AI decision checklist
2026年6月26日
Discover our AI research readiness decision checklist to help your team evaluate whether AI-assisted workflows can deliver value without compromising research integrity.
Use it to review evidence traceability, attribution and transparency, privacy and IP protection, human oversight and ongoing evaluation needs.
If you can confidently answer the checklist questions, you are better positioned to adopt AI with research-grade trust.
Use this checklist to assess whether AI is ready for your workflow.
1) Evidence quality
Are outputs grounded in trusted, curated evidence?
Are sources attributable and citable?
2) Verification and reproducibility
Can users verify context quickly through linked evidence?
Are limitations and uncertainty clearly communicated?
3) Governance and compliance
Are privacy and IP protections documented and enforceable?
Is neutrality and risk managed through governance?
4) Ongoing safety and evaluation
Is there continuous evaluation for accuracy, completeness and safety?
Is there a monitoring plan after deployment?
5) Human oversight
Is expert judgment clearly integrated into the workflow?
Are roles and accountability defined?
Decision: If you can confidently check these boxes, AI is more likely to deliver productivity gains without compromising research integrity.