And like you, I don't wanna minimize the value of efficiencies.

Part of the answer comes in thinking through, well, what do you do with the efficiency that you've gained? And the second part is, how do you i-in fact leverage AI to make the human part of the business stronger as well? So let me start with the second piece of that.

One of the places I started out really skeptical was the use of AI to help managers manage people better, right? And this is, like, a long-standing issue in business, right? Like, you know, in the old aphorism, like, people don't leave companies, they leave managers, right? And if you ask, like, so many HR professionals, though, they all told me the difference is often just, like, are these people engaging? Are they having the hard conversation? Are they avoiding it? And I tried all these AI coaches really skeptical, like, "Uh, it's not gonna help me." And it did.

Like, these are places where you can practice that hard conversation, where AI nudge tech is gonna tell you, like, your employee survey says that your team wants to be recognized more, and they just turned in a big deliverable.

Make sure that you go acknowledge them, go ask a question, et cetera.

These are places where you're tuning the AI to the human side of the equation.

But the first thing I said also was about what do you do with the gains of AI? How is that part of your strategy, right? So I think a lot about at Salesforce, we are using AI, and we're not only producing AI for customer service.

But there is this- I'd say very vocal strain of, of skepticism and, you know, how do you think about that balance?

That doesn't strike me as obviously a human AI interaction problem so much as just an AI problem that it hallucinates.

I guess I would debate that with you.

So for example, let's take the legal AI questions of lawyers, including hallucinated citations in their cases.

One of the things that we talk about or that I talk about in the book is around how you design something that's called positive friction into AI systems so that at the right moments, people are prompted to pay attention.

And to decide what they're going to trust and what they're not going to trust or where they might want to exercise judgment.

So I think you could think about that kind of as something that should happen after the AI runs in the case of, let's say, you're a lawyer that's delegating a research task to AI.

There's also lots of examples of why you get better results when you do this.

Yeah.

actually go through.

I love that story.

It's such a cool story.

Thank you for sharing it.

It made me think of so many things.

And there was a story.

So there's a story in the book that kind of echoes that.

And I see sometimes AI does a good job in this area and sometimes...

How does your role fit into that governance?

Well, I will say much to the credit of Salesforce leadership, this role got invented well before this wave of AI.

It's always been pretty AI focused, but I've been in the role for seven years.

And when I first took this role, it didn't really exist elsewhere.

But now you start to see a whole bunch of responsible AI officers at various enterprises.

But then the instinct was, look, technology is always going to evolve really quickly.

It's not like we're going to be able to have some sort of external blueprint to just apply.

You can give us that as a baseline.

modes,

right? So just thinking about like a good example to go into, maybe customer service is a good one because it is a place where I think AI adoption is quite strong.

And there's like a pretty good product market fit.

And you see all over the place, right, where AI can really solve pain points for people.

Like when I want to know where my order, what my order status is or whether I can, you know, return an item or whatever, I don't want to wait on hold for half an hour.

Like I just want an answer.

And AI is very good at that.

So very curious to hear what your concern is with that concept.