The Control Layer with Amer Altaf
Sep 2, 2026 · 1 hr 5 min · 12 segments
Elastic CISO Mandy Andress on agent identity, and who answers when it goes wrong. Your organisation is about to get very strict about what its AI agents may touch, and no stricter about what you may…
Mandy AndressGuestAmer AltafHostSo from that vantage point, what can you see when it comes to AI and security that others may end up missing?


So putting it through its paces, a lot of people don't know the name Elastic, but it sits in the... core infrastructure of many, many, many of the online services and other companies that you interact with on a daily basis.

So sitting at that convergence just allows us to see all the different ways that customers are trying to utilize AI, how, what's working, what's not, what types of data is interesting and relevant, and then how we can continue to analyze that deeper and understand within our environments how we need to adapt and adopt to AI.
So when you speak to security leaders and your customers, what do you think is the thing they most often get wrong when it comes to AI?

For me, these days, and things are changing so rapidly, I think they put a lot of emphasis on the underlying models.

And while that's critical and that's important, certainly models have their strengths and their weaknesses, and some are much better at different types of analysis and different types of applications.

But I see them not focusing as much on the data within their own organizations that they're utilizing within their AI processes.

And so focusing on the model versus focusing on what are the inputs to the models from your organization, you might get different answers if you had a different foundational data.
So from that vantage point, what can you see when it comes to AI and security that others may end up missing?


So putting it through its paces, a lot of people don't know the name Elastic, but it sits in the... core infrastructure of many, many, many of the online services and other companies that you interact with on a daily basis.

So sitting at that convergence just allows us to see all the different ways that customers are trying to utilize AI, how, what's working, what's not, what types of data is interesting and relevant, and then how we can continue to analyze that deeper and understand within our environments how we need to adapt and adopt to AI.
So when you speak to security leaders and your customers, what do you think is the thing they most often get wrong when it comes to AI?

For me, these days, and things are changing so rapidly, I think they put a lot of emphasis on the underlying models.

And while that's critical and that's important, certainly models have their strengths and their weaknesses, and some are much better at different types of analysis and different types of applications.

But I see them not focusing as much on the data within their own organizations that they're utilizing within their AI processes.

And so focusing on the model versus focusing on what are the inputs to the models from your organization, you might get different answers if you had a different foundational data.
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