Jul 27, 2026 · 44 min · 13 segments
What if the person whose entire job is risk was the most excited one in the room about AI? That's Mea Clift. While most CISOs are bracing for what could go wrong, she's leaning in, she calls it being…
Mia CliftGuestMoHostNo, that's pretty cool.
And, you know, you talk about like education data.
And, you know, on the show, we've had folks from like all different sorts of backgrounds, from financial.
We've had medical.
I think you are one of the few people that have come on the show that is coming from an ed tech place.
And specifically, you know, it sounds like you have a lot of student data to deal with.
So one of the things that I like to ask when you're in any of these kind of spaces is like, how's like AI just initially when it first started being adopted by orgs? What did that look like? A lot of orgs would take a governance heavy approach at the beginning because of the types of data that they had.
A lot of them are more innovative approach.
So like, how do we like innovate first and then figure out the problems later? So how did it kind of happen for you?
So it's been very much a journey of what are we doing with it? How can we do it? How can we leverage it to make our environment better, to make the customer experience better with engaging with support or even engaging with our education components? So we've taken that very, like, I want to say, I said this at a different presentation, a very risk-excited posture when it comes to AI.
Like we're willing to see where it's going to go and how well it can work in our environment.
Yeah.
Okay.
So makes sense.
And risk excited is one way to say it, I will say.
And it was the first panel of the day and I just dropped it and everybody went with it.
Yeah, I mean, it makes sense though, right? For a lot of organizations, it's like, okay, we are going to build, we're going to do it fast, and we are excited to build.
No, that's pretty cool.
And, you know, you talk about like education data.
And, you know, on the show, we've had folks from like all different sorts of backgrounds, from financial.
We've had medical.
I think you are one of the few people that have come on the show that is coming from an ed tech place.
And specifically, you know, it sounds like you have a lot of student data to deal with.
So one of the things that I like to ask when you're in any of these kind of spaces is like, how's like AI just initially when it first started being adopted by orgs? What did that look like? A lot of orgs would take a governance heavy approach at the beginning because of the types of data that they had.
A lot of them are more innovative approach.
So like, how do we like innovate first and then figure out the problems later? So how did it kind of happen for you?
So it's been very much a journey of what are we doing with it? How can we do it? How can we leverage it to make our environment better, to make the customer experience better with engaging with support or even engaging with our education components? So we've taken that very, like, I want to say, I said this at a different presentation, a very risk-excited posture when it comes to AI.
Like we're willing to see where it's going to go and how well it can work in our environment.
Yeah.
Okay.
So makes sense.
And risk excited is one way to say it, I will say.
And it was the first panel of the day and I just dropped it and everybody went with it.
Yeah, I mean, it makes sense though, right? For a lot of organizations, it's like, okay, we are going to build, we're going to do it fast, and we are excited to build.
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