What is agentic AI?
By Yassine Seghrouchni, founderUpdated
In short
Agentic AI is the umbrella term for AI systems that work towards a goal on their own. They plan the steps, use tools and other systems to carry them out, assess the intermediate result and adjust. An AI agent is one such system. Agentic AI refers to the approach as a whole, often with several agents passing work to each other.
Also known as: agentic systems
From answering to acting
Agentic is about how much an AI system is allowed to do on its own. That increases in steps:
- Chatbot: answers a question and waits for the next one.
- Assistant with tools: carries out a single action on request, such as looking up a customer in the CRM.
- Agent: gets a goal and works out which steps are needed, and in what order.
- Multiple agents: each with its own task, passing work to one another. One gathers, another checks, a third carries out.
So the word says something about how independent the system is, not about the model behind it. That is almost always a large language model that plans the steps and picks the tools.
Agentic AI and generative AI
Generative AI makes something: a text, a summary, an image. Agentic AI does something: it takes steps in your systems. An agent uses generative AI to work out the next step, and an integration to carry it out, for example through an API or an MCP server.
Why it matters in practice
Autonomy is a design choice, not a property you want as high as possible. Every step an agent takes on its own is a step where an error can creep in and carry through to the next. And every extra agent is one more place where that can happen.
So set out for each agent what it may decide on its own and what always goes to a person, which systems it may use and how you can see afterwards what it did. For a retail organisation, we built an overview in which every agent has a task, fixed limits and a manager. Agents only pass work on through fixed routes, and anything outside their limits goes to a person. Every action is recorded in an audit log that can only be added to.
The misconception: the more autonomy, the better
Much of what is sold as agentic AI is an ordinary workflow with an AI step in it. That’s not a problem; it’s often the better choice. If a task always follows the same steps, fixed automation is cheaper, faster and easier to check than an agent that picks its own route every time.
An agent only earns back its complexity when the order of steps differs from case to case. More in AI agent or ordinary automation.
Frequently asked questions
What is the difference between agentic AI and an AI agent?
An AI agent is a single system that gets a goal and takes steps on its own. Agentic AI is the broader term for this way of working: AI that plans, acts and adjusts, often with several agents working together. In practice, the two terms are often used interchangeably.
Is agentic AI safe enough for business processes?
It is if you set the limits. Give each agent only the rights and tools it needs, have a person approve irreversible actions and log every step. If an agent reads email or documents from outside, bear in mind prompt injection: hidden instructions that make it do something else.
