The one-sentence definition
An AI agent is software that uses an AI model to take in information, make decisions and act in other systems. It can repeat that process until it reaches a defined goal.
"Agent" refers to the autonomy and action. "AI" refers to the language model, such as Claude or GPT-4.5, that handles the reasoning.
How AI agents differ from chatbots
A chatbot replies to messages. You ask a question, it gives an answer, and the exchange continues. It does not normally change anything in your systems.
An AI agent can act. Depending on the permissions and tools you give it, the agent can:
- Read emails and decide which need an urgent reply
- Search the web and summarise what it finds
- Query a database and produce a report
- Send messages on your behalf
- Update CRM records
- Call external APIs
A chatbot can tell you what to do. An agent can carry out the action.
How agents actually work
Most AI agents follow a five-step loop:
- Perceive: receive a message, scheduled trigger or webhook
- Think: send that input to an AI model with the available context and tools
- Act: select and call the appropriate tool
- Observe: receive the result of the tool call
- Repeat: use the new information to choose the next step until the goal is met
A single model call produces one response. A multi-step agent can research a subject, write a summary, format a report and send it by email after one instruction.
Real examples we have built
Customer support agent
The agent receives a support ticket, checks the customer's order history and status in the e-commerce platform, then decides whether it can resolve the issue. It might issue a refund, arrange a reshipment or provide an update. If the case needs a person, the agent routes it with the relevant context already written.
Deal origination agent
The agent receives a batch of company profiles. It researches revenue, sector and recent news for each company, scores the opportunity against the fund's investment criteria and returns a prioritised list with its reasoning.
Lead research agent
The agent starts with a list of target companies. It finds decision makers, LinkedIn profiles and recent company news, drafts personalised outreach for each contact, saves the information to the CRM and queues the messages for sending.
The tools an agent can use
An agent can only act through the tools connected to it. Common examples include:
- Web search for current information
- Database queries that read from or write to SQL and NoSQL databases
- API calls to systems such as a CRM, email platform, Slack or Stripe
- File operations that read, write or parse documents
- Python or JavaScript execution for calculations
- Memory that stores and retrieves information across sessions
The design work lies in giving the agent the smallest useful set of tools and clear instructions about when each one is appropriate.
When should you use an AI agent?
Use an agent when the task has several decision points, depends on changing information, requires action in another system or repeats at high volume.
Do not use one when a deterministic, rules-based automation can handle the job. Agents add cost and complexity. They are also a poor choice when mistakes carry a high cost and the accuracy requirement is very high, or when the task is a one-off question that only needs an answer.
The state of agents in 2026
Over the past 18 months, agents have moved from research projects into production use. Three developments made that possible:
- Reasoning models such as Claude Sonnet 4.5, GPT-4.5 and Gemini 2.5 can follow more complex instructions reliably
- Model providers now offer structured tool-calling APIs
- Platforms such as n8n make agent workflows practical to deploy without deep engineering resources
We now deploy agents that complete thousands of tasks per day with little human oversight. Their reliability is sufficient for many business processes, provided the workflow has sensible controls and exception handling.
Over the next 12 months, production agents are likely to become standard operating infrastructure. Businesses deploying them now will build an operational advantage while others are still testing isolated tools.
To assess where an AI agent would genuinely help your business, book a 30 minute discovery call. We will map the process and tell you whether an agent or a simpler automation is the better fit.