15 Real AI Agent Examples in 2026 (by Function) · TinyCommand

Klarna’s support agent now handles two-thirds of its customer chats, and a Danfoss agent clears 80% of B2B order decisions on its own. The best AI agent examples all do the same thing, they take action on the company’s own data, not just chat. Below are 15 real ones from 2026, grouped by function. Each is grounded in real data, connected to real tools, and handing off to humans when it should.

What Counts as a Real AI Agent Example?

A real AI agent example does work, not just talk. It reads context, decides its own steps, uses tools to act (look up, update, send, route), and knows when to escalate. A chatbot that only answers FAQs does not count.

Keep that filter in mind as you read. The examples below were chosen because the agent actually completes a task, not because it gives a slick answer.

Customer Service Agents

This is where agents are most common. Production deployments in 2026 already automate 55% to 70% of structured support workflows.

• Klarna’s support agent handles about two-thirds of all customer service chats, doing the work of 853 agents and cutting response times from 11 minutes to under 2.
• Intercom Fin works across chat and voice, accesses customer data, issues refunds or updates accounts, and decides when to escalate to a human.
• Salesforce Agentforce resolved 83% of customer service queries autonomously in its own internal deployment.

Sales & Marketing Agents

• AI sales development agents research, qualify, and follow up with leads. One fintech replaced three SDRs with an agent at a tenth of the cost. See the full AI sales agent breakdown.
• AI marketing agents plan and run campaigns across channels, personalizing at scale. Customers engaged through AI personalization are 2.3 times more likely to buy. See the AI marketing agent guide.

Operations & Finance Agents

• Danfoss order management. The industrial manufacturer deployed an agent that processes B2B orders arriving by email, with more than 80% of transactional decisions now handled by the agent.
• Genpact finance agents let finance teams pull revenue and profit-and-loss insights through plain-language conversation instead of building reports.
• Harvey reviews legal documents, reasoning over hundreds of pages so lawyers focus on strategy.
• Walmart’s Wally aggregates sales, inventory, and demand signals across the business and surfaces decisions for merchants in seconds.

IT & HR Agents

• Moveworks resolves employee IT and HR requests end to end. Provisioning software, resetting a password, or answering a benefits question happens without a ticket ever reaching a human.
• Onboarding agents walk new hires through setup, answer policy questions, and create the right accounts automatically.

Industry-Specific Agents

• Healthcare: AtlantiCare’s clinical assistant cut documentation time by 42%, saving providers about 66 minutes a day.
• Manufacturing: predictive-maintenance agents watch IoT sensor data for anomalies in vibration and temperature, then trigger maintenance before a breakdown.
• R&D: Genentech built agent ecosystems to automate research workflows so scientists focus on drug discovery.
• Cybersecurity: agents write detection rules, isolate compromised workloads, and neutralize tier-1 threats without human intervention.

The Common Thread

Every example here is grounded in real company data, connected to tools that let it act, and built to hand off to a human at its limits. The demos that flop usually skip one of those three.

That is also the recipe you can copy. You do not need Klarna’s budget to build a useful agent. You need your own data, a few tools, and clear rules. Our guide on how to build your own AI agent walks through it step by step.

Pick the example closest to your own busywork and ship your version of it. TinyAgents lets you build that agent on your real data, no code, free to start.