04.01. Adam Grainger of Agentic Risks discusses the rise of AI agents

And so, let's start by setting the stage for what that is.

So, when we talk about an AI agent, you have a very specific definition for what you mean by an agent.

And that's very important to understand why it is that you Founded agentic risks to deal with the very specific nature that this technology represents.

So perhaps we can start there with what an agent is under your understanding.

Okay, so if our listeners take away one thing from this session, from this podcast, I would like it to be that AI agents are not just another agent.

AI model and that we perhaps need to stop referring to just AI as an overall phenomenon.

We already know that we have predictive AI and assistive AI.

A few years ago, there was a big leap forward and generative AI came on the scene.

Generative AI is the most powerful.

It is self-directed.

You can set it a task and it will figure out how to achieve that, but it is passive.

and this is a really important point it will create an output for me to review what a gentic ai will do is it will again plan it will pull in the tools it needs the ones that you've let it use it will take actions it will interact with its environment it'll interact with other agents it'll interact across systems both internal and external systems again if you allow it But crucially, it will then, rather than creating an output for my review, it'll create an outcome in my name.

Done.

Gone.

And then the last thing before I pause for breath, it's really important to remember the final feature of AI agents.

And that is that they learn from there.

They can learn from their experiences so they can adapt for the future, for the next time you ask it to perform the same task.

So I think agents, the way you've described them, are a more versatile technology than we've seen in the past.