Performance reviews are already loaded moments. They carry the weight of past achievements, missed opportunities, and hopes for the future. For many managers and employees, adding AI into the mix feels like one complication too many. Is it fair? Is it safe? Does it even belong here?
The truth is, whether you’ve officially adopted it or not, AI has already found its way into performance management. Managers are using tools like Microsoft Copilot and ChatGPT to polish feedback. Employees are running their self-assessments through AI to make them sharper.
The question isn’t should AI be used in performance management? It’s how do we use it responsibly, fairly, and legally?
Why Ignoring It Isn’t an Option
Some leaders assume that by banning AI they’re keeping their processes safe. But pretending it isn’t happening doesn’t reduce the risk - it increases it. If managers are already leaning on AI to draft feedback, or if employees are quietly polishing their reviews with AI tools, you’re operating in a shadow system with no visibility or guardrails.
And the risks are real. AI can easily amplify bias if not monitored closely. A “black box” algorithm that spits out ratings without explanation won’t stand up to scrutiny, especially with new laws like the EU AI Act and guidance from regulators such as the EEOC in the US. In Australia, early frameworks are already in motion. Just as importantly, employees lose trust quickly if they suspect AI is assessing them in secret.
Why Banning It Isn’t the Answer
The temptation to simply say “no AI in performance reviews” is understandable - but unrealistic. People will use it anyway, whether it’s managers looking for help with wording or employees asking a chatbot to rewrite their goals.
The smarter approach is to accept that AI has a role to play and decide what that role should be. That means using AI to support insight, not replace judgment. It means keeping accountability with people, not machines. And it means being transparent about when and how AI is being used.
The Opportunity in Getting It Right
Handled well, AI can make reviews better. Not colder, not more robotic - better. It can help managers prepare specific examples from 121s or other conversations instead of relying on what they can remember from the last couple of months. It can flag when feedback language might reflect unconscious bias. It can lighten the admin load by turning meeting notes into themes, so managers spend less time writing and more time listening. Anyone who still runs an annual cycle knows how disruptive the process can be!
That’s exactly why we’ve built new features into GoFIGR:
- AI-enabled prep support so managers and employees never walk into a review unprepared.
- Conversation insights over time that surface risks, themes, or even problematic language - while keeping humans firmly in control.
- Guardrails designed for HR leaders who want the benefits of AI without the blind risks.
The goal isn’t to replace human conversations. It’s to make things clearer, fairer, and more useful for everyone.
So, Does AI Belong in Performance Reviews?
The truth is, it’s already there. The real choice is whether to let it happen quietly, with all the risks that brings, or to bring it into the open with clarity, accountability, and support.
For leaders still on the fence, there’s no need to jump headfirst into AI. Start by getting the basics right - a well-structured review process, clear goals, and better conversations. That’s the foundation AI can build on.
📥 Download our free Performance Review Toolkit to get practical prep sheets, templates, and conversation starters. Once you’ve nailed the fundamentals, you’ll be ready to see how AI can take the load off and help you run performance conversations that actually work.
Helena Turpin spent 20 years in talent and HR innovation where she solved people-related problems using data and technology. She left corporate life to create GoFIGR where she helps mid-sized organizations to develop and retain their people by connecting employee skills and aspirations to internal opportunities like projects, mentorship and learning.
