Agentic AI use cases: 15 examples in different industries

Looking at industry-specific agentic AI use cases provides a great snapshot into the flexibility and resourcefulness of this tool. Real-world examples show how agentic AI extends beyond traditional enterprise AI. Instead of offering isolated predictions, it uses coordinated AI agents to interpret goals, organise work into steps, and carry actions forward across systems. These patterns become especially visible in industries where timing, accuracy, and compliance intersect.

Agentic AI works by combining a number of AI agents into a shared framework that can pursue business goals with a degree of independence. Each agent is a small, specialised programme that can perceive, decide, and act within a narrow area – such as checking inventory, updating a schedule, or validating a contract. The agentic layer coordinates multiple agents and allows them to interpret intent, break work into steps, assign those steps to the right agent, and keep track of what has happened so far. It strings multiple actions together, moving across ERP, supply chain, asset, and industry-specific systems and keeping context as it goes – so work progresses from one step to the next without constant human nudging.

In industry settings, this coordination is what turns AI from “helpful insight” into “work that actually moves.” A single agent might spot a maintenance risk; an agentic system can schedule the work, reserve parts, update production plans, and capture the outcome. The examples below show how that same pattern plays out in manufacturing, healthcare, public sector, distribution, and more – using AI agents that understand the rules, data, and workflows that make each industry unique.

No matter what it produces or provides, every business in the world shares the desire to improve efficiency, productivity, and quality. And those same businesses are also vulnerable to a range of both controllable and uncontrollable risks. To succeed, you need the ability to recognise both risks and opportunities, as soon they present themselves – and the agility to act without delay. In today’s world of heightened competition and fast-shifting markets, it feels harder than ever to achieve these goals. Enter agentic AI. With its ability to learn from every cycle, it helps you move from reacting to anticipating. It gives team members clearer options, frontline staff smoother workflows, and customers more consistent experiences. With agentic AI embedded in core processes, you’re better prepared for whatever the next season, shift, or disruption brings.