# Evidence note: AI in grant administration

Last checked: **19 August 2026**. [Version française](nonprofit-grantmaking-ai-cases.fr.md).

This note bounds the synthetic
[A2 grant-dossier case](../examples/en/nonprofit-grant-dossier-business-agent.md).
It separates administrative handling from a decision that affects access to
funding.

## Useful anchors

- In Candid's [2025 survey](https://candid.org/blogs/will-foundations-soon-use-ai-to-screen-grant-applications/),
  1% of 529 responding foundations reported using generative AI to screen
  applications or assist decisions. Summaries and administrative tasks were
  described as more acceptable uses. This measures reported practice, not
  productivity.
- [Degrees of Change](https://learn.microsoft.com/power-platform/guidance/case-studies/nonprofit)
  uses a central system to handle more than 1,000 applications and support 150
  volunteer reviewers. Staff review extracted information and matching
  recommendations. The supplier case gives a useful workflow analogue, not a
  causal time estimate.
- The [National Zakat Foundation case](https://www.microsoft.com/en/customers/story/23068-national-zakat-foundation-microsoft-copilot-studio)
  reports an 80% reduction in disbursement delay after several data,
  automation, and agent changes. Treat it as a high scenario, not a forecast.
- Swiss [FDPIC guidance](https://www.edoeb.admin.ch/en/duty-to-provide-information)
  explains the information and human-review rights that can apply to fully
  automated individual decisions.

The worked case therefore lets the agent check a published checklist, prepare
a packet, and perform writes after approval. It does not score merit,
vulnerability, or success probability. A high productivity scenario can still
be explored for a standard digital sub-flow, while offline, ambiguous,
sensitive, and new-program cases stay visible in the whole-workload denominator.

For a real pilot, measure active human time, corrections, escalation, critical
errors, complaints, appeals, reversed decisions, access by channel and group,
and the downstream outcome. A nominal human review is not enough unless that
person has the evidence, time, competence, and authority to disagree.