Snowflake Inc. The Six Five Summit: AI Unleashed 2026

Welcome. Thank you, Pat. Super excited to be here.

Yeah, really appreciate you joining, Sridhar. Thanks so much for helping us kick off day one. What an esteemed group to have. You're one of four. Marc Benioff also spoke here today. We've got enterprise apps, we've got data, we've got Matt Murphy kicking off, CEO, across the semiconductor space. We even have a wafer fabrication equipment with Gary Dickerson over at Applied Materials. We love having this broad perspective of CEOs opening up the days for us. I want to get your broader take. There's just so much going on, and you're all in different parts of the market, but I want to hear yours. You're in the middle of this data, this build-out. You talk a lot about provenance, governance, sovereignty, and so much is going on.

Where are you seeing what's going on at the enterprise layer, and what do you think the market is still underestimating about all that's happening in AI right now?

I think portions of the market actually get it, Daniel, and that is that software is getting easier and easier to create. What used to be a precious item Yeah is now more industrialized, more of a commodity.

That means that if you have great data, and Snowflake has always been about getting our customers to have great trusted data governed the right way, the value that you can get from it is pretty immense. It is not just me or any number of our customers finding out how much revenue did they make yesterday, but even a CEO can now slice and dice and look at the data. Why did this go on? Why did this go up? That kind of access to data, combined with access to all of the information and the tools that we all use, thanks to technologies like MCP, is heralding a real revolution.

I would say the final thing is also that because we are making tools that make the act of bringing data into Snowflake go a whole lot faster, there is like this ever-speeding up virtual cycle of you can get more done, which means bringing data into Snowflake, which means that you can get more value from the data, which means that you can begin to adapt what it is that you do. We have lived through changes like this with both us, our sales teams, our finance teams, and so on, but increasingly with our customers. I think that is what is really, really unique about the moment. It is that ability to both program and get stuff done with software, but also then get value from it in terms of how you get things done every day. All of the things that drive enterprises and businesses.

Ironically, it is the models themselves. That was the first point that I made, which is that they have gotten so good at writing code.

Yeah. I do not think people internalize that enough.

Code was always really, really hard. Just look at your phone. Look at all the apps that you have on your phone. It is probably 3 to 5 people at the very minimum. Obviously, with the big apps, it is thousands of people. They had to work incredibly hard to make something like that happen. Now, I have literally, in the space of an hour, taken an app that I have on my phone, something like a simple metronome app, and I can get one of the coding agents, including our own Cortex, to write me a new app that can do something like that. That is what I mean when I say software has gotten significantly cheaper.

What has not gotten cheaper is what matters to your business. Data is the thing that matters to your business because it is not just how much revenue you made yesterday, it is how are your opportunities progressing through the pipeline of actually turning into customers? Who is being most effective? Who is not? Is there a better pitch that somebody has? All of that analysis can now be done a whole lot faster. Where governance and provenance and things like that matter is if you have bad data, no amount of software is going to help you. Even in my own situation, once I realize that I am not quite interpreting a data set correctly, I immediately stop all work because the smartest model in the world cannot make sense of truly bad data. I think it is that realization that is driving this change.

But I think we are also seeing the second-order changes happen. Used to be, like a salesperson, when we gave him a sales agent, what they would do, it's like, "Oh, great, I can spend less time looking up the open use cases so that I can figure out what to do." It went from there to, "Okay, let me use AI to figure out what the three best next things that I should be doing for this customer are." Or if I have a new conversation, let me make sure I take the latest news about this customer into account as part of my pitch.