AI agents are systems that use a language model to decide on and take actions toward a goal: reading data, calling tools and updating systems, with people stepping in where judgment or approval is needed. The examples below show where agents are doing real work in companies today, followed by five you can build yourself on your own data.
AI agent examples by department
Customer support
- Ticket triage agent: classifies urgency and topic, attaches order history and routes to the right queue.
- Resolution agent: answers common questions using your help center and account data, and handles simple actions like resending an invoice.
- Refund agent: checks eligibility against policy and issues small refunds; larger ones go to a person for approval.
Sales
- Lead research agent: enriches new leads with company data, scores fit and drafts a personalized first email for the rep.
- CRM hygiene agent: finds duplicates, missing fields and stale deals and suggests fixes.
Finance
- Invoice matching agent: extracts invoice data, matches it to POs and receipts, and flags exceptions.
- Expense review agent: checks receipts against policy and routes violations to managers.
- Collections agent: identifies overdue accounts and drafts reminders for approval.
HR and IT
- Onboarding agent: runs the new-hire checklist, creating accounts, ordering equipment and scheduling meetings.
- Access request agent: checks requests against role policies, routes approvals and provisions access.
Operations
- Inventory agent: watches stock levels, forecasts shortfalls and drafts purchase orders.
- Order exception agent: finds stuck or failed orders, diagnoses the cause and fixes or escalates.
What successful agents have in common
- One clear job with a measurable outcome.
- Direct access to the systems of record, not a stale copy.
- Scoped permissions: only the rows and actions the job needs.
- Human approval on actions that are expensive or irreversible.
- A review interface where people see and correct agent work.
- Logs of every action for debugging and audit.
5 AI agents you can build yourself
1. Support triage agent
Trigger: new ticket. Tools: read ticket, read customer and orders, set priority and queue. Guardrail: read-only on customer data. Measure: routing accuracy and first-response time.
2. Lead enrichment and routing agent
Trigger: new lead in the CRM. Tools: company lookup, update lead fields, assign owner, draft email. Guardrail: emails saved as drafts, never sent automatically. Measure: time to first touch.
3. Invoice exception agent
Trigger: invoice uploaded. Tools: extract fields, look up PO and receipts, set match status. Guardrail: cannot mark invoices payable; finance approves. Measure: share of invoices auto-matched.
4. Weekly ops report agent
Trigger: every Monday. Tools: query orders, tickets and revenue; write a summary with anomalies. Guardrail: read-only. Measure: hours saved on reporting.
5. Stuck order agent
Trigger: hourly. Tools: find orders stuck in a status too long, check payment and shipping, retry or open a ticket. Guardrail: retries limited; refunds require approval. Measure: orders resolved without manual work.
For a step-by-step guide, see how to build an AI agent.
Build these agents with Jet Admin
Jet Admin lets you build agents like these on your own data across 200+ integrations, including PostgreSQL, Snowflake, Salesforce, HubSpot, Stripe, Zendesk and Slack, querying data in place. Agents run inside the same permission model as your apps, workflows add approval steps before sensitive actions, and you can build the review queue or dashboard your team uses to check agent work next to the agent itself. Granular permissions, SSO and audit logs are on Business and above. See also AI agents vs chatbots.
Frequently asked questions
What are some examples of AI agents?
Support triage agents, lead research agents, invoice matching agents, onboarding agents, inventory agents and access request agents are common examples in business.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions in conversation. An AI agent takes actions in other systems to complete a task.
Which AI agent should I build first?
A read-mostly agent with a clear job and high volume, such as ticket triage or a weekly report, is a low-risk place to start.
Do AI agents replace employees?
Mostly they take over repetitive steps, so people spend more time on exceptions, decisions and customers.
Put an agent to work this month
Start with Jet Admin for free and build your first agent on your own data.