What does AI do in a forest products company's back office?

In most finance teams AI does two generic jobs: answering questions from company documents, and automating the handling of supplier invoices. A forest products back office has a third job, built around records a generic finance tool isn't designed for. They include scale tickets, haul rates, stumpage and levy schedules, settlement statements, and deductions for defect and trim. Matching those records to what was booked is where we would expect AI to find the larger amounts. No published source yet measures the return on that work, so this piece sets out why, and how to test it.

What the usual answer says

The top results for this question are generic workflow products and an article on office AI tools: writing assistants, image generators, step-by-step automation of approvals. That is a common place to start, and none of it is specific to timber.

What finance teams use AI for

Gartner surveyed 183 finance leaders in May and June 2025. As reported by CTMfile in November, it found 59% using AI in the finance function, against 58% in 2024 and 37% in 2023. The most common uses were knowledge management at 49%, payables automation at 37%, and anomaly detection at 34%. CTMfile adds that, according to the report, 91% of respondents initially see low or moderate benefits. CFO.com's account of the same survey says 16% of respondents had no AI plans for the coming year. Gartner's own release could not be opened, so these figures come from the two trade reports.

A newer Gartner survey, of 204 finance leaders in March 2026, reported by MarketScale, found that "Forty-five percent of finance AI investments lean toward productivity" and "Only 20% of projects lean toward decision quality". The report files "automated reconciliations, invoice processing, or report generation" under productivity. On that split, matching work sits with the efficiency uses, even where it finds money.

Where timber records sit

Payables tools match the documents a purchase creates. Microsoft's documentation for its ERP describes invoice matching as "the process of matching vendor invoice, purchase order, and product receipt information". A log or chip settlement adds records that are not part of that match: the scale ticket, the contract's rate table and the deduction schedule, which often sit in other systems or on paper. Where they do, a check that needs all of them stays manual even after payables has been automated.

Anomaly detection, the third use in Gartner's list, is the generic version of this work. The timber version is specific. Does every load on the scale appear on a settlement? Does every settlement line use the contract's rate? Does the accrual match what was later invoiced?

How to test the return

Because nobody has published the return on this work, a business has to measure its own. Take one month of settlements. Check every line's rate against the contract, every load against the scale record, and every accrual against the invoice that followed. Count the exceptions and add up their value. That total, set against the time the check took, is the case for automating it or not. Repeat it for a second month before deciding, because one month can be unusual.

Where to start

List the matches your back office depends on: loads to settlements, settlements to contract rates, accruals to invoices, haul to loads. For each, estimate how often it is checked by hand and how large the amounts are. Data readiness will also set the order. Where the records aren't yet digital or joined, the generic uses may be the practical first step, and the matching comes once the data is ready. Where they are, start where the amounts are largest and the checks least complete, and measure the result in money found or protected as well as hours saved.

When it doesn't apply

A forest products business that trades wood without handling scale records or settlements, such as a broker working from supplier invoices, has fewer timber-specific matches, and payables automation may be most of what it needs. A very small operation where one person checks every settlement by hand may find the checks are already complete. And where tickets and settlements are still on paper, reading them comes first.

Quarri for finance and strategy teams is built for the people who close the month, explain the margin and answer the board.

Quarri is an AI-native data platform for the timber supply chain. It connects buying, production, sales and inventory for forest management, sawmill, wood products and pulp, paper and packaging operators.