The biggest mistake in adopting AI is starting with a «big and ambitious» project. Such attempts often eat money and time while the result stays unclear. The right path is to start with a small, measurable, fast-paying step.
Step 1: pick one pain point
Apply AI not «in general» but to one specific problem. A good candidate is work that repeats often, eats a lot of time or produces many errors: answering customer questions, entering documents, sorting through chats.
Step 2: prepare the data
AI works only at the level of the data it's given. So your product list, Q&A or internal guide must be in order. Chaotic data means a chaotic answer.
Step 3: test and measure
- Test on a small scale (one channel, one department)
- Set a clear metric: time saved, reply speed, fewer errors
- Compare the result against a real number
- If it works — expand; if not — stop quickly
Step 4: human oversight
AI isn't autonomous — it's an assistant. At first let a person check every important answer, and increase automation as trust grows. This lowers risk and builds confidence in the team.
We work precisely by the «start small, measure, expand» principle — the first result shows quickly, and then AI spreads to other parts of your business.