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Yes, AI can be involved in a performance review in very different ways. A manager might use it only to polish wording after deciding what to say, or a system might summarize employee records, generate an assessment, rank workers, or recommend promotions. The practical question is not just whether AI was used, but what information it processed and whether its output changed a decision about your work or career.
What does it mean for AI to be used in a performance review?
“AI wrote my review” can describe anything from a spell-check-like edit to an AI-generated evaluation. Algorithmic management is broader still: the European Commission’s Joint Research Centre (JRC) defines it as “the use of computer-programmed procedures to coordinate labour input in an organisation.” Such systems may use AI, but algorithmic management does not necessarily involve AI.
| System role | What it might do | Why the distinction matters |
|---|---|---|
| Language editing | Rephrase or tidy a manager’s completed assessment. | The manager has already made the evaluation; the tool may affect presentation without changing the judgment. |
| Record summarization | Condense work records or attendance information for a manager. | A summary can shape what the manager notices, even if the tool does not issue a rating. |
| Evaluation or ranking | Generate a rating, compare employees, or score performance. | The system is directly assessing workers, and the output may influence career prospects. |
| Promotion recommendation or decision | Recommend who should advance, or help make that decision. | The system’s role is tied to an employment outcome rather than just the wording of a review. |
These are practical distinctions, not a universal legal checklist. The European Commission AI Act Service Desk’s examples distinguish supportive editing after a manager has completed an evaluation from systems that influence employment decisions. It also gives the example of a preparatory attendance-reporting system that makes no evaluation or recommendation.
How common is AI-written review text or AI-supported promotion?
There is no representative, cross-industry prevalence estimate established here for how many employers use generative AI to draft performance reviews or AI systems to recommend promotions. Broad workplace-AI figures do not answer those narrower questions.
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The JRC reported in 2025 that one third of EU workers said they used AI for work-related purposes. Its AIM-WORK survey was conducted across EU Member States in 2024–2025; the figure covers work-related AI use generally, not AI-written reviews or AI-assisted promotion decisions. The JRC also describes algorithmic management as covering areas such as work organization, performance assessment, and rewards or penalties, whether or not AI is involved.
A European Commission study of algorithmic management published on 28 March 2025 has a temporal scope through September 2023. It can help explain established forms of workplace management, but it should not be read as a current survey of generative-AI review practices.
How could AI affect a rating or promotion?
A tool can influence an outcome without making the final decision. A manager may rely on an AI-produced summary, rating, or shortlist, or may treat a recommendation as persuasive even when they retain formal authority. Conversely, a tool that only edits language after a manager has decided what the review should say may have a much narrower role.
The OECD identifies several ways bias can enter: historical training data may carry forward past disparities; records may be incomplete or unrepresentative; and design choices determine which variables and measures count as performance. A system could also support more consistent assessments if it is well designed and implemented. But consistency alone does not show that the measures are valid or that outcomes are fair. The OECD notes that more empirical research is needed to establish how perceptions of these systems compare with company outcomes.
For example, a system that sees only recorded output may miss mentoring, collaboration, difficult assignments, or work whose quality is not captured by a simple metric. Whether that happens depends on the data and design; it is a risk to examine, not proof that a particular employer’s tool is biased.
What can you ask your employer?
If you want to understand AI’s role in your review or a promotion process, ask specific questions about the tool’s function, information, and influence. These are practical questions to clarify what happened; this article does not establish a universal right to receive a particular answer.
- What did the tool do? Did it edit wording, summarize records, generate a rating, rank employees, recommend promotion, or make a decision?
- What information did it use? Ask whether the assessment relied on performance records, attendance, targets, communications, or other data, and whether relevant work could be missing.
- How much weight did the output carry? Did a manager independently assess the case, review the underlying information, and have the ability to reject the output?
- How can you correct an error? Ask how to point out inaccurate records, missing context, or an assessment that does not reflect your work, and who reviews a challenge.
- Is there an audit or review process? Ask how the employer checks for errors or unequal outcomes and whether the process applies to the specific tool and decision.
If a review seems inaccurate, keep a copy of the review and relevant work records, then respond with concrete corrections and examples. Ask for the manager’s reasoning and the process for having disputed information considered. Keep the discussion focused on identifiable errors, missing evidence, and the way the AI output affected the human decision.
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European Union
Regulation (EU) 2024/1689, the EU AI Act, identifies certain AI systems used in employment as high-risk. Recital 57 specifically refers to systems used for decisions affecting work-related relationships, promotion, task allocation based on individual characteristics, and monitoring or evaluation of workers. It explains that these uses may appreciably affect future career prospects, livelihoods, and workers’ rights.
That does not mean every AI writing assistant used at work is automatically a high-risk system. The system’s actual function and influence matter: supportive editing after a manager has completed an evaluation is different from a system that evaluates workers or influences promotion decisions. The examples from the AI Act Service Desk illustrate that distinction; they are not a complete account of every legal classification or obligation.
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Singapore
In a November 2024 parliamentary response about automated employment decision tools in hiring or promotion, Singapore’s Ministry of Manpower said the government would monitor trends and assess whether existing guidelines and regulations remained adequate. That was a dated policy statement, not a universal rule or a complete description of employee rights in Singapore today.
Employment rules depend on where you work and on what the system actually does. The EU and Singapore examples should not be treated as a summary of rights in every jurisdiction.
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