How Do You Evaluate Work Done With AI? 4 Changes to Performance Reviews in 2026
A report arrives fast and polished, and the manager hesitates: did the employee think this through, or did AI write it? A survey of 1,701 directors and senior managers in seven countries, conducted by Nielsen for monday.com and published in October, found that 53% find it harder to evaluate an employee's original work since adopting AI, and 78% have changed how they evaluate their teams. A separate August survey by Highwire found that 78% of managers used AI to prepare feedback or a review in the past year, yet only 16% of employees said they were told. AI makes work faster, and it makes AI performance reviews harder to get right. Here are four changes managers and business owners should make.
Change 1: AI Performance Reviews Should Judge Decisions, Not Just Deliverables
When every deliverable looks tidy, the deliverable alone stops being the best basis for a rating. TechCrunch's coverage of the monday.com survey notes that managers are giving more weight to other skills: how people prompt, which tasks they hand to AI and how they experiment with new ways of working.
In practice, it can be simple:
- Ask employees to walk through the process: which parts of this proposal used AI, which calls were their own, and why they chose this direction over another.
- Look at what they caught: when AI produced a wrong number or the wrong tone, did they notice and fix it?
- Measure outcomes, not output: whether the client replied or the project launched on time matters more than page count.
If you want measurable indicators for your team or your AI agents, see Everyone Uses AI Agents, but Only a Quarter Measure Results.
Change 2: Set Clear AI Rules, and Make Disclosure Two-Way
When employees can't tell how their manager views AI, they stay quiet. A healthier approach is to write the rules down: which work can use AI, which data must never go into it, and whether AI use should be noted. We covered how in Employees Are Already Using AI: Give Shadow AI a Proper Path.
Disclosure should go both ways. In Highwire's survey, 40% of employees suspected their manager used AI without being able to confirm it, or weren't sure. If a manager uses AI to help structure a review, saying so upfront builds more trust than being found out.
Change 3: Three Lines Managers Shouldn't Cross When Using AI for Reviews
AI can help managers write more specific feedback. In Highwire's survey, 54% of employees said feedback became more specific and actionable, but 34% said it became more generic and 32% less useful. Separately, a July survey by The Predictive Index found that 44% of managers admitted entering employee names or performance details into public AI tools.
When managers use AI for reviews, they should hold at least three lines:
- Keep identifiable employee data out of public AI tools: use a company-approved environment where data stays in.
- Let AI organize material, not reach conclusions: ratings and anything tied to pay or promotion are human decisions. TechCrunch also cites research warning that AI models can carry biases against certain groups.
- Write the final paragraph in your own words: what employees care about most is whether their manager actually saw their effort.
Change 4: Count the Work of Supervising AI
AI speeds up output but adds invisible work: giving AI enough context, checking its output and fixing mistakes. In the monday.com survey, 47% of managers say they spend more time reviewing and guiding team output, and 58% expect to manage more AI agents than people within a year.
If reviews only count how many things were delivered, the people who take time to verify AI output look slower. Consider writing these into your criteria:
- A record of catching and correcting AI errors.
- Turning a useful AI workflow into a method the whole team can reuse.
- Deciding when something should not be handed to AI.
Conclusion: AI Produces, People Judge and Earn Trust
In the AI era, performance reviews shift from "how much did you do" to "how good was your judgment" and "can we trust your work." AI delivers perfection; people make it moving. In the same way, AI can help organize review material, but seeing someone grow is still the manager's job. If you want to set AI rules and build internal tools for your team, take a look at TitApeX's services or get in touch.
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