Where people search for, classify or summarise the same information every day, AI can be a powerful starting point. Choosing a model, however, comes after defining the problem.
Describe the flow first
Where does input come from? Who makes the decision? What happens when something goes wrong? Where must human approval stay? Choosing a model before answering these questions turns the system into a technology demo. Writing the workflow down step by step makes the best automation candidates visible.
The best first candidates
- Repetitive e-mail and request classification.
- Extracting decision summaries from long documents.
- Searching the internal knowledge base in natural language.
- Spotting anomalies in operations data early.
- Draft content and report generation that passes human approval.
How will we measure success?
Fewer manual steps, faster answers, fewer errors or better prioritisation — pick a measurable goal. “The model answers well” is not a business metric on its own. How many hours a support team saves per week, how waiting times change, and whether misrouted requests decrease are far more meaningful.
Where should the human stay?
In flows that act on behalf of finance, law, health, access rights or the customer, human approval is usually part of the system. Position AI as a decision supporter rather than a decision maker, and define where the human checkpoint stands.