Chatbots answer questions. AI agents get things done. An agent can read, decide and act across your business tools - working through a multi-step task the way a capable assistant would.
What is an AI agent?
An AI agent is an AI model that has been given:
- A goal - for example "make sure every new enquiry gets a helpful reply and ends up in the CRM".
- Tools - access to specific systems such as your email, calendar, CRM or accounts package.
- Rules - what it may do on its own, and what needs a person's approval.
The leading models from OpenAI, Anthropic, Google and Microsoft are now reliable enough to use tools and work through tasks step by step, and a common standard called MCP (Model Context Protocol) makes it much easier to connect AI safely to everyday business software.
Examples for small businesses
Enquiry handling
Reads new enquiries from email or your website, answers common questions, asks for missing details, adds the lead to your CRM and books a call in your diary.
Invoices and receipts
Reads supplier invoices and receipts, checks them against purchase orders and enters them into Xero, QuickBooks or Sage for approval.
Credit control
Spots overdue invoices, sends polite personalised reminders, and flags customers who need a phone call from a person.
Quotes and proposals
Drafts a quote or proposal from a call summary or enquiry, using your price list and past proposals, ready for you to check and send.
Recruitment admin
Summarises CVs against the job requirements, arranges interviews and sends updates to candidates - with a person making every hiring decision.
Weekly reporting
Pulls figures from your systems every Monday, writes a plain-English summary of what changed and why, and emails it to the team.
Simple automation first
Not everything needs a full agent. Tools such as Zapier, Make, n8n and Microsoft Power Automate now include AI steps, so you can add "read this email and decide which team it's for" or "summarise this form" into an ordinary automated workflow. This is often the quickest, cheapest win - and we will always suggest the simplest thing that works.
Keeping agents safe and under control
An agent that can send emails or update records needs sensible safeguards. Every agent we build includes:
- Human in the loop - a person approves anything important (payments, emails to customers, deleting records) until you are confident to relax it.
- Least privilege - the agent only gets access to the systems and data it genuinely needs.
- Protection against prompt injection - content from outside (emails, websites, documents) is treated as information, never as instructions.
- A full log - you can see what the agent did and why.
- Spending limits - so AI usage costs can't run away.
How we build an agent
We follow our 5 Phases of AI Implementation: map how the task is done today, build a small pilot on real (or realistic) examples, measure the time saved and the error rate, then roll it out with training for the people who work alongside it.
Which job would you hand over first?
Tell us about the repetitive task that eats your week.
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