Identify practical AI use cases, readiness gaps, risks, and responsible-use guardrails tied to mission execution and impact work.
Each engagement includes a focused set of deliverables designed to create clarity, structure, and practical next steps.
Assesses whether goals, data, workflows, governance, and reporting needs are clear enough to support useful AI adoption.
A nonprofit wants AI to help summarize impact stories and draft reporting language, but participant data includes sensitive information. The review identifies what must be clarified before AI is introduced safely.
Identifies practical AI opportunities tied to impact work, reporting, operations, and decision support.
Possible use cases include summarizing program notes, drafting first-pass board report narratives, identifying themes in impact stories, or helping staff prepare grant reporting summaries.
Defines responsible-use considerations, data sensitivity issues, approval needs, and adoption risks.
The organization agrees that participant names, donor details, financial information, and sensitive case notes should not be entered into public AI tools. Approved use cases and review expectations are documented.
Reviews how current tools support or block impact tracking, reporting, and decision visibility.
The CRM tracks donors, spreadsheets track program activity, grant files track funder requirements, and reports are created manually. The review clarifies what should stay where and how the systems should support a clearer reporting flow.
Prioritizes next steps, sequencing, and the practical implementation path.
- First 30 days: confirm reporting needs and ownership.
- Next 60 days: structure goals, programs, grants, KPIs, and workflows.
- Next 90 days: implement Track Impact Now, adoption routines, and reporting review cadence.