All 2026 Conference Sessions

7 Practical Actions to Improve Data Governance Now

Speakers:

• Sally Parker, Sr Director Analyst, Gartner

Key takeaways

• “Organizations with low data governance maturity are significantly more likely to be among those that will fail to realize AI value in the near future.”
• Practical ways to improve data governance:
  • “Understand the purpose behind data governance in the organization. D&A leaders should start by identifying business outcomes first.”
  • “Deliver incremental value. Focus effort on prioritized business outcomes to accelerate ROI and minimize the required effort.”
  • “Rebrand governance as a team sport to help secure the necessary participants’ involvement in data governance activities.”
  • “Embed governance and culture activity into business workstreams as part of normal operations. Only 26% of organizations incorporate culture and communication into their D&A governance strategy.”

The Future of D&A Governance

Speakers:

• Anurag Raj, Director Analyst, Gartner

Key takeaways

• "Data governance will be the single point of failure for organizations’ AI ambitions.”
• “The core principles of D&A governance (stewardship, decision rights, accountability) are as critical now as ever. As data environments become more complex, governance models must evolve from simple, distributed controls to sophisticated, adaptive frameworks.”
• “The fundamentals of D&A governance (clarity, integrity, trust) don’t just remain; they become even more essential. It’s innovation in these fundamentals that enables organizations to scale and adapt.”
• There are five best practices organizations should follow to adapt D&A governance for the future:
  • Be explicitly business-outcome and risk driven
  • Scale adaptive governance of data and derived assets
  • Implement an integrated governance operating model
  • Ensure diversified and dynamic stewardship
  • Implement technology-enforced behavioral controls

Signature Series: Get Ready for Data and Analytics 2030

Speakers:

• Rita Sallam, Distinguished VP Analyst, Chief of Research, Gartner

Key takeaways

• “Chief data and analytics officers (CDAOs) and other D&A leaders play a critical role in AI success or risk failure.”
• “Through 2030, responding to this imperative will require shifts in how the D&A team organizes and works, builds and scales and creates value.”
• Shift #1: Create Value Compounding through Agentic Transformation

   

  • “Shift to becoming an AI‑first D&A organization. This starts with an explicit AI ambition — one that uses AI to transform, not simply optimize, business and operating models.”
• Shift #2: Treat Context as Critical Infrastructure

   

  • “Evolve your data foundation with context as critical infrastructure so AI agents operate with trusted situational awareness. D&A success is not about better models — it is about giving agents governed, contextual access to the right data.”
• Shift #3: Establish Trust as Catalyst of Value and Innovation

   

  - “Without trust in the data, outputs and decisions of AI models and agents, there is no value from AI.”