Agent AI is the next step beyond basic Generative AI. It uses the same foundational large language models (LLMs), but wraps them in a layer of logic that allows them to operate with autonomy. Rather than responding to one-off prompts, an agent carries out a multi-step process in pursuit of a defined outcome. 

Let’s say you want to send 2,000 personalised emails. A traditional AI might help you draft the message, but you'd still need to format the contact list, integrate it into your CRM, write the final version, and send it. An Agent AI takes care of all of that. 

It does this by “thinking” like a human breaking down the job into smaller subtasks, completing each one, and even checking its own work along the way. The agent has a continuous internal dialogue (think: a conversation with itself), adjusting its approach to get a better outcome. It can access tools, systems, and APIs whether it's reading a spreadsheet, generating content, or logging into another system to perform an action. 

And crucially, an agent doesn’t need you to stand over its shoulder. Once set up correctly, it can repeat processes consistently, improving speed, reducing errors, and freeing up your team to focus on strategy and creative thinking.