Key takeaways
- AI is useful for categorising transactions, extracting data from documents, drafting commentary and spotting anomalies, with a person reviewing the result.
- It does not replace reconciliation, judgement on accounting policy or your CPA's work on tax and year end.
- Financial data is confidential, so where it is sent, who can see it and how it is stored are decided before any tool is switched on.
- Measure the time saved and the errors caught, and switch off anything that does not earn its place.
Every accounting platform and a growing number of standalone tools now offer AI features for bookkeeping and reporting. Some save real time. Some create confident errors that are harder to catch than the manual ones they replaced. The difference is not the technology, it is how it is deployed and who checks the output.
Ali's team has built automation for companies since MyAutomation.ca in 2020 and advises on AI through SAZ. This is how we introduce AI into a finance function in a growing BC company without putting the books or the data at risk.
Where AI helps today
Transaction categorisation is the clearest win. Tools learn from past coding and propose accounts and tracking categories for new bank and card transactions, which turns the bookkeeper's job from entry into review. Document extraction is the second: supplier bills, receipts and remittance advices are read and turned into draft entries. Anomaly detection is the third: duplicated bills, unusual amounts, a supplier whose banking details changed, a customer whose payment pattern broke.
Reporting is the fourth. Drafting the monthly commentary from the variance report, summarising the aging for the weekly pack, answering a plain language question about last quarter's spending. The draft is a starting point for a person, not a finished product.
In each case the tool proposes and a person decides.
Where it does not belong
Reconciliation is a control, and controls are performed by people. A tool can prepare the match, and a person confirms it. Accounting policy, such as how revenue is recognised, how inventory is valued or what is capitalised, is decided with your CPA and applied consistently, not inferred by a model. Tax filings, year end statements and anything that carries a professional's signature are the CPA's work. Payments should never be released on an automated recommendation alone.
Anything that touches an external party, such as a collection email or a supplier query, is reviewed by a person before it leaves.
Decide the data rules first
Before any AI feature is enabled, answer four questions. What data does the tool receive, and does it include customer, employee or banking details. Where is that data processed and stored, and is that acceptable for a Canadian company under its privacy obligations, which your lawyer can confirm. Who in the company can access the tool and its outputs. Is the data used to train models outside your company. Write the answers down and make them part of the vendor file.
Prefer features built into your accounting platform or offered by established vendors with clear Canadian or contractual data commitments over pasting ledgers into general-purpose tools.
Keep a list of every tool that touches financial data, what it receives and who approved it. Finance teams accumulate tools quickly, and a year later nobody remembers which one has access to the bank feed. Review the list quarterly and remove anything that is no longer used. Access that is not needed is risk without benefit.
Build the review into the process
- Every automated categorisation is reviewed before the month is closed, with a sample checked line by line and all large or unusual items checked individually
- Extracted bills are matched to purchase orders or approvals before payment
- Anomaly alerts go to a named person with a deadline to resolve
- Drafted commentary is edited and signed by the finance lead
- A monthly log records what the tools did, what was corrected and how long it took
Measure whether it earns its place
Track two numbers for each feature: hours saved per month and errors caught or introduced. A categorisation tool that saves a day a month and introduces a handful of mistakes caught in review is a good trade. One that requires more review time than it saves is switched off. Revisit the measurements quarterly, because the tools change quickly and so does the business.
A sensible order of adoption
Start with bank feed categorisation inside your accounting platform, with review. Add bill extraction once the supplier list and approval flow are tidy. Add anomaly alerts once the ledger is reliably reconciled, so the alerts are not drowned in noise. Add report drafting last, when the chart of accounts and the dashboard are stable enough that the drafts are describing the right numbers. Each step depends on the previous one being clean.