Talk to me about your priorities and your objectives with that hat on.

Sure.

And maybe some context would be helpful.

So at S&P Global, we've always been managed.

We're a large company, and this is not rocket science.

We're large companies.

We manage as multiple business units or divisions.

Your views on how the desktop product may evolve in the coming years, particularly in the context of AI?

Now, if I think of the data and AI leaders out there listening, some of them get a little bit beat up in the role and yet you have elevated it to you actually own the business outcomes How do the synergies between having a data and AI strategy and owning the outcomes work together?

So I'd like to start by reminding your listeners that for us at SMD Global, data is not an afterthought.

It is our stock in trade.

That's what we do.

We sell several tens of billion dollars worth of data every year.

So it's imperative that we get it right.

And for us, Capturing business value from the data is not option.

What should leaders be paying attention to here?

But that's where I think the potential

is.

I think Venkat nailed it on the head with the last part, which is, as you said...

The barrier to adoption, the adoption curve will be defined not by technology or the technologists or the people who deploy the technology.

It will really be defined by the societal willingness to accept change and our ability to manage the change socially.

I think, you know, the... acceptance, social acceptance of errors made by humans versus machines is a good one, right? If you look at what's happening with autonomous driving globally is a good example.

And if you extend that into other industries like ours, we are very quick to jump to errors made by machines and point out how that might be unacceptable.

Glad he asked you that question.