AI has the potential to reshape performance management, but only if it makes the experience simpler for employees and managers. That was the clear message from Bruce Walcroft, Director of Solutions Engineering at Betterworks, in conversation with UC Today at HR Tech Europe 2026.
UC Today’s time at HR Tech Europe showed that AI was one of the dominant themes across HR conversations, with vendors and buyers focused on how to bring it into everyday workflows. But interviews like this make one point especially clear: AI alone is not enough. The real test is implementation and whether these tools remove friction or simply move complexity elsewhere.
In performance management, that distinction matters. If AI adds another layer of process, another prompt, or another system to learn, it risks becoming part of the problem rather than the solution.
The Problem with AI-Enabled Performance Management
Walcroft’s central argument is that many organizations still expect AI to fit neatly into the way they already work. That, he suggested, is a mistake:
“The enterprise vendors generally underestimate the amount of thought that they have to put into what they’re trying to achieve.”
That goes to the heart of why so many transformation projects stall. Companies often take old processes and place them inside new software, expecting better results. But as Walcroft noted, “you’re not going to get any different outcome” if the process itself is unchanged.
That is especially true in performance management, where the gap between strategy, goals, feedback, and reviews is often wide. Employees are expected to define goals, managers are expected to review performance, and HR teams are expected to keep the whole system aligned. If AI is layered onto that structure without rethinking the workflow, it can make the experience harder to navigate.
Walcroft’s comments also point to a wider market issue: a lot of AI innovation is largely interface decoration. The product may look smarter, but if employees still need to understand complicated workflows or figure out how to use the tool, adoption will lag.
Why Complexity Kills Adoption
Part of the challenge is that employees are often asked to use AI tools without being shown how to use them properly. Walcroft said, “You’ve got to write a prompt,” but for many people, that is not intuitive. That is a serious issue in performance management, where users are often not power users and may not be confident with the underlying process to begin with.
His point was that AI should reduce the burden on users, not shift it onto them. The best systems, in his view, work almost invisibly in the background. “AI is a great label for impressing people,” he said, but the better approach is to make it feel simple, with “a button they press that does the work behind the scenes.”
That is an important distinction for HR technology buyers. Employees are unlikely to embrace AI because it is novel. They will embrace it if it helps them complete tasks faster, with less effort and more confidence.
Walcroft also highlighted where AI can add practical value: supporting people who are outside their usual comfort zone, such as writing a performance review in a second language or summarizing a large volume of feedback.
What Betterworks Believes AI Should Do
For Betterworks, the answer is not to use AI as a standalone feature but as a copilot embedded across the performance process. Walcroft said the company sees AI as something that helps refine work already started by the user, rather than replacing human input altogether.
That philosophy shows up in the examples he gave. AI can help employees draft better goals by pulling together context such as job descriptions, business strategy, prior feedback, and completed goals. It can help managers summarize dozens of feedback points into something usable. It can also support people who are not experts in performance writing by offering structure and clarity when they need it most.
This is where the difference between novelty and utility becomes clear. A good AI-powered performance tool does not simply generate text. It helps align work with strategy, gives people a stronger starting point, and saves managers from being overwhelmed by information.
That also explains why Walcroft stressed change management so strongly. Betterworks reportedly treats implementation as 20% technology and 80% change management. That reflects a reality many vendors overlook: even the best software fails if the organization is not prepared to use it differently.
The Future of Performance Reviews
In that model, the manager’s role changes. Rather than carrying the full administrative burden of the review, the manager becomes more of a validator and guide. The heavy lifting happens over time, making the end-of-year review a lighter, more accurate checkpoint rather than a once-a-year exercise.
That is where performance management appears to be heading over the next few years: less episodic, more continuous, and more embedded in the flow of work. But the key lesson from Walcroft’s comments is that technology alone will not get organizations there.
AI can transform performance management, but only if it is designed to reduce complexity rather than repackage it. That is the real story here.
