AI Automation for Accountancy Firms

The single biggest time drain in most practices. An invoice arrives by email, someone downloads it, opens Xero, manually types the supplier, amount, line items, and VAT treatment, then files the original. Multiply by hundreds of invoices per month across multiple clients.

AI automation reads the invoice (PDF, photo, or email attachment), extracts the structured data using computer vision and language models, matches it against existing suppliers and nominal codes, and pushes it directly into Xero or QuickBooks. The accuracy rate on well-formatted invoices sits above 95%. Unusual formats or new suppliers get flagged for human review rather than guessed at. See the full workflow breakdown in our Invoice Processing use case guide.

The typical time saving for a 20-person practice processing 2,000+ invoices per month: 30-40 hours per month.

Staff and clients submit expenses in every format imaginable — photos of receipts, forwarded emails, CSV exports from corporate cards, scanned PDFs. Someone has to look at each one, categorise it, match it to the right client and nominal code, and flag anything unusual.

AI handles the initial triage. It reads the receipt, identifies the merchant, amount, date, and VAT, suggests the categorisation based on historical patterns for that client, and routes it for approval. Edge cases and policy exceptions surface for human review. Everything else flows through automatically.

This integrates with Dext, Receipt Bank, and direct bank feeds. The goal isn't to remove human oversight — it's to make the human step a 10-second approval rather than a 3-minute data entry task.

Bank reconciliation is pattern-heavy work. Most transactions in a given month follow patterns established in previous months — the same suppliers, the same recurring payments, the same client receipts. AI learns these patterns and suggests matches, flagging only the genuinely ambiguous transactions for human decision.

This doesn't replace the accountant's judgement. It pre-populates the reconciliation with high-confidence matches and surfaces the 10-15% of transactions that actually need attention, rather than making someone scroll through 100% of them.

Monthly or quarterly client reports follow a predictable structure — pull data from Xero, format it into a standard template, add commentary on variances, and send it. The data pull and formatting is pure automation territory. The commentary layer can be AI-assisted (generating first-draft variance explanations based on the numbers) with the accountant editing and approving.

Firms that automate client reporting typically reduce report production time from 2-3 hours per client to 20-30 minutes — mostly spent on the review and personalisation step. See how the full pipeline works in our Client Reporting Automation use case guide.

Client onboarding paperwork, engagement letter generation, deadline tracking, internal task assignment, team capacity monitoring — the operational glue that keeps a practice running but isn't billable work. Workflow automation handles the triggers (new client added → generate engagement letter → assign to team member → set review deadlines → send client portal invite) without anyone manually shepherding each step.