5 Key Takeaways from the 2026 Gartner Data & Analytics Summit

The 2026 Gartner Data & Analytics Summit was a great event filled with inspiring keynotes, thoughtful perspectives, and insightful conversations. And it will come as no surprise to anyone that AI dominated the discussions. From analyst presentations to vendors on the show floor, everyone was talking about the many ways AI—and AI agents—are changing how we work and think about the critical role data plays in ensuring success. 

5 Insights from Gartner’s Data & Analytics Summit

Here are my top five insights from this year’s event. 

‍1. Dashboards are dead

During the opening keynote on day one, an interesting thing happened. The Gartner analyst presenting the session made a bold statement: People are “sick and tired of dashboards.” And quite literally, the entire crowd cheered. 

This reaction was a bit unexpected. But with four out of five organizations increasing their investments in AI, it’s not all that surprising. As AI systems such as Claude and ChatGPT continue to gain traction, many organizations are under pressure to replace their dashboards and visualizations with chat capabilities. But not every organization—or their data—is ready for this level of change. As the keynote speaker mentioned, 57% of IT leaders are pushed to adopt AI before they are ready, and only 14% of respondents are confident that their content and data assets are suitably secured and governed. 

While dashboards may be heading toward obsolescence, many organizations have some work to do before they can eliminate them altogether. Which brings us to my next insight.  

‍2. Context is king

While AI was the leading theme throughout the event, context is a sleeper one. Many attendees, vendors, and speakers, such as Luke Mellors from CNA Insurance Canada, were talking about how organizations can prepare, organize, clean, and normalize their data—not for use in dashboards, but rather for consumption in agentic interfaces. 

Having a way to organize data into contextual layers—also known as enterprise knowledge graphs—is definitely top of mind. Enterprise knowledge graphs are connected, contextualized views of an organization’s data that highlight the relationships among and between key business entities, revealing meaningful connections that surface valuable and often overlooked context. And they are a critical component to ensuring your data is AI-ready and fit-for-consumption. 

Context is part of the critical infrastructure that fosters trust in the data. When agents have governed, contextual access to the right data, they deliver trustworthy insights. Without context, AI systems can misinterpret the data, leading to faulty insights, bad choices, or hallucinations, which erode confidence and trust.

3. Trust is the new currency

Trust was another trending topic throughout the event. And for good reason. Without trustworthy data, AI models and AI agents tend to confidently amplify poor-quality, inconsistent data, which can result in bad decisions that damage the business. 

By developing a trust model, organizations can provide guidance on whether or not the data is fit for use. Well-defined, well-governed data that’s updated consistently may fall into the “free use” category, while data that lacks quality, lineage, and oversight may be classified as “do not use” or “use with caution and monitoring.”

With trust as the foundation, organizations can successfully deploy and integrate reliable AI agents into business workflows to deliver greater value.  

4. Governance (still) matters

As there was in years past, there was a lot of talk about governance. But this year, governance took on a slightly different tone, with more than one analyst referencing the famous line from Fight Club: “The first rule of Fight Club is you do not talk about Fight Club.”

The same is true for data and AI governance. Instead of talking about governance, data leaders should focus the conversation on the business outcomes and value governance provides. By discussing outcomes such as greater agility, increased automation, and improved efficiency, organizations will see the value governance provides, while leaving preconceived notions behind. 

A Prediction for 2027

During the last night at the event, I was talking with another attendee over dinner. And the attendees asked me a great question: What did I predict as the theme for next year’s Data & Analytics Summit? I didn’t love my answer, but I did love his response which was “organizational resilience.” 

This theme makes a lot of sense. After all, AI and AI agents are disrupting so much of what we do. In fact, according to a Gartner survey, CIOs estimate that by 2030, 0% of IT work will be done by humans alone—everything will be at least augmented or supported in some way by AI. Over the next year (and beyond), we are going to experience big changes to workflows and processes related to data. And as these changes begin to take hold, they will spark many discussions and debates about the best ways to build and organize our data teams. With AI agents as our new teammates, the ways in which we collaborate and interact will fundamentally change. It’s exciting, but worth plenty of discussion for sure. 

The Momentum Continues

Once again, this year’s event brought together great ideas, honest conversations, and a shared sense of momentum. But remember, the work doesn’t stop here. The ideas you discussed, the insights and advice you collected, and the actions you need to take are first steps toward realizing even greater value from your data.