Agentic AI: what is it, and how does it differ from generative AI?

Agentic AI is talked about more and more, and is often confused with classic generative AI. Yet the difference is simple to grasp once you know where to look: it is a question of autonomy, not just power.

What is agentic AI?

An agentic AI is a system able to perceive its environment, reason, draw up a step-by-step plan, use external tools and adapt to results, all without continuous human intervention. It works in a loop: perception, reasoning, action, verification, adjustment.

How does it differ from generative AI?

Generative AI produces content (text, images, code) on demand: it answers, but does not act on its own. Agentic AI often uses a generative model as its reasoning engine, but goes further by carrying out tasks end to end in real software or computer systems, for example launching a campaign, analyzing the results and adjusting the strategy without validation at each step.

Real-world examples of agentic AI

• An agent that runs a marketing campaign end to end: writing, publishing, analyzing the impact, automatic adjustment.
• An automated customer service able to resolve a request in full without handing it over to a human, except in special cases.
• Layers of agents built into business platforms (CRM, line-of-business tools) to automate repetitive decisions.

Generative or agentic: what do you really need?

Before starting an agentic AI project (often complex and costly to implement), it is worth checking whether a simple generative AI already meets your need.

Test the reasoning of the models behind agentic AI

Before investing in an agentic project, testing the reasoning quality of the models that will serve as its foundation remains a useful step. On Ai-chatpro, ChatGPT, Claude, Gemini and Mistral are accessible from a single interface, with 3 free messages every 24h on the free models.

What to Remember

• Agentic AI acts autonomously to reach a goal; generative AI simply answers a request.
• An agentic system often uses a generative model as its reasoning engine, but adds a real action loop inside software.
• Most everyday needs remain covered by a standard generative AI, without requiring a full agentic system.
• On Ai-chatpro, several reasoning models are accessible for free to assess their relevance before any more complex project.