In this article
Two terms show up in every AI conversation and are often confused: generative and agentic. Understanding the difference is not technical trivia, it is what separates a project that saves hours from one that just generates more text for someone to review.
What generative AI is
Generative AI creates content: text, images, code, summaries. You give it an instruction, it returns a result. It is extraordinary at accelerating creative and analytical work, but there is one important limit: it does not act on its own. It produces a response and waits for a human to take the next step.
What agentic AI is
Agentic AI goes further. Instead of returning text, it executes tasks with access to tools. It can read an email, query the CRM, draft a proposal, update the billing system and notify the team, all in one flow, without intervention at each step. The difference is the autonomy to close the loop.
The simple analogy
Generative AI is like a brilliant consultant who writes a flawless report and hands it in. Agentic AI is like a colleague who receives the objective, executes the tasks and only calls you when there is a decision that needs human judgement.
When to use each
Use generative when the value is in accelerating creation and human review is part of the process: drafting proposals, producing content, analysing documents.
Use agentic when the value is in eliminating repetitive manual work end to end: handling support requests, processing invoices, orchestrating handovers between teams.
The mistake that costs time
Many companies deploy generative where they needed agentic. They produce excellent content, but someone still copies data from one system to another. The apparent gain hides the real bottleneck, which is still manual.
The decision
The right question is not which is better. It is: what needs solving, creating content or executing tasks. The answer drives the choice, and often the solution combines both, with generative producing and agentic executing.
Writes about AI consulting for operations and processes: how to map and simplify processes, apply AI where it has the most impact and measure the gains.