AI for accountants in Ireland: realistic uses in a practice today

Coding is where most practices see the first gain. Software that learns how a client codes recurring suppliers can suggest the account and VAT rate for each bank line, so the bookkeeper confirms rather than types. The value comes from consistency across months, not from any single suggestion.

The largest time saving is in coding bank transactions to accounts and Irish VAT rates. AI learns each client’s suppliers and proposes the treatment, leaving staff to confirm and handle exceptions. For clients with steady, repetitive activity, most lines need only a glance. The practice’s skill moves from typing to spotting what looks wrong.

Document reading turns a photographed receipt or a supplier PDF into structured data: supplier, date, net, VAT and total. The reviewer still checks that the VAT number and rate make sense, especially on mixed-rate invoices, but the keying is gone.

Bills and receipts arrive as photos, PDFs and email attachments. AI reads the supplier, date, amounts and VAT into fields and attaches the image to the transaction. That ends the manual keying of purchase invoices and leaves a document trail that makes VAT reviews and Revenue queries straightforward.

Matching payments to invoices and drafting a list of unreconciled items, missing receipts and possible accruals are pattern-based tasks AI handles well. A staff member who used to spend a day closing a client’s month can review a draft close and resolve the exceptions in an hour or two.

Some work needs a qualified person, whatever the software claims.

• Borderline VAT treatment, mixed supplies and reverse-charge construction work.
• Year-end adjustments, provisions and valuations.
• Tax planning and advice.
• Anything the client has not done before.
• The final sign-off on every return.

The main risks are confident errors, client data leaving the practice’s control, and staff trusting suggestions they should question. Each has a practical control: review thresholds, clear data processing terms with any vendor, and a habit of sampling automated work every month.

Ask every AI vendor whether anything posts without human confirmation, whether you can see why the AI proposed a posting, how client data is protected and whether it trains shared models. Treat accuracy figures that are not independently audited as marketing. Document how the practice reviews AI output, so your quality control covers it.

If AI removes much of the entry work, hourly billing for bookkeeping becomes harder to defend. Many practices are moving to fixed monthly packages that include bookkeeping review, VAT returns and year end, priced on value rather than hours. The margin improves when the routine work shrinks and the fee reflects the outcome.

Pick one repetitive task, such as bank coding for ten clients with simple books, and measure the time before and after for two or three months. A measured result is easier to roll out across the practice than general enthusiasm for AI.

Pick five clients with simple, repetitive books and run them on AI-assisted software for two VAT periods. Measure hours, corrections and review time against your current process. The results, not a vendor’s claims, should decide whether to roll it out further.

HelloBooks is built as an AI accountant: it proposes accounts and Irish VAT treatment, reads documents, reconciles bank activity, drafts the month-end close and computes VAT3 figures, with nothing posted until a person confirms. Accountants manage client workspaces from one login at no extra cost. HelloBooks does not file to ROS or run Irish payroll.