Earlier this month, I had the opportunity to attend the Gartner Data & Analytics Summit 2025 in London. Over three days of engaging sessions and dynamic keynotes, one statement we’ve been emphasising to customers for years stood out: data is no longer a back-office concern it’s a boardroom priority.
Below are the top takeaways I believe are most relevant for organisations navigating today’s evolving data landscape.
1. Trust Is the New Data Currency
Trust emerged as the defining theme of the summit. Whether it’s trusting your data, your AI models, or the agents acting on your behalf building confidence in what we see, what we share, and what we automate is critical. A standout moment was a keynote exercise where attendees were asked to unlock their phones and swap them with a stranger a powerful reminder of how personal and uncomfortable trust can be.
In our world, trust in data means robust governance, transparency, and accountability. Without trusted inputs, any AI-driven outcome is on shaky ground.
2. Governance Moves Beyond IT
There was a strong push toward democratising data governance. Organisations are now encouraged to embed ownership across the business. That means business leaders not just IT need to act as data stewards. Encouragingly, we’re seeing clients proactively embrace tools like Microsoft Purview to facilitate this shift, aligning technical metadata with business context to create meaning and manage risk.
3. Human-in-the-Loop Is a Necessity (For Now)
AI continues to accelerate, but full automation is still a distant dream. Today, human oversight is not only necessary for compliance it’s crucial for building user confidence. That said, Gartner introduced the idea of “guardian agents” AI agents that supervise other AI agents. It’s a practical vision for scalable oversight in a future where no human could possibly monitor every automated decision.
4. Organisational Change is the True Enabler
No technology transformation succeeds without people. One of the most impactful messages from the summit was this: “Bet big on organisational change.” Upskilling, communication, and supporting employees through role evolution is as important as any tool or platform. This includes new hybrid roles like data translators who bridge the gap between analytics and decision-making.
5. Data Products Are Going Mainstream
The concept of “data as a product” is gaining serious traction. The key idea? If data will be used more than once, it should be treated like a product with a roadmap, stakeholders, performance metrics, and a value proposition. MVP thinking is central here start small, measure impact, and scale strategically.
6. Metadata Is the New Backbone
While we’ve long championed meta data-driven architectures, Gartner reinforced how critical this remains. From cataloguing and lineage to automated discovery and AI readiness, metadata is the key to turning raw data into actionable intelligence. It’s not just about technology it’s about making data understandable and useful at scale.
7. Data Fabric Isn’t Just a Buzzword
Multimodal data fabrics designed to connect structured, semi-structured, and unstructured data are laying the foundation for the next generation of analytics. Rather than centralising everything, the emphasis is on connecting data meaningfully, reducing duplication, and enabling analysis where the data lives.
8. Agentic AI & Natural Interfaces Are Coming Fast
Gartner predicts a future with fewer dashboards and more dialogue. AI agents capable of understanding natural language queries are beginning to replace traditional user interfaces. While early efforts like Power BI’s Q&A feature have laid the groundwork, what’s coming is more adaptive, conversational, and embedded in daily workflows.
9. AI Must Be Composite, Not Just Generative
It’s tempting to equate AI solely with large language models. But Gartner reminded us that real-world AI solutions must be composite combining traditional machine learning, symbolic reasoning, and graph-based intelligence to deliver more nuanced, explainable results.
10. Decision Intelligence Is the Destination
Ultimately, the goal is not dashboards, but decisions. Decision Intelligence platforms designed to augment, accelerate, or automate decisions represent the next frontier. But this raises ethical and legal questions around transparency, fairness, and accountability. Organisations must tackle these concerns head on if they hope to build lasting trust in automated decision making.
Final Thoughts
If I had to summarise the conference in one sentence, it would be this, “Data and AI is maturing rapidly but success depends on trust, governance, and people, all key elements of our Data Culture Methodology.”
As leaders in data transformation, we need to guide our clients beyond the hype and into the practical, ethical, and human centred use of data and AI. It’s an exciting time and if the energy at Gartner’s summit was any indication, the best is yet to come.