What is the difference between AI-assisted testing and agentic/autonomous testing, and how do you decide which to adopt?

AI-assisted testing (current mainstream): AI tools in the developer loop — generating test code, reviewing PRs, triaging failures. The output is a deterministic, human-reviewed artefact that runs reliably in CI. The AI accelerates human work; the human owns the result.

Agentic testing (emerging): an AI agent runs the test autonomously at test time — planning, clicking, asserting — without a pre-written script. There is no fixed artefact to review; the agent decides what to do based on the current page state.

Decision criteria for agentic adoption: Change frequency: if the UI changes every sprint and maintaining scripts costs more than agent runs cost, agentic may be cost-effective. Determinism requirement: if the test must produce the same result every run (payment flow, compliance check), use a scripted test. Agentic is non-deterministic by design. Speed and cost: agentic tests are 5–30× slower and cost per LLM call. Not suitable for fast PR pipelines. Purpose: agentic excels at exploration and broad coverage sweeps; scripted tests are better for regression of known critical paths.

See Agentic testing landscape and Agent cost and latency.