The State of Data Teams 2025: AI, self-serve, and the reality check

First, a heartfelt thank you to everyone who took the time to participate in this year's survey. Your input is what makes this work possible. We've packed a lot into this year's report, and you can explore all of it right here.

Why we set out to do this survey

We wanted to capture a collective snapshot of what data leaders are thinking about in 2025.

Data team goals are the same, but the tools and landscape in which we’re all doing data work is changing. AI is evolving at breakneck speed, more data tool acquisitions are happening, and stakeholder expectations are only growing. Amidst so much change, we set out to get clear on:

What’s actually going on across data teams right now? What are people struggling with? Where is all this AI buzz leading? Where are data teams spending their time?

We asked over 2,000 data professionals to better understand what’s top of mind, what’s working, and what’s still very much a work in progress.

A few themes that caught our attention

We got tons of great insights, big and small, from the data leaders who took our survey. But what was most interesting to us were the questions they are grappling with: questions that we expect to be themes for data teams over the next year:

1. “When is the right time to take advantage of AI on data?”

We heard some healthy concerns about the readiness and trustworthiness of AI to deliver meaningful data-driven insights - 77% are excited about the possibilities, but at the time of the survey, only 3% said it was the top priority for them or their team.

Our take: If you aren’t making AI a priority right now, you’re falling behind your competitors. One of the reasons it might not seem as urgent is because AI is only as powerful as the tools it has access to. If you are looking at AI through a BI lens, you might see it as a way to generate dashboards faster. We see it as a sea-change for the industry. On a related note…

2. “Why is my BI dashboard solution failing?”

Data leaders who took our study got emotionally charged when we asked about self-service BI, expressing frustration; the tools aren’t working, people don’t use it, the vendors aren’t innovating. 70% of teams are actively rethinking their stacks to make self-serve work better. Few feel like they’ve fully cracked it.

Our take: Dashboards fail because they are built around the concept that questions are finite. If the data team can think of every question their stakeholders might have, they can create a dashboard for every answer. But questions are not finite. Every day there are new challenges and opportunities that data can help address. This is why tools that make going from novel question to unique insight faster are key to being successful in the modern world.

3. “How should I be developing my team if AI is coming for all our jobs?”

It’s a common refrain in every tech circle - is the primary benefit from AI to eliminate jobs? Our survey revealed that data leaders have big aspirations for their impact. 90% of respondents said they were hiring or staying steady in team size, and leaders described themselves as strategic value drivers for their organizations.

Our take: Our survey suggested that data teams are growing and expanding. Despite advances in AI, the need for human context, judgment, and collaboration isn’t going away. Data teams can leverage new tools to increase their impact, not shrink to fit old standards.

For data leaders, it’s a balancing act

If you’re leading a data team right now, none of this is probably surprising — but hopefully, it’s helpful to see that you’re not alone. There are still lots of demands on data teams; but we’re here to continue to discuss tool evolutions and how to navigate the change.

👉 You can read the full report here.

We hope you find it insightful — and as always, we're here to help.