A baseline comparison measures a tool or change against a known reference, such as an existing process, a previous version, or a controlled test without the tool. It helps determine whether an observed result is actually an improvement rather than an assumption or marketing claim.
In cybersecurity, teams can compare an AI-assisted detection system with existing detection methods using the same data and measures, such as detection accuracy, false positives, response time, or analyst workload. A fair comparison accounts for test conditions and limitations. Baselines help defenders decide whether a tool improves security, introduces trade-offs, or needs further testing before deployment.