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AI Tool Selection Scorecard

Score AI tools against the work you actually need done, your data rules and the review effort they create.

Decision: [Which workflow needs a tool?] • Owner: [ ] • Review date: [ ]

Pass/fail prerequisites

Check these before comparing convenience or price:

  • Approved for the data and account being used.
  • Access controls match who should see the inputs and results.
  • Required source access and export are available on the proposed plan.
  • The team can inspect, correct, and retain the output.
  • Total spending can be bounded and monitored.
  • A person can maintain the resulting workflow or code.

Compare two candidates on the same task

Task and representative inputs: [ ]
Expected useful output: [ ]
Difficult input: [missing data, conflict, error, or edge case]

CriterionCandidate A evidenceCandidate B evidence
Correctness and completeness[ ][ ]
Source traceability[ ][ ]
Handling of uncertainty[ ][ ]
Total preparation + review effort[ ][ ]
Team fit and accessibility[ ][ ]
Export and portability[ ][ ]
Cost under expected and heavy use[ ][ ]
Failure recovery and support[ ][ ]

If numeric scores help, use a documented 1–5 rubric and task-specific weights. Do not let a weighted total override a failed prerequisite. Record evidence, not just a score.

Cost model

Monthly cost = seats + estimated usage + integration/hosting + review labor + maintenance allocation. State assumptions and avoid false precision.

Decision

Choose [tool / existing workflow / further test] because [evidence]. Revisit when [usage, cost, feature, or access condition changes]. Keep an export of the pilot artifacts and the official documentation links checked on [date].