Where AI helps, and where it does not
AI is strong at first drafts, summaries, sorting messages, pulling facts out of documents and answering common questions from your own material. It is weak where one wrong answer is costly, where facts change daily and are not in front of it, or where the task is not written down.
- Good fits: drafting replies, summarising calls, tagging enquiries, searching your own documents.
- Poor fits: legal or medical advice, final pricing, anything with no human check.
Check your data and privacy first
Find out what each tool does with what you give it: whether it stores it, whether it learns from it and where it is processed. Customer details, contracts and staff records need a clear rule before they go near a tool. Choose plans with business terms, and write down what staff may and may not paste in.
Run a pilot that tells you something
Pick one task, agree the measure first (time per task, error rate or customer response) and run it for a few weeks next to the current way. Keep a person checking the output. At the end, decide: stop, adjust or widen.
- One task, one team, one measure.
- Compare with the current way, not with nothing.
- Write down what went wrong as well as what worked.
Run a 45-minute readiness check
You need two or three people who know how the work really gets done.
- List ten tasks your team does with words, numbers or documents.
- For each, note how often it happens, how long it takes and how costly a mistake would be.
- Mark which involve customer or staff data. Those need a privacy rule before any tool.
- Pick the one with high volume, low risk and no private data. That is your pilot candidate.