aiaim.org
For product teams defining measurable AI use cases before they choose a model or vendor.
Explore focused topics and check consequential details against original sources.
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For product teams defining measurable AI use cases before they choose a model or vendor.
Use-case framing
A focused way to check sources, conditions and next steps for use-case framing.
Explore topic →Outcome measuresA focused way to check sources, conditions and next steps for outcome measures.
Explore topic →Review cadenceA focused way to check sources, conditions and next steps for review cadence.
Explore topic →How to use this site
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Each section explains its scope. For costs, eligibility or deadlines, use the latest material from the responsible organisation.
About this siteGuides
Latest guides
- How can a review distinguish product drift from model behavior?A review can separate product-context changes from model-output changes while tracking unexpected and emerging AI risks, consistent with NIST guidance.
- How can a team connect an AI output to the product decision it supports?This guide explains how to link an AI output to a product decision through mapped context, user needs, an explicit action rule, and follow-up evidence.
- How can a team decide whether to continue, narrow, redesign, or stop a pilot?A pilot review should combine performance metrics with user research and test AI systems before deployment and regularly in operation before a team chooses to continue, narrow, redesign, or stop.
- How can a team preserve a decision history for model and vendor changes?A versioned decision record can preserve rationale, metric evidence, and risk tracking, with NIST advising that existing, unanticipated, and emergent AI risks be tracked regularly.
- How can a team review an AI use case without quietly changing the task?Defining service purpose before metrics and interpreting output in context helps teams detect when a proposed review has changed the task rather than evaluated it.
- How can teams measure adoption without treating usage as value?Teams can assess adoption with need-aligned performance metrics and user research, treating usage as a behavioral signal rather than proof of value.
The first guides are being prepared. No articles are published yet.