Public institutions handle high volumes of text, forms and records, and staff who are already stretched. That makes them a natural fit for AI assistance, and a place where careless AI does real damage. The difference lies in what the AI is allowed to decide.
Good fits
- Summarising long records so a supervisor can decide where to look.
- Triage: sorting incoming requests by type and urgency, with a person confirming.
- Drafting routine correspondence for a clerk to review and send.
- Translation and transliteration between Marathi, Hindi and English, checked by a speaker.
- Flagging unusual patterns in logs for a human to investigate.
Poor fits
- Automated decisions that affect a person’s rights, benefits or liberty.
- Opaque scores nobody can explain or contest.
- Anything that sends sensitive records to a third-party service outside the institution’s control.
Principles that keep it safe
- A named person is accountable for every outcome. AI proposes, people decide.
- Every output shows its sources, so the underlying record is one click away.
- Inputs and outputs are logged, so the system can be audited later.
- Data stays under the institution’s control; privacy is decided before the model is.
- Accuracy is measured on the institution’s own data and languages, not on a vendor’s benchmark.
- There is always a manual path when the AI is wrong or unavailable.