"AI agent" has become a buzzword, so it helps to be precise. An agent is a language model that can do more than chat: it can look things up, call your tools and take actions, such as booking a meeting or updating a record.
That's powerful, and it's also where the risk comes from. Here's where we've seen agents work well, and where we still keep a person in charge.
Where agents work well today
- Answering repeat customer questions about orders, timings, prices and policies, using your real data.
- Qualifying leads by asking a few structured questions and routing serious buyers to sales.
- Booking and rescheduling against a real calendar.
- Reading documents and pulling out fields, with validation.
- Internal Q&A over SOPs and policies, with links to the source.
- Drafting follow-ups, summaries and replies for a person to approve.
Where to keep a human in the loop
- Anything that moves money: refunds, payments, credit decisions. Let the agent prepare; let a person approve.
- Legal, medical or financial advice. Agents can find information; they shouldn't be the final word.
- Angry or sensitive conversations. A good agent recognises these and hands over quickly.
- Rare edge cases the agent has never seen. Build a clear "I don't know, let me get someone" path.
How to tell if an agent is ready to launch
- Test it on a few hundred real past conversations, not made-up ones.
- Measure how often it answers correctly, hands over correctly, and gets something wrong.
- Read the failures. If any would embarrass you or cost money, fix those before launch.
- Launch to a slice of traffic first, and review conversations weekly.
The real benefit
The best agents don't replace your team. They take the 60–70% of conversations that are routine, answer them instantly at any hour, and hand your people the ones that genuinely need them, with the context already gathered.