to do your document

review.

The courts have been pretty clear that there is no block or prohibition on using technology to do your document review.

Two, If you are going to do that, you need to have a process and be able to explain it.

This is, you know, 99% of the time when we have an issue with discovery, it's because that the, you know, the folks involved couldn't really explain it very well, what they did and why they did it.

And I think at first lessons learned from TAR, we did have that at first where people couldn't or refused to explain how they were doing it and what the procedures were.

So what I'd say is be prepared to be able to explain your process if it gets to that point.

I

And I think, I don't think the regulators, I think, Robert, as you said, regulators are going to say, well, this method is wrong, but you just have to make sure it's working, right? So again, you have to do lots of All the stuff that you should be doing in terms of monitoring, how it's working, adjusting for new data sources, all the things that if you have a supervisory program you should be doing anyway, it's just using a tool instead of probably a lot of people reading and communications and stuff.

And I'm going to play the role of Anthony Diana here in talking about predicting dramatic changes in the future.

But I will say is things to look out for is that, look, reality is that, well, Robert is right.

Like there's been like analytics and things that have been a part of supervision for a long time.

The compliance industry in the matter of technology has been fairly slow.

to move into new and advanced technologies, right? Still heavy reliance on things like lexicons and the like, which we know are not great.

I mean, they're not great.

And then finally, you know, Therese, you sort of started to touch on this earlier, but, you know, as firms switch to models, as firms start to, you know, leverage more agentic AI as part of their supervisory systems, you know, what can they do to defend those actions? Like, what do they need to do to take the steps so if they're ever questioned about it, they can defend it and, you know, justify their use of these agentic AI or these models?

I mean, how do we see the regulators providing guidance here in terms of how firms should be dealing with AI outputs? Therese, what have you learned? What have we gathered from regulators as far as their obligations?

Yeah, I mean, I think from the regulatory perspective, what we're hearing from the regulators is what we always hear from the regulators, which is, well, there are rules out there.

And if the rules apply to, you know, the same rules that apply to other technology apply to AI.

And so if you're using AI and the output is a record under the existing regulations, then you need to keep them.

And I think this gets frustrating for a lot of our clients when you're trying to interpret it.

The regulators, particularly with new technology, tend to be deliberately vague, right? In some perspectives, they don't want to stop innovation and they don't want to stop development.

They're still feeling out what AI is and how it works and how it's being used in business.

Do you guys see any change in the way that companies are approaching due diligence on the model providers themselves in terms of their data protection practices, where they're storing their data, how they're storing the data, what is your ability to retrieve it if you get a regulatory request or litigation? If that's the location of where you're managing this data, how are firms approaching third-party risk management differently, or are they?