A comparison with the rules-based alternative: Before approval | AIGP
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A comparison with the rules-based alternative: Before approval, which evidence is most relevant?

AIGP Understanding How to Govern AI Development Medium

Comparing AI with a feasible rules-based queue determines whether the proposed use provides sufficient contextual value.

The question

An insurer proposes an AI tool to prioritize routine claims. The operations team has not shown that prioritization solves a material problem better than a rules-based queue, although the AI vendor promises future scalability. Before approval, which evidence is most relevant?

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  1. A broader list of possible insurance applications.
    Additional use cases do not resolve whether AI is justified for the specific proposed prioritization workflow.
  2. A comparison with the rules-based alternative. ✓
    Comparative evidence tests whether the AI offers material benefits over a feasible non-AI alternative for the stated purpose.
  3. A demonstration using synthetic claims.
    A demonstration may illustrate functionality but does not establish comparative value or whether synthetic data reflects operational risks.
  4. The vendor’s projected future scalability.
    Projected scalability does not show that AI is necessary or preferable for the current claims-prioritization problem.
The trap
Compare the proposed AI use with a realistic alternative for the same purpose, users, and decision context.

How to remember it

Comparing AI with a feasible rules-based queue determines whether the proposed use provides sufficient contextual value.

How many of these would you get right?

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