The Death of Data Gatekeeping: AI Makes Everyone An Analyst | Hex Cofounder

**Barry McCardel** (0:00)
The fastest way to really annoy a lot of people is to have a system that's giving them consistently wrong answers. I think that the percentage of actual decisions that are made every day that are informed by data is really, really low. As sexy and cool as the things like the notebook agent and threads are, the thing I wind up gravitating to is actually the things we're doing around context management and observability and governance, because that's the stuff that are going to make those answers trustworthy. Palantir has generated a lot of successful founders, because it is selected for and then cultivated people who are really interested in. I'm just going to go out, find a problem, and run like hell and figure out how to solve it. Whenever you have these technical shifts that settle in, you're just going to have a consolidation. There's going to be a few sets of people who really are able to win and accrue a lot of value, and then other people who will get acquired or pivot or figure other things out.

**SPEAKER_2** (0:56)
Dashboards became the center of data work, but they rarely delivered real answers. For two decades, companies have relied on the same basic workflow to understand their data. Open a dashboard, drill into metrics, export information and share it across teams. AI introduces a different approach. It interprets context, applies reasoning steps and generates insights without depending on manual navigation or predefined dashboards. Barry McCardel is working at the center of this shift. He's the co-founder and CEO of Hex, a platform designed to make AI an analytical partner rather than an add-on to existing BI tools. In this conversation with a16z General partner Sarah Wang, Barry explains how data teams are evolving into context engineers, how agentic workflows are reshaping analysis, and why time to insight may soon move faster than the questions themselves. They explore why dashboards are becoming less central, how semantic context improves trust in AI systems, and why the structure around the model matters more than the model alone. Hope you enjoy.

**Sarah Wang** (1:58)
Barry, thanks for being here today.

**Barry McCardel** (1:59)
Yeah, thanks for having me.

**Sarah Wang** (2:00)
Awesome to have you here. So I wanted to kick off on a meaty topic. You talk to a lot of different data teams at different enterprises, and Hex is obviously a leader in the data space. The application of AI to data feels like the Holy Grail.

**Barry McCardel** (2:15)
Yes.

**Sarah Wang** (2:15)
Can you say a little bit more just to kick off on how you think AI is going to change the data space?

**Barry McCardel** (2:21)
Totally. So it's interesting when you talk to people at enterprises, organizations, companies of any size. The last 20 years has really been chasing this promise of data democratization. I was in the analytics software space like 10 years ago, and data democratization was like the buzzword everyone was saying.

**Sarah Wang** (2:38)
Totally.

**Barry McCardel** (2:39)
But it's not really happened. The last 10 years, the big change has been easier than ever to bring all your data together. You had the cloud data warehouse, you had technologies like 5chan and dbt. So now we can like get all of this data, and then it's well, what are we doing with that? We're still just putting dashboards on top. Like dashboards are really good for like what happened and sort of like KPI trends. I love a good dashboard, but dashboards raise more questions than they answer. For sure. And so there's always this dream of like, well, wouldn't it be great if everyone in the organization could use data to ask and answer questions? I think that the percentage of actual decisions that are made every day that are actually informed by data is really, really low. Like, if you think about all of the different things that you could better inform with data, and then the number of people that goes through the whole workflow, well, let me open my BI tool and find the dashboard and then find the right data and drill down and do all the different things. It's very hard. And so obviously with AI, it's like the appeal of just being able to ask a question in natural language. And get an answer. It's so obviously exciting. And in fact, there's been like demos and concepts, like promises of this, well predating LLMs. And so now with these AI technologies that are really working, we do have this potential and now a reality that we're starting to bring to bear of a world where everyone in an organization can ask and answer questions with data. And it's just enormously exciting.