Data leaders left the Gartner Data & Analytics Summit London 2025 with a wealth of insights to navigate the rapidly evolving landscape of data and AI governance. As Pieter den Hamer, VP Analyst at Gartner, cautioned in his opening keynote:
“If you can’t explain the value of what you do in terms that your business peers understand, you will be viewed as a cost center ripe for reduction when we face economic headwinds versus a strategic growth engine of the business.”
This warning perfectly describes the central theme of the summit: in the era of AI, data governance must be redefined as a driver of business value, not just a compliance checkbox. At Atlan, we’ve long believed in this vision of governance as an enabler of innovation and growth. As we reflect on the summit’s key takeaways, we’re excited to see our philosophy validated and gain fresh perspectives on how to maximize governance impact.
In this post, we’ll explore 7 key lessons from the 2025 Gartner Summit in London — each offering practical ways to turn data governance from a cost center into a growth driver.
Lesson 1: Trust is the Connective Tissue of AI Adoption #
One of the summit’s core messages was that trust is the foundation of successful AI adoption. Organizations must apply trust models across three critical journeys:
- Business outcomes
- Technical capabilities
- Cultural change
This means ensuring that AI systems are transparent, explainable, and aligned with organizational values.
Heard during the summit: As Aura Popa, Sr Director Analyst at Gartner, warned, “Misplaced trust in data for AI has led to an accumulation of issues, and the bill is coming due.” This underscores the urgency of building trust into every stage of the AI lifecycle, from data sourcing to model deployment.
Lesson 2: AI is Powering the Next Generation of Analytics #
The summit highlighted the rapid shift from traditional analytics to AI-powered insights. Augmented analytics, generative AI, and decision intelligence platforms are enabling organizations to extract more value from their data and make faster, more accurate decisions.
Heard during the summit: The “Future of Analytics in the Era of Generative AI” session emphasized the need to “power the next generation of analytics with AI” by broadening adoption and enhancing analytic and BI platforms through generative AI capabilities. This reflects the growing recognition that AI is not just a nice-to-have, but a critical component of modern analytics.
Lesson 3: Measurable Outcomes are the New North Star #
Another key insight from the summit was the urgency to link data governance to measurable business outcomes. Too often, governance initiatives focus on abstract metrics or compliance checklists rather than tangible results.
Heard during the summit: The “Peculiarly Challenging Business Case for GenAI” session revealed that nearly half of CDAOs lack metrics to track data and analytics value. Without clear outcome-based KPIs, it’s difficult to justify investments in governance and demonstrate ROI.
Lesson 4: Federated Data Management is the Future #
The summit made clear that the days of centralized, command-and-control governance are over. Federated data management, which balances local autonomy with global standards, is emerging as the new normal for enterprise data landscapes.
Heard during the summit: Thomas Oestreich, Managing Vice President at Gartner, declared in the opening keynote, “Federated data management is the new normal.” The “Data Mesh: A Successful Path to Federated Data Management” session advised organizations to “prefer soundness over speed at the beginning” when implementing a federated approach, emphasizing the importance of getting the foundations right.
Lesson 5: Strategic Platform Selection is Key #
Choosing the right data governance platform is critical to maximizing impact. Organizations need to evaluate platforms based on their specific use cases, maturity level, and ecosystem requirements.
Heard during the summit: Guido De Simoni, VP Analyst at Gartner, advised in the “Key Steps for Assessing Your D&A Governance Platform Requirements” session, “Select your platform thinking about enterprise health like you would do for your personal health.” This means looking beyond features and considering factors like scalability, user experience, and integration capabilities.
Lesson 6: Responsible AI Governance is a Must-Have #
The disruptive power of generative AI (GenAI) was a hot topic at the summit. While GenAI offers tremendous potential, it also introduces new risks and challenges for governance, from data privacy to model bias.
Heard during the summit: Pieter den Hamer warned in the opening keynote, “Through 2028, at least 50% of GenAI projects will overrun their budgeted costs due to poor architectural choices and lack of operational know-how.” This highlights the need for robust governance frameworks and practices to ensure the responsible development and deployment of GenAI systems.
Lesson 7: Change Management is Make-or-Break #
Perhaps the most powerful lesson from the summit was that people, not just technology, are the key to governance success. Driving cultural change and stakeholder alignment is just as important as implementing the right tools and processes.
Heard during the summit: The opening keynote emphasized that “the paradox of the data, analytics, and software engineering collision is that the more automation there is, the more — not less — training of staff is required.” This underscores the critical role of change management in ensuring that governance initiatives are adopted and sustained over time.
Bonus Lesson: Supercharging Data Transformation Through Strategic Partnerships #
Mauro Flores from VMO2 shared how partnering with Atlan was instrumental in driving data transformation at scale. Mauro stressed that technology alone is not enough, you need the right mindset and partners to truly drive change. Atlan provided not just the tools but the strategic partnership VMO2 needed.
VMO2 went from zero self-service analytics to embedding a data culture across 16,000 employees in less than a year by centralizing people and best practices first before decentralizing. Atlan helped VMO2 implement a “marketplace” approach where employees can discover data, engage, and adopt new capabilities - leading to 300,000 interactions with data assets in just 3 months.
The partnership focused on empowering users through governance guardrails rather than restrictive controls. This enabled scaling without sacrificing security. Moving forward, the focus is on continued innovation through AI capabilities, driving accountability through data contracts, and doubling down on self-service for both data consumers and producers.
“If I didn’t have a partner next to me to disrupt this business, where we could be really agile, we cannot do it. Right? Because it’s not just about the tool. Do you agree? You cannot change things with the tool. You have to have the right mindset to be able to change it.” - Mauro Flores
The VMO2 story showcases the core lessons from the Gartner D&A Summit: linking governance to business outcomes, driving cultural change, and leveraging partnerships to accelerate success.
Conclusion #
The Gartner Data & Analytics Summit London 2025 painted a vivid picture of the future of data governance in the age of AI. As data leaders, we have a choice: we can either view governance as a cost center, or we can redefine it as a growth engine that unleashes the full potential of AI-powered innovation.
At Atlan, we’re committed to helping our customers make this transformation a reality. By leveraging the powerful lessons from the Gartner summit - from trust-building to federated architectures to responsible AI practices - we believe any organization can maximize their data governance impact and thrive in the AI era.
Ready to start your own governance transformation journey? Sign up for a demo of Atlan and experience the power of a modern, AI-ready data governance platform. Together, let’s redefine what’s possible with data!