How Real Estate Firms Can Beat the 95% AI Project Failure Rate | Ilya Feldman

I think companies are starting to become wise and lock things down more and more. And as you lock things down, that's when, that's when-- That's how you actually can fight back against AI, is locking down your data. And if I, as a PE firm, am the only one, let's say, has access to a specific type of data about single-family rentals that nobody else does, then that's gonna be my big differentiator. And I advise every company to really be thoughtful about their data. Don't treat it as a secondary kind of like throwaway object.

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Hey, folks. Welcome back to the show. Today, we're joined by Ilya Feldman, the founder of SLED AIQ, bringing AI expertise to help streamline business and give solutions where many AI projects fail. Ilya, thanks for joining us here today.

Thanks for having me, Dylan.

Uh, what types of deals and conversations are coming across your desk these days?

Yeah. So it's not so much deals for me because really my conversations are happening with private equity, um, managing partners and more larger scale real estate, uh, companies. But what I'm hearing is everyone wants to use AI. Everyone is playing around with it. Just like your show, and I could tell a lot of our pre-communications were driven by AI. Everyone is doing something, but at the same time, at the corporate level, a lot of AI projects are stalling, and there seems to be a gap of, yes, everyone knows it's in, in improving productivity. At the same time, there's a, I believe it was a MIT study that said ninety-five percent of corporate AI projects actually failed. So that's the conversations I'm having, where people are coming to me trying to figure out where is that gap and how do we close it. And then the second piece I'm also discussing is the security aspect of it all. A lot of traditional IT, the security folks, et cetera, and even outside of IT and just there's this misunderstanding on what vulnerabilities AI can actually, uh, expose, what prompt injection actually is, how easy potentially somebody can get data out using AI without somebody even understanding what the risks are. So those are the two things that I've been really focused on over the past couple of months.

Now, you mentioned a figure, ninety-five percent of corporate AI projects fail. I mean, so much comes to mind here, but what might that look like?

Yeah. It's a great question. And I think, again, that number is coming from a study done by MIT, so I'm surprised as well. I think all of us are, 'cause we can all see what AI is actually capable of, the productivity gains that it does provide. There is a few key things that seems to stand out across these