Customer-facing AI gets the attention. Back-office automation is where the measurable return usually is — the work is repetitive, the rules are writable, and a mistake costs a correction rather than a customer.
Scoring your own processes
Rate each candidate one to five. Anything scoring above 18 is worth costing properly.
| Criterion | Score 5 if… | Score 1 if… |
|---|---|---|
| Volume | Many times daily | A few times monthly |
| Rule clarity | You could write the rules down today | It depends on judgement |
| Input structure | Consistent format every time | Free-form and varied |
| Verifiability | Correct output is checkable by code | Only an expert can tell |
| Current cost | Consumes significant staff hours | Minor time cost |
| Failure cost | A mistake is easily corrected | A mistake is expensive or public |
Pay particular attention to the last row. Your first automation should be somewhere a mistake is cheap. You are building organisational confidence as much as software, and an early visible failure in a high-stakes process sets the whole programme back further than a slow start would.
Seven processes that reliably score well
1. Document extraction and filing
Invoices, purchase orders, delivery notes, forms arriving as PDFs and needing their contents entered somewhere. High volume, structured output, machine-verifiable, and a mistake is a correction.
Design note: confidence scoring per field, with anything low-confidence routed for human review. Do not aim for full automation on day one.
2. Reconciliation across systems
Matching payments to invoices, stock counts to records, bookings to bank entries. Rule-based, tedious, and error-prone when done manually under time pressure.
3. Recurring report compilation
The weekly report someone assembles from three systems every Monday morning. Purely mechanical, and a strong first project because the current cost is easy to measure precisely.
4. Enquiry triage and routing
Reading incoming messages, classifying them, extracting key details, routing to the right team with context attached. Works after hours, which is where much of the value sits.
5. Supplier and vendor communication
Chasing order confirmations, following up on late deliveries, requesting documentation. Repetitive, rule-describable, and currently consuming someone's afternoon.
6. Onboarding sequences
New customer or employee onboarding involves many small steps across several systems, each simple, collectively substantial, and easy to do inconsistently.
7. Data enrichment and hygiene
Filling gaps in records, standardising formats, flagging duplicates and inconsistencies. Continuous background work nobody has time for.
Notice what these have in common: none of them are exciting, all of them are currently done by people who would rather be doing something else, and every one produces output a machine can check.
The 80/20 design principle
Do not try to automate the exceptions. Handle the routine majority automatically, detect anything unusual, and route it to a person with context attached. Systems designed to handle everything end up handling nothing reliably — and the exceptions are exactly where judgement is required.
Practically, that means:
- Confidence thresholds — below a level, escalate rather than proceed.
- Explicit exception categories — known unusual cases routed by rule.
- Clean handoff — the human receives the work with everything the system found.
- Learning loop — exceptions reviewed periodically; recurring ones become new rules.
Fix the process before automating it
Automating a broken process produces broken output faster. Before building:
- Write the process down, including the exceptions people actually handle.
- Confirm with the people doing it — the documented process and the real one usually differ.
- Remove steps that exist only from habit. Some processes shrink substantially at this stage.
- Decide who owns exceptions once the routine cases are automated.
- Measure the current state — hours, error rate, turnaround — so you can prove the change.
Calculating return honestly
| Input | Example |
|---|---|
| Hours per month on the task | 60 |
| Fully-loaded hourly cost | Your finance figure |
| Share automatable (routine cases) | 75% |
| Hours actually saved | 45 |
| Build cost | Vendor quote, itemised |
| Annual running cost | Model API plus maintenance |
| Add: error reduction value | Quantify if you can |
If payback exceeds roughly two years on hours alone, look for a better candidate process rather than trying to justify this one.
A sequence that builds confidence
- Pick one process with a high score and low failure cost.
- Measure the current state precisely.
- Build for the routine cases, with human review on everything initially.
- Run in parallel with the manual process briefly, comparing outputs.
- Reduce review on categories the logs show are reliable.
- Measure again, then use the proven result to justify the next process.
Have processes consuming hours that look automatable? Describe the workflow and its volume — we will score it honestly, including saying if it is not a good candidate. See our agentic AI service, agentic vs chatbot, and document processing.