AI in Testing interview questions — Medium
448 medium-level AI in Testing questions from our Automation Testing bank, each with the correct answer and an explanation of why it is correct.
What this covers
AI in Testing appears throughout Automation Testing interviews. At medium level, interviewers are typically checking that you have used it in practice: what you configured, what broke, and how you knew it worked. Work through these, then explain your answer out loud; the second part is what interviews actually test.
20 example questions
1. Which of the following statements about AI in Testing is TRUE?
- A. AI-generated tests are always correct and never need review.
- B. AI has fully replaced the need for QA engineers in all organizations.
- C. Synthetic test data must always be copied from production customer records.
- D. Risk-based test selection with ML prioritizes tests most likely to catch regressions in a change.correct
Why: Predictive selection runs fewer tests with similar defect detection.
2. "Workflow where people review and approve AI output" — in AI in Testing, this describes which of the following?
- A. Synthetic data.
- B. Test impact analysis.
- C. Human-in-the-loop.correct
- D. Self-healing locator.
Why: human-in-the-loop: Workflow where people review and approve AI output.
3. "Selecting tests affected by a specific code change" — in AI in Testing, this describes which of the following?
- A. Self-healing locator.
- B. Test impact analysis.correct
- C. Visual AI.
- D. MCP (Model Context Protocol).
Why: test impact analysis: Selecting tests affected by a specific code change.
4. "Large language model used to generate or review test artifacts" — in AI in Testing, this describes which of the following?
- A. Self-healing locator.
- B. Autonomous test agent.
- C. Test impact analysis.
- D. LLM.correct
Why: LLM: Large language model used to generate or review test artifacts.
5. "Open protocol connecting AI models to tools such as a Playwright browser" — in AI in Testing, this describes which of the following?
- A. MCP (Model Context Protocol).correct
- B. LLM.
- C. Failure clustering.
- D. Self-healing locator.
Why: MCP (Model Context Protocol): Open protocol connecting AI models to tools such as a Playwright browser.
6. "Grouping similar test failures to speed up triage" — in AI in Testing, this describes which of the following?
- A. Test impact analysis.
- B. MCP (Model Context Protocol).
- C. Autonomous test agent.
- D. Failure clustering.correct
Why: failure clustering: Grouping similar test failures to speed up triage.
7. "Artificially generated data that mimics production characteristics" — in AI in Testing, this describes which of the following?
- A. LLM.
- B. Hallucination risk.
- C. Synthetic data.correct
- D. Test impact analysis.
Why: synthetic data: Artificially generated data that mimics production characteristics.
8. "Tendency of generative AI to produce plausible but incorrect output" — in AI in Testing, this describes which of the following?
- A. Hallucination risk.correct
- B. MCP (Model Context Protocol).
- C. Test impact analysis.
- D. Failure clustering.
Why: hallucination risk: Tendency of generative AI to produce plausible but incorrect output.
9. "AI system that plans and executes testing toward a goal" — in AI in Testing, this describes which of the following?
- A. Autonomous test agent.correct
- B. Synthetic data.
- C. Hallucination risk.
- D. Test impact analysis.
Why: autonomous test agent: AI system that plans and executes testing toward a goal.
10. "Mechanism that repairs broken element selectors using alternative attributes" — in AI in Testing, this describes which of the following?
- A. Failure clustering.
- B. Test impact analysis.
- C. Self-healing locator.correct
- D. Visual AI.
Why: self-healing locator: Mechanism that repairs broken element selectors using alternative attributes.
11. "ML-based comparison of UI screenshots tolerant to noise" — in AI in Testing, this describes which of the following?
- A. Test impact analysis.
- B. Visual AI.correct
- C. Failure clustering.
- D. Autonomous test agent.
Why: visual AI: ML-based comparison of UI screenshots tolerant to noise.
12. Which statement correctly describes AI in Testing?
- A. Agentic QA means a human writes and maintains every test script line by line.
- B. AI visual testing flags every single pixel difference as a failure by design.
- C. Risk-based test selection with ML prioritizes tests most likely to catch regressions in a change.correct
- D. AI has fully replaced the need for QA engineers in all organizations.
Why: Predictive selection runs fewer tests with similar defect detection.
13. Identify the accurate statement about AI in Testing:
- A. Playwright MCP works by sending raw screenshots and asking the model to guess pixel coordinates.
- B. Machine learning cannot be used to prioritize which tests to run.
- C. AI-generated tests are always correct and never need review.
- D. Flaky-test detection tools can use historical run data to quarantine unstable tests automatically.correct
Why: Statistical models flag tests whose outcomes vary without code changes.
14. In AI in Testing, which of the following is described as: "Artificially generated data that mimics production characteristics"?
- A. Autonomous test agent.
- B. Synthetic data.correct
- C. Failure clustering.
- D. Visual AI.
Why: synthetic data: Artificially generated data that mimics production characteristics.
15. Which AI in Testing concept matches this description: "AI system that plans and executes testing toward a goal"?
- A. Autonomous test agent.correct
- B. Synthetic data.
- C. LLM.
- D. Human-in-the-loop.
Why: autonomous test agent: AI system that plans and executes testing toward a goal.
16. Which AI in Testing concept matches this description: "Selecting tests affected by a specific code change"?
- A. Failure clustering.
- B. MCP (Model Context Protocol).
- C. Autonomous test agent.
- D. Test impact analysis.correct
Why: test impact analysis: Selecting tests affected by a specific code change.
17. In the context of AI in Testing, which of the following is a correct statement?
- A. Self-healing locators eliminate the need for any human review of test results.
- B. Machine learning cannot be used to prioritize which tests to run.
- C. AI has fully replaced the need for QA engineers in all organizations.
- D. Prompting an LLM with the DOM or accessibility tree yields more reliable element targeting than screenshots alone.correct
Why: Structured snapshots beat pixel-guessing for AI-driven interaction.
18. Which AI in Testing concept matches this description: "Artificially generated data that mimics production characteristics"?
- A. Failure clustering.
- B. Hallucination risk.
- C. Synthetic data.correct
- D. LLM.
Why: synthetic data: Artificially generated data that mimics production characteristics.
19. Which AI in Testing concept matches this description: "Tendency of generative AI to produce plausible but incorrect output"?
- A. LLM.
- B. Human-in-the-loop.
- C. Synthetic data.
- D. Hallucination risk.correct
Why: hallucination risk: Tendency of generative AI to produce plausible but incorrect output.
20. In AI in Testing, which of the following is described as: "Tendency of generative AI to produce plausible but incorrect output"?
- A. MCP (Model Context Protocol).
- B. Synthetic data.
- C. LLM.
- D. Hallucination risk.correct
Why: hallucination risk: Tendency of generative AI to produce plausible but incorrect output.