AI Agent Examples:
15 Real-World Use Cases

An AI agent reads every incoming support ticket, categorises it by urgency and topic, and routes it to the right team member — with a suggested response draft attached.

Handles customer queries in 12+ languages without needing native speakers on staff. Detects the customer's language, responds naturally, and escalates complex issues to a human with a full translation of the conversation.

Monitors customer behaviour patterns — declining logins, missed renewals, negative sentiment in emails — and triggers personalised retention outreach before the customer leaves.

Engages website visitors in real time, asks qualifying questions, scores leads based on your ideal customer profile, and books meetings directly into your sales team's calendars.

Continuously scans competitor websites, social media, review sites, and press releases. Flags pricing changes, new features, and positioning shifts with a daily summary.

Generates unique email content for each prospect based on their company, role, recent activity, and industry. Not templates with mail merge — genuinely personalised outreach.

Reads incoming invoices (PDF, email, paper scans), extracts line items, validates against purchase orders, codes to the correct nominal accounts, and queues for approval.

Reviews every expense claim against company policy — checking receipt validity, spending limits, duplicate claims, and unusual patterns. Flags violations before approval.

Analyses historical payment patterns, current invoices outstanding, and seasonal trends to predict cash flow 30, 60, and 90 days ahead. Alerts when potential shortfalls are detected.

Reads applications, scores them against the job specification, identifies standout candidates, and generates a shortlist with reasoning. Removes bias by focusing on skills and experience rather than demographic signals.

Coordinates the entire onboarding process — sending welcome packs, scheduling introductions, provisioning system access, assigning training modules, and checking in at day 7, 30, and 90.

Answers employee questions about policies, benefits, leave entitlement, and procedures by searching the company handbook and HR documents. Escalates ambiguous queries to HR.

Watches server metrics, application logs, and network traffic. Detects anomalies before they cause outages, runs basic troubleshooting scripts, and pages the on-call engineer with diagnosis notes.

Reviews pull requests for bugs, security vulnerabilities, style inconsistencies, and performance issues. Provides specific, actionable feedback — not generic suggestions.

Analyses codebases, APIs, and internal systems, then generates and maintains up-to-date documentation. Flags when code changes make existing docs outdated.