When companies ask us where to start with AI, they often arrive with a chatbot idea or an ambitious prediction model. Those can be worth building — but they’re rarely the quickest win. The biggest time savings tend to hide in repetitive, high-volume back-office work: the tasks people do dozens of times a day by copying information from one place to another.
1. Start with volume, not novelty
A simple test: list the tasks your team repeats more than 20 times a week. Note how long each one takes and how often mistakes slip through. Multiply volume by time. The top of that list is usually your best AI candidate — not the most impressive idea in the room.
2. Documents are the obvious first win
Invoices, receipts, contracts, onboarding forms and identity documents all follow the same pattern. Modern AI models can read them, pull out the fields you need and check them against your records.
The setup that works: AI extracts and validates, anything uncertain goes to a person, and confident matches flow straight into your accounting system or CRM. Good fits include accounts payable, customer onboarding and KYC, claims intake and contract review.
The best first AI project is boring, frequent and easy to check.
3. Routine questions, answered from your own policies
Support teams and internal helpdesks answer the same questions again and again. An assistant grounded in your own documentation can handle the routine ones and pass the rest to your team with the conversation already summarised.
The key word is grounded. Every answer should point to the policy or record it came from, so staff and customers can trust it — and so you can fix the source when something is wrong.
4. Triage and routing
Emails, tickets and requests often sit in a shared inbox until someone reads and forwards them. AI is good at classifying requests, pulling out key details and sending them to the right person or queue. Because a misrouted ticket is easy to correct, this is a low-risk place to build confidence.
Where AI isn’t the answer (yet)
- Decisions with legal or financial consequences and no human review.
- Processes that change every week, or that nobody has written down.
- Data scattered across personal spreadsheets — fix access first.
Sometimes a simple rule or a better integration solves the problem without AI at all. That’s a good outcome too.
How to pick your first use case
Score each candidate process against five questions:
If a process ticks four or five boxes, it’s a strong candidate for a four-to-six-week pilot.
Not sure where to start?
Our AI readiness workshop finds your best first use case in two weeks.