AI Agent Examples: By Business Function (2026)

An inbound lead arrives. The agent reads the email, scrapes the company website and LinkedIn, scores the lead against an ICP rubric (industry, company size, role seniority, intent signals), and posts the score and supporting evidence to the CRM. A human SDR sees the qualified lead with reasoning attached, not a raw inbox entry.

Given a list of 500 prospects, the agent drafts a personalised email per prospect by reading their company news, product launches, and public posts, then composing a one-paragraph note that references something specific. The human SDR reviews and sends.

Before a Monday pipeline meeting, the agent compiles a deal-by-deal digest from CRM, calendar, Slack, and email. Each open deal gets a one-paragraph status with risk flags (last contact date, missed follow-ups, competitive mentions in email).

A new ticket arrives. The agent searches the knowledge base, drafts a reply if confidence is high, and hands off to a human if the answer is not in the corpus or if the user signals frustration. Handoff conditions are explicit: refund requests, account deletions, and any mention of legal or regulatory issues route to a human immediately.

Incoming tickets are classified by category and urgency, assigned to the correct queue, and tagged with relevant context (customer tier, recent product changes, related historical tickets). A human supervisor sees a pre-organised queue rather than a raw stream.

When customer questions repeatedly hit the deflection bot but no good answer exists, the agent flags the gap, drafts a candidate KB article based on the eventual human response, and posts it for review. Closes the loop between support and documentation.

A new vendor request arrives. The agent reads the request, checks the procurement policy, runs the vendor through the standard due-diligence checklist (credit, sanctions, security questionnaire), and produces a procurement-ready packet for the buyer to review. Routes to legal if anything in the questionnaire raises a flag.

A new hire is created in the HRIS. The agent provisions accounts in IT systems, schedules first-week meetings, sends the welcome packet, assigns the onboarding buddy, and creates the 30-60-90 day checklist. Each step is a tool call to the relevant system.

Every quarter, the agent re-runs the security and financial checks for each active vendor, flags vendors whose status has materially changed, and produces a renewal recommendation. The human procurement lead sees the exceptions, not the routine.

Pull requests are reviewed by an agent before a human looks. The agent flags style violations, missing tests, obvious bugs, security concerns (hardcoded credentials, SQL injection patterns), and proposes fixes. Concrete failure modes: false positives on idiomatic code, missing nuanced bugs, hallucinated test coverage claims.

Incoming bug reports are deduplicated against existing issues, classified by severity, and routed to the right team. The agent reads logs, checks the relevant code, and writes a one-paragraph triage summary.

When an alert fires, the agent reads the alert, queries the relevant monitoring systems, runs the standard diagnostic playbook, and writes a one-line summary to the on-call channel. The on-call engineer arrives at a triage already done rather than a raw alert.

Reported phishing emails are analysed by an agent that reads headers, scans the URL reputation, checks the body against known phishing patterns, and either dismisses the report (with reasoning) or escalates to the security team with a structured summary.

Security alerts from EDR, SIEM, and cloud platforms are clustered and deduplicated. The agent groups related alerts, identifies the underlying incident, and surfaces a single tracked incident rather than a stream of alerts.

New CVEs are matched against the running asset inventory, scored for actual exposure (asset reachability, sensitivity, mitigations in place), and ranked. The security team sees a prioritised remediation queue.

Vendor invoices are matched to purchase orders and goods-receipt records. Discrepancies are flagged with the specific line items in question. The AP clerk sees exceptions, not raw matches.

Expense reports are reviewed against policy. Out-of-policy items are flagged with the specific policy reference. Approvers receive pre-screened reports.

Cash positions across bank accounts are reconciled daily. Material variances trigger an exception report. The treasurer reviews exceptions rather than the full reconciliation.