AI can help research teams move faster, but speed needs a clear quality system. A shared checklist helps the team decide where AI is useful, where human review is required, and what evidence must be retained.
What to check every time
- Can the sources behind the AI output be traced?
- Does the output fit the research question and methodology?
- Is a human accountable for interpretation and final decisions?
- Are prompts, inputs, outputs, and edits retained for audit?
How Thai teams can apply it
Start with a low-risk workflow such as literature screening or document summarization. Define review points before expanding AI into higher-risk work. A good checklist should live inside the team's real tools, not become another document burden.
Caution
Do not use AI to replace methodological judgment, and do not send personal or sensitive data into systems that have not been risk-assessed.