee AI experience

When we talk about employee experience and AI, we often think about the employee as the user.

Does this tool make their job easier? Can it remove repetitive tasks? Does it help them find information, generate ideas or work more effectively?

Those are useful questions. But there's another side to the experience: the employee as the subject of AI.

AI can now play a role in recruitment, workforce planning, performance analysis, employee listening, scheduling and the allocation of work. Other workplace technologies can monitor location, activity or behaviour.

The UK Government is currently consulting on workplace monitoring technologies, including AI-driven management tools, productivity scoring, biometric surveillance, GPS monitoring and keystroke logging.

The regulatory questions surrounding these technologies are important. But there is also an employee experience question that deserves our attention.

What is it like to work somewhere when you don't fully understand how technology is being used to understand, assess or make decisions about you?

We need to think beyond the user experience

EX professionals spend a lot of time thinking about how employees experience organisational processes and systems.

We map journeys. Identify pain points. Explore moments that matter. Look at where processes create unnecessary effort or frustration. Increasingly, we're also considering how AI could improve those experiences.

But the growing use of AI means we may need to broaden that lens.

Imagine an employee going through a recruitment process in which AI plays a role in screening applications. Or receiving feedback that has been informed by automated analysis. Or discovering that workplace activity data contributes to how productivity is assessed.

The system might work perfectly from a technical perspective. The process might even be faster and more efficient than what came before.

But that doesn't automatically make it a better experience.

Employees may have entirely reasonable questions. What information is being used? How accurate is it? Who has access to the output? Can a human challenge the recommendation? What happens when the technology gets something wrong?

These aren't simply questions for IT, legal or data teams.

They're questions about people's experience of work.

Trust isn't something we can communicate into existence

When employees are hesitant about new technology, the organisational response is often communication.

Explain why we're introducing it. Tell people how it works. Provide training. Share examples of the benefits. Reassure employees that AI is there to support them.

Good communication absolutely matters. But there's a limit to what it can achieve.

If people don't agree with the underlying way technology is being used, explaining it more clearly won't necessarily make them trust it.

An organisation could be completely transparent about monitoring employees' activity, for example. That transparency would remove uncertainty, but it wouldn't answer the more fundamental question of whether employees believe that monitoring is reasonable.

Trust therefore goes beyond transparency. It involves purpose, proportionality and fairness.

Why are we using this technology? What problem does it solve? What information do we really need? How will it affect people's autonomy? Where does human judgement sit? And would we be comfortable having an open conversation with employees about the answers?

For EX practitioners, those questions should sound familiar. They're fundamentally questions about designing experiences around people rather than systems.

Employee voice needs to move upstream

There is also an opportunity here to rethink when employees become involved in workplace technology decisions.

Too often, employees enter the process at the adoption stage.

A platform has been chosen. Decisions have been made. Processes have been redesigned. Then the organisation turns its attention to employees and asks how it can encourage them to embrace the change.

By then, some of the most important EX decisions have already happened.

What if employee voice came in much earlier?

Employees could help identify where AI would genuinely make work better. They could explore potential unintended consequences, test proposed solutions and help organisations understand where human interaction or judgement remains particularly important.

That doesn't mean every technology decision needs to become an organisation-wide consultation exercise. But human-centred design reminds us of something incredibly simple: if we're designing something that will affect people, understanding their needs and involving them in the process usually leads to better decisions.

AI shouldn't be an exception.

EX can help organisations ask better questions about AI

There are already plenty of people thinking about the technical, legal and governance questions surrounding workplace AI.

EX professionals bring something different to that conversation.

We can ask what the technology will feel like from the employee's perspective. We can explore where it removes friction and where it might create it. We can help organisations understand what employees value about an existing experience before deciding which parts to automate.

And perhaps most importantly, we can challenge the assumption that successful AI adoption is simply about getting more people to use more AI.

A high adoption rate tells us very little about whether technology has actually improved someone's experience of work.

The more useful questions might be whether people understand how AI is being used, whether they feel able to challenge it, whether it has made work easier or more meaningful and whether they trust the organisation making decisions about its use.

Perhaps trust is the next measure of AI maturity

The first stage of workplace AI has understandably been dominated by experimentation. Organisations have been discovering what's possible, employees have been building confidence and everyone has been learning as they go.

The next stage may require something more considered.

As AI moves from being a tool employees choose to use towards something embedded in the systems and decisions around them, the quality of the employee experience will increasingly depend on how those choices are made.

That gives EX professionals an important role.

Not because we need to become AI experts or understand every technical detail, but because we already have many of the skills organisations need: listening, research, human-centred design, journey thinking, co-creation and an understanding of what makes experiences feel fair and human.

Perhaps the next big AI question for EX isn't simply, "How can we use this technology?"

It's, "How do we make sure people can trust the way we're using it?"

And that feels like a conversation EX should be right at the heart of.