Your next performance review may already have AI fingerprints on it. New research shows that nearly half of companies in the US and UK are now using artificial intelligence to evaluate how well employees perform their jobs. Most workers sitting in those review meetings have absolutely no idea it is happening.
Raises, promotions, and job security are all directly tied to performance reviews. The stakes could not be any higher.
What the New Survey Actually Found
General Assembly, a leading tech and AI training firm, surveyed more than 500 senior leaders across the US and UK. The headline number is hard to look away from. Forty-seven percent of those leaders said they are already factoring AI usage into employee performance evaluations.
The broader findings add even more context. A full 93 percent of those leaders said they encourage AI use at work, while 82 percent reported using AI tools themselves on a regular basis.
The expansion has moved well beyond just writing review templates or summarizing notes. HR professionals are now using AI tools to analyze employee feedback, run talent assessments, and generate performance reports that feed directly into formal evaluation processes.
Nearly half of senior leaders are now using AI as a measuring stick for employees, yet most workers have never been told this is happening.
Key Numbers You Need to Know
- 47% of senior leaders factor AI usage into performance evaluations
- 93% of leaders encourage employees to use AI at work
- 82% of leaders use AI tools
- them
- selves
- regularly
- Only 30% of HR professionals have received job-specific AI training
- 92% of CHROs expect AI to be further integrated into their workforce this year
Why Employees Have Every Right to Be Worried
Daniele Grassi, CEO of General Assembly, flagged a fundamental flaw in how most companies are handling this shift. He pointed out that leaders are far more likely to measure how much employees use AI than whether that usage actually delivered better results or improved business outcomes.
When AI use becomes a metric in itself, workers quickly learn to appear productive with AI rather than genuinely become more effective with it.
HR consultant Bryan Driscoll was far more direct in his assessment. He argued that the same executives who admit in this survey they do not fully understand AI are the ones using it as a yardstick to measure everyone else in the organization.
The concerns workers and independent experts raise fall into three clear categories:
- Algorithmic bias: AI systems trained on flawed or historical data can replicate and even amplify discrimination at a scale no single manager ever could. Research in 2026 has already flagged troubling disparate impact patterns in AI tools used across employment decisions.
- Lack of transparency: Many AI systems operate as black boxes. Employees may never know what data shaped their evaluation, what weight each factor carried, or why they received a specific score.
- Over-reliance on automation: When managers defer their judgment entirely to AI output, the human context behind an employee’s performance can get erased. Team dynamics, personal circumstances, and growth over time can all disappear from the picture.
The legal risks are real and accelerating. A wave of recent lawsuits in the US has alleged that AI tools used in employment decisions disproportionately harmed workers from certain groups. Legal experts are clear on one point: employers are fully liable for discriminatory outcomes, even when an algorithm made the call.
States are already moving. California has extended its civil rights protections to cover AI tools used in employment evaluations. Colorado’s AI Act is set to take full effect by June 2026, requiring formal impact assessments for high-risk systems. New York City already mandates independent bias audits before any automated employment decision tool can be deployed.
The Case Companies Are Making for AI Reviews
The picture is not entirely one-sided. When implemented thoughtfully and transparently, AI does offer real advantages that traditional review processes cannot easily replicate.
AI can analyze performance signals across a full year rather than relying on the last few weeks before review season. That directly addresses one of the most stubborn flaws in traditional performance management: recency bias, where only recent events shape the final score.
A study published in SSRN found that employees from underrepresented minority groups actually responded more positively to negative feedback when evaluations were AI-assisted, compared to traditional human manager reviews. The perception of objectivity matters to workers who have faced inconsistent or subjective treatment in the past.
A 2026 Resume Now survey found that 67 percent of employees said they are more likely to accept a job at a company that uses AI in pay decisions, showing that workers see real fairness potential in these tools when they are used transparently and responsibly.
What Has to Change Before This Goes Too Far
Training is the most critical gap right now. General Assembly’s own research found that only 30 percent of HR professionals have received job-specific AI training. These are the exact people deploying AI tools to evaluate entire workforces.
The SHRM 2026 CHRO Priorities report found that 92 percent of chief human resources officers expect AI to be further integrated into the workforce this year, with 87 percent forecasting greater adoption within HR processes specifically. That is a massive wave of expansion with a very thin layer of training underneath it.
Gallup’s February 2026 survey of more than 23,000 US employees found that 27 percent of workers at AI-adopting organizations said their workplace had changed in disruptive ways. That disruption carries very real costs in morale, trust, and retention. And a separate report found that 44 percent of US workers either have no clear AI policy at their company or have no idea whether one exists.
| Responsible AI Use in Reviews | Irresponsible AI Use in Reviews |
|---|---|
| Measuring AI’s impact on actual outcomes | Measuring how often employees use AI tools |
| Transparent disclosure to employees | Using AI in evaluations without informing workers |
| Regular third-party bias audits | Deploying AI tools with no audit process |
| HR teams trained on AI tools they use | Rolling out AI-driven reviews with zero training |
| Human manager as final decision-maker | Letting AI output determine review scores automatically |
Driscoll’s warning cuts to the core of what is at risk here. When employees do not know how they are being measured, they disengage. If they have the option to leave, many of them will. Short-term cost savings from AI-driven reviews can very quickly be swallowed by higher turnover, eroded trust, and in the worst cases, expensive discrimination lawsuits that follow companies for years.
The technology is already here, it is already being used, and it is already shaping careers without most workers realizing it. Whether that becomes a story of smarter, fairer workplaces or a cautionary tale of unchecked automation depends almost entirely on what companies choose to do next, and how fast they choose to do it. Workers deserve to know what is grading them. The companies that earn trust by being transparent about it will be the ones people actually want to work for. Share your thoughts below: do you think AI should have a role in your performance review?
