When employers use AI tools to help decide who is selected for termination, the risk is not always an obviously flawed tool. The more practical risk is that the tool may appear objective while missing important context HR and leadership need before turning a recommendation into a final decision.
That is where the “rubber stamp” trap starts.
Most employers have heard the phrase “garbage in, garbage out” when discussing AI. But in this context, the issue is not always bad data. A tool may rely on information that is accurate, familiar, and business-relevant, yet still produce an incomplete result.
The practical takeaway is straightforward: AI-generated separation recommendations may be part of a review process. That review process is most meaningful when it tests a recommendation rather than simply approving it. Employers that rely on those recommendations without testing the inputs, outputs, and surrounding context may create avoidable risk, particularly if a neutral metric produces results that are difficult to explain or defend later.