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Nonprofit Solutions AIMission-first AI field lab

Start with one decision

Do the work that makes an AI experiment understandable.

The sequence is intentionally small. Keep the current human process available until the evidence and accountable owners support a different decision.

01

Frame the mission question

Name the person, program, decision, or operating burden that could improve. Describe the current workflow and what dignity, access, trust, quality, and accountability must remain true.

02

Map information and authority

Write allowed and prohibited information, account and service boundaries, human decision authority, mandatory review, escalation, and the non-AI fallback before comparing features.

03

Prepare representative cases

Use safe synthetic, public, or approved minimum information. Include normal, difficult, ambiguous, incomplete, accessibility, multilingual, and stop-path cases with a review rubric.

04

Run the smallest useful pilot

Compare the full current and proposed workflow, including preparation, prompting, review, correction, documentation, escalation, support, and the result people receive.

05

Decide from evidence

At the written gate date, choose stop, revise, continue at the same scope, or scale under a separately reviewed operating plan. Record the owner and rationale.

06

Keep change and exit visible

Set retest triggers for provider, model, plan, data, population, consequence, integration, policy, and owner changes. Keep a usable path to suspend, remove access, clean up, notify, and fall back.

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Monthly field guidance for mission fit, data boundaries, human review, and bounded AI pilots.
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