As more GenAI projects move from pilots to full-scale deployments, all eyes are on the data team.

Data teams have struggled for years to deliver clean, high-quality data. Widespread GenAI adoption has only increased the demand. Data teams are also uniquely positioned to leverage GenAI to reimagine data processing and deliver greater productivity. 

In our new survey, we asked 500 data leaders how they were navigating these changes. Could GenAI provide the breakthroughs needed to help data teams meet the AI moment?

GenAI taking off

It’s no surprise that GenAI is a hot topic among data teams. Just last year, Randy Bean’s Data and AI Leadership Executive Survey found that only 4.9% of organizations had GenAI in production. In the 2025 edition, the number surged to 23.9. Our survey showed a similar level of adoption: 23% of leaders saying they had GenAI projects fully scaled, in widespread production.

Why the rapid adoption? Data leaders are reporting dramatic results from GenAI. 87% of our respondents using GenAI reported 15% or more in productivity gains. 43% said they were seeing a 31-50% productivity boost. Interestingly, the majority of leaders not yet using GenAI expected to see lower gains. 53% said they would see 15-30% productivity gains.. Despite all the hype, GenAI is outperforming expectations.

In fact, GenAI is making such a good impression that 25% data leaders reported that their leadership would approve any project with AI as a core component.

Data teams skill up

But it's not all a rosy picture. Our survey asked central data team leaders and line of business data leaders what was holding back GenAI adoption.

Access to data was at the top of the list. The top data processing challenge was the excessive time required to create new data pipelines followed by the frequent back and forth with business teams on requirements and challenges in ensuring data quality.

When we asked what specific issue was impeding AI adoption, not surprisingly, improving data governance topped the list for the central data team. However, the line of business data leaders cited faster access to data as a top issue.

And even though driving efficiency is an overall goal of GenAI, data leaders from both teams identified a skills gap. Finding and hiring highly skilled data engineers was the overall top data team challenge. And more than half of our data leaders reported that both hiring more data experts and hiring AI experts were part of their organization’s plans to use and support GenAI.

Applying GenAI

To help meet these new challenges, data leaders were bullish on the adoption of GenAI. Fully 100% were using or planned to use GenAI. 33% were already using GenAI in workflows and 31% use GenAI capabilities embedded in tools.

When we asked where data leaders were focusing their GenAI efforts, access to clean, trusted data was again the hot topic. The number 1 area was data transformation and preparation, closely followed by data quality and data ingestion.

Data leaders are also looking at the big picture. Their top overall data systems challenge was ensuring data scalability. And for central data teams consolidating data platforms, retiring legacy systems, modernizing data systems ranked high.

Data leaders weigh in - live at Gartner in Orlando

We’re pleased to present the full results of our survey in this report. Download it today to explore even more findings including data team use cases for GenAI, organizational plans for GenAI, data leaders take on assistive versus autonomous AI, and where organizations stand on GenAI governance.

At the Gartner Data and Analytics Summit coming up March 3-5 in Orlando, we’ll hear directly from data leaders on what they are seeing as GenAI continues to impact the data world.‍

Join us for our panel The Impact of GenAI on Data Teams on March 5th at 2:30 to continue the conversation.

GenAI is reshaping every part of the data world. We hope these findings are helpful as you navigate these changes.