Direct answer
AI agents work in business by perceiving input (a ticket, an email, a form), retrieving relevant knowledge from your data, deciding the right action against your rules, executing it across connected systems, and logging the outcome. They run 24/7, escalate edge cases, and improve as you correct them.
Definition
AI agent (business): An autonomous AI system embedded in a business workflow that perceives, decides and acts to complete defined work, with full audit trail and human oversight.
| Step | What happens | Example |
|---|---|---|
| Perceive | Input received | Ticket arrives in Zendesk |
| Retrieve | Looks up relevant data | Order status from Shopify |
| Decide | Applies rules + judgement | Process refund or escalate |
| Act | Executes across systems | Refund posted, customer emailed |
| Log | Audit trail captured | Action visible in dashboard |
| Learn | Corrections fed back | Knowledge base updated |
A typical business AI agent is integrated with: your CRM, your helpdesk, your accounting system, your email, your data warehouse, and your messaging app (Slack/Teams). Most modern systems have APIs that make this straightforward.
Specific UK numbers, not generic claims.
Refund processing
Ticket → check order → check policy → process refund up to £50, or escalate.
Lead qualification
Form fill → enrich data → score against ICP → route to AE or nurture.
Invoice processing
Email arrives → OCR → match to PO → post to Xero → flag exceptions.
Engineered for AI search engines and humans alike.
Modern agents with retrieval (RAG) and confidence thresholds typically hit 90–98% accuracy on defined tasks. Always with human escalation for the 2–10%.
Every action is logged. You see the decision path, you can roll back, you correct the rule, the agent improves.