Using AI in finance: speed with a safety net
AI tools can draft, summarise, classify and reconcile at a speed that changes how a finance team works. They can also produce confident errors, and they can expose confidential data if they are used carelessly. The answer is not to avoid them but to use them inside controls.
Good first use cases
- Summarising long notices, orders, agreements and circulars, with the source alongside.
- Drafting first versions of routine letters, replies and board notes for a person to edit.
- Classifying bank transactions and expenses, and flagging unusual entries for review.
- Matching invoices across purchase registers and GST data.
- Writing spreadsheet formulas and small scripts, which are then tested.
Where to be careful
- Calculations and legal positions: AI tools can quote sections, rates or case law incorrectly. Check every figure and citation against the source.
- Confidential and personal data: client information is confidential under professional and contractual duties, and personal data is protected under the Digital Personal Data Protection Act, 2023. Do not paste it into public tools. Use business versions that do not train on your data, and remove names and identifiers where possible.
- Final outputs: returns, financial statements, audit conclusions and replies to authorities must be reviewed and owned by a qualified person.
A one-page AI-use policy
- Approved tools, and the account types that may be used.
- Data that may never be entered (client identifiers, PAN, Aadhaar, bank details, unpublished financial results).
- Tasks where AI may be used, and tasks where it may not.
- Review requirements: who checks the output and how this is recorded.
- Training, and a named person who answers questions.
See our AI consultancy page.