LAST UPDATED: FEBRUARY 7, 2026
Not theory. Not demos. Actual AI agents doing real work right now — handling customer support, writing code, closing sales, managing logistics, processing claims, and operating autonomously across industries. Here's what's working in production.
Every use case on this page represents agents operating in production environments — not prototypes, not research projects, not marketing promises. These agents handle real transactions, interact with real users, and operate with real autonomy.
The examples are organized by industry and function. Some are simple (answering FAQs). Some are complex (coordinating multi-step supply chains). All are deployed and working today.
AI agents now resolve 40–80% of customer support conversations without human intervention. They handle returns, track orders, troubleshoot issues, and escalate when necessary.
Agent monitors shipments, proactively notifies customers of delays, initiates refunds when carrier issues occur, and updates tracking information in real time.
Agent validates return eligibility, generates return labels, processes refunds, updates inventory systems, and sends confirmation emails without human approval.
Agent walks users through setup processes, diagnoses common issues, provides step-by-step fixes, and escalates to human support when problems require hands-on intervention.
Agent handles plan upgrades/downgrades, processes cancellations, applies promotional credits, and answers billing questions by querying payment systems directly.
Agent verifies user identity through multi-factor authentication, resets credentials, unlocks accounts, and logs security events for audit trails.
Agent answers common questions by pulling from knowledge bases, updates responses based on new documentation, and suggests when articles need revision.
Agents handle prospecting, lead qualification, outreach personalization, and campaign optimization — automating workflows that previously required entire teams.
Agent scores inbound leads based on firmographic data, engagement patterns, and intent signals. Routes high-value prospects to sales, nurtures others via email sequences.
Agent identifies target accounts, researches decision-makers, personalizes outreach based on company news/tech stack, sends emails, tracks engagement, follows up automatically.
Agent coordinates calendars across time zones, sends invites, handles rescheduling requests, sends reminders, and prepares meeting agendas based on email context.
Agent monitors ad performance across platforms, adjusts bids in real time, reallocates budget to winning creative, and pauses underperforming campaigns automatically.
Agent personalizes drip campaigns based on user behavior, A/B tests subject lines, adjusts send times for optimal open rates, removes unengaged contacts.
Agent monitors competitor pricing, product launches, job postings, and social media activity. Summarizes trends and alerts sales team to strategic changes.
Coding agents plan features, write across multiple files, run tests, debug errors, and create pull requests — operating more like junior engineers than autocomplete tools.
Agent reads requirements, plans architecture, creates files, writes code across frontend/backend, adds tests, runs build, creates PR with descriptive commit messages.
Agent analyzes error logs, reproduces bugs in test environment, identifies root cause, implements fix, verifies solution passes existing tests, deploys to staging.
Agent checks PRs for style violations, security vulnerabilities, performance issues, missing tests, and outdated dependencies. Suggests improvements with code examples.
Agent reads codebase, generates API documentation, creates setup guides, writes inline comments, and updates README files when code changes.
Agent writes unit tests for new code, creates integration tests for API endpoints, generates edge case scenarios, and maintains test coverage metrics.
Agent monitors package versions, tests compatibility updates in isolated environment, creates PRs for safe upgrades, flags breaking changes for human review.
Medical AI agents handle appointment scheduling, insurance verification, prescription refills, and patient communications — all within HIPAA compliance requirements.
Agent books appointments based on provider availability and patient preferences, sends reminders, handles rescheduling, confirms insurance coverage before visit.
Agent checks eligibility in real time, verifies coverage for specific procedures, calculates patient responsibility, submits prior authorization requests to insurers.
Agent processes refill requests, checks medication interactions, verifies dosage with patient history, sends prescriptions to pharmacy, notifies patient when ready.
Agent asks symptom questions, assesses urgency using clinical protocols, schedules appropriate level of care (urgent vs routine), escalates emergencies to clinical staff.
Agent validates claim information, checks for coding errors, submits to payers, tracks claim status, handles rejections, resubmits with corrections.
Agent contacts patients after procedures, asks standardized health questions, flags concerning symptoms for clinical review, schedules follow-up appointments.
Financial agents monitor markets 24/7, execute trades, manage risk, detect fraud, and handle compliance — operating within regulatory frameworks and risk limits.
Agent executes strategies based on predefined rules, monitors price movements, manages position sizing, implements stop-losses, adjusts to market volatility in milliseconds.
Agent monitors transaction patterns, flags anomalies in real time, freezes suspicious accounts, generates detailed reports for compliance teams, learns from confirmed fraud cases.
Agent analyzes loan applications, pulls credit reports, assesses risk using historical data, calculates approval probability, routes decisions to underwriters with recommendations.
Agent monitors asset allocations against target percentages, executes rebalancing trades when thresholds are exceeded, minimizes transaction costs through tax-loss harvesting.
Agent extracts data from invoices, validates against purchase orders, routes for approval based on amount thresholds, schedules payments, reconciles accounts payable.
Agent categorizes expenses from receipts, flags policy violations, processes reimbursements, generates spending reports, identifies cost-saving opportunities.
Logistics agents optimize routes, manage inventory, coordinate shipments, and respond to disruptions — keeping supply chains running efficiently.
Agent plans delivery routes considering traffic, weather, delivery windows, and vehicle capacity. Reroutes in real time when delays occur, minimizes fuel consumption.
Agent monitors stock levels, predicts demand based on historical patterns, triggers reorder points automatically, coordinates with suppliers, prevents stockouts and overstock.
Agent coordinates picking/packing workflows, assigns tasks to warehouse robots, optimizes storage locations for frequently ordered items, manages fulfillment queues.
Agent monitors carrier updates, predicts delays based on route data, notifies customers proactively, coordinates with carriers for exception handling, updates delivery ETAs.
Agent sources suppliers, compares quotes, negotiates pricing based on historical data, generates purchase orders, tracks order status, manages vendor relationships.
Agent analyzes product defect rates, identifies patterns in returns, flags quality issues to manufacturing, coordinates recalls when necessary, maintains compliance documentation.
HR agents screen candidates, schedule interviews, answer employee questions, and handle administrative tasks — freeing HR teams to focus on strategic work.
Agent reviews resumes against job requirements, conducts initial phone screens via voice, assesses skill match, schedules qualified candidates for interviews with hiring managers.
Agent coordinates availability across interviewers and candidates, books conference rooms, sends calendar invites, handles rescheduling, prepares interview packets.
Agent sends offer letters, collects signed documents, provisions equipment, creates accounts, assigns training modules, schedules first-day activities.
Agent answers benefits questions, guides employees through plan selection, processes enrollments, handles life event changes, sends deadline reminders.
Agent processes time-off requests, checks accrual balances, routes approvals based on team coverage, updates payroll systems, sends calendar invites for approved leave.
Agent answers HR policy questions, troubleshoots payroll issues, processes address/banking updates, routes complex cases to HR specialists with context.
Content agents write blog posts, create social media content, generate product descriptions, and produce marketing copy — maintaining brand voice and SEO optimization.
Agent researches topics, identifies keyword opportunities, writes SEO-optimized articles, generates meta descriptions, suggests internal links, schedules publication.
Agent creates platform-specific content, schedules posts for optimal engagement times, responds to comments, monitors brand mentions, adjusts strategy based on analytics.
Agent writes compelling product copy from specifications, optimizes for search engines, A/B tests variations, updates descriptions based on customer questions, maintains consistent tone.
Agent drafts email campaigns, personalizes subject lines, creates multiple variants for testing, segments audience by behavior, analyzes performance metrics.
Agent writes video scripts based on content briefs, optimizes for engagement retention, generates closed captions, suggests B-roll footage, creates YouTube descriptions.
Agent translates content across languages, adapts messaging for cultural context, maintains brand voice consistency, handles technical terminology, validates with native speakers.
E-commerce agents handle product recommendations, pricing optimization, cart abandonment recovery, and inventory synchronization across platforms.
Agent analyzes browsing behavior, purchase history, and similar customer patterns. Suggests relevant products in real time, optimizes placement for conversion.
Agent monitors competitor pricing, adjusts prices based on demand/inventory levels, implements promotional strategies, maintains margin targets, tests price elasticity.
Agent sends personalized recovery emails, offers time-limited discounts, reminds of items left in cart, adjusts messaging based on abandonment stage.
Agent solicits reviews from verified purchasers, responds to negative feedback, highlights positive reviews, flags fake reviews, monitors review sentiment trends.
As this list shows, AI agents now operate across dozens of industries doing hundreds of different tasks. A customer service agent requires different verification than a trading agent. A healthcare agent needs different trust signals than a content creation agent.
The traditional approach — "show me your credentials and I'll trust you" — breaks down when agents operate across contexts. What you need is transparent data: What has this agent actually done? How long has it existed? Has ownership changed? What patterns appear in its interaction history?
RNWY provides that transparency layer. Soulbound identity tokens that can't be transferred. On-chain attestations showing actual usage. Wallet creation timestamps that can't be faked. Pattern detection that surfaces anomalies automatically.
Not a trust score computed by the agent itself. A transparent record of what actually happened.
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Read guide →Intercom Fin, Sierra, Zendesk AI, and more compared side by side.
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