There is a lot of noise about AI in the back office, and not all of it is useful. The honest answer is that AI helps enormously in some places and barely at all in others. Knowing the difference is what separates a return on investment from an expensive pilot.
The tasks where AI earns its keep
The strongest candidates share a profile — they are high-volume, rules-heavy and bound up in documents:
- Document extraction. Pulling structured data out of invoices, statements, contracts and clinical records is a natural fit. The work is repetitive, the formats vary, and humans are slow at it.
- Exception triage. When 95% of items follow the rules, AI can clear the routine and route only the genuine exceptions to a person.
- Summarisation at volume. Condensing large document sets into the few facts that matter saves real review time.
The tasks where it does not
Equally important is knowing where to not spend. Low-volume, high-judgement, relationship-driven work rarely benefits from automation — and forcing it there usually adds fragility, not speed.
Start narrow, prove it, then widen
The most successful automation programmes we see start with one painful, well-bounded process, prove the value with hard numbers, and only then expand. Big-bang transformations look impressive in a deck and disappoint in practice.
Our AI & Automation practice is built around exactly this discipline — find the high-leverage process, automate it well, and measure the result.