Traditional API testing often requires writing and constantly maintaining test cases, especially when APIs evolve frequently. This leads to flaky tests, higher maintenance costs, and slower release cycles.
AI-driven API testing tools can automatically capture API behavior, generate test cases from real traffic, and keep tests in sync as APIs change. This approach helps teams detect regressions early, improve test coverage, and reduce manual effort.

It would be great to discuss how teams are adopting automated and AI-based API testing approaches, what challenges they face, and what measurable impact they’ve seen on release velocity and reliability.

Reference: https://keploy.io/blog/community/what-is-api-testing