You have probably heard that “AI agents” will change how businesses work. Strip away the hype and the idea is simple: an AI agent is software that can decide what to do next and then do it using the tools you give it.
Chatbot vs AI agent
| Chatbot | AI agent | |
|---|---|---|
| Main job | Answer questions | Achieve a goal |
| Works with | Text conversations | Conversations plus your systems and tools |
| Example | “What is your refund policy?” | “Refund order #482” — checks the order, applies the policy, issues the refund request and replies |
| Needs | Good content | Good content, tool access and safety rules |
Read our guide to AI chatbots for business for the basics; agents build on the same ideas.
How an agent works
- Understands the request in everyday language.
- Plans the steps needed to complete it.
- Uses tools — searching your documents, checking an order system, updating a CRM, sending an email, booking a calendar slot.
- Checks the result and responds, or asks a human when unsure.
The “tools” are connected through APIs and are limited to exactly what you allow.
Practical business uses
- Customer support: answer from your documents, look up orders and escalate hard cases. See our AI support chatbot example.
- Sales assistant: chat with website visitors, score leads and book meetings. See the AI sales assistant example.
- Document assistant: search contracts, policies and manuals and answer with sources — see the document Q&A example.
- Marketing helper: draft product descriptions, ads and emails in your brand voice — see the AI writing tool example.
- Back-office automation: sort emails, extract data from invoices, update spreadsheets and systems.
What can go wrong (and how to prevent it)
| Risk | Safeguard |
|---|---|
| Wrong answers | Ground the agent in your documents and show sources |
| Unwanted actions | Give minimum permissions and require approval for sensitive steps |
| Data exposure | Limit what data it can see; choose providers with clear terms |
| Poor quality over time | Log conversations, review samples weekly and improve |
Many AI projects that disappoint do so because the underlying data is messy, so prepare your content first.
How to start
- Pick one task that is repetitive, well understood and low risk.
- Define success, for example “answer 50% of support questions without a human”.
- Connect only the tools needed and give read-only access first.
- Add a human hand-off for anything uncertain or sensitive.
- Pilot with a small group, review results and expand carefully.
Do you really need an agent?
If a fixed rule solves your problem, use simple automation. Use an agent when inputs are messy or varied — free-text requests, long documents or many possible paths.
Talk to us
We build custom AI assistants, chatbots and automation grounded in your data. Explore our AI and automation service or ask for a free quote.
