For most SMEs, the best first AI projects are not the most “visible”. These are the feeds that monopolize attention each week, follow a recognizable pattern and create frustration because they are repetitive, slow or uneven.
Start from a painful process, not from an abstract innovation.
If a task comes up often, relies on recurring information and has a clear definition of “good result”, it is often a better candidate than rare or extremely complex work. Hence the interest in starting with support triage, lead qualification, research of internal procedures or repetitive administrative processing.
Choose cases with visible gain.
The first successes create confidence and internal momentum: fewer manual actions, faster responses, smoother handovers, shortened customer deadlines.
- Entry and qualification of requests
- Preparation of customer responses and reminders
- Consultation of internal procedures
- Document retrieval and control
- Routing to the right queue or person
Avoid over-designing the first project.
The first system must help the company learn: neither lock in a giant choice of platform nor impose a total overhaul of the operational model. Start with an understood process, measurable value and rapid adoption by the team.
Three useful layers.
1. Friction
What is slow, repetitive, or focused on too few people?
2. Feasibility
Is the task structured enough for AI or automation to reliably support it?
3. Leverage
Does improving this flow free up time, quality, service or consistency?
SMEs that are making good progress with AI generally don't start with everything at once: they start with one stream where the value is obvious, then expand to the adjacent one.