Why CDAOs Are Taking Centre Stage as AI Strategy Leaders
Gartner's latest research reveals a significant shift in enterprise leadership: 70% of Chief Data and Analytics Officers (CDAOs) now lead AI strategy. This change highlights the growing importance of data-driven decision-making and AI in business competitiveness.
A Shift in C-suite Dynamics
Data leadership is no longer confined to back-office operations. In 2025, 36% of CDAOs report directly to the CEO, a notable increase from 21% just a year earlier. This trend signals that data executives are becoming key players in shaping corporate strategy and AI initiatives.
Sarah James, Senior Director Analyst at Gartner, points out that CDAOs have a unique advantage. Their cross-organizational insight and expertise in AI-ready data position them to lead and challenge their companies to extract real value from AI projects. This makes the CDAO role central to AI success, bridging data and analytics with business strategy in a way no other executive can.
Key Gartner Statistics on AI Strategy
As investments in AI grow, executive boards demand clear, measurable results. Gartner predicts that by 2027, 75% of CDAOs who fail to prove their essential role in AI success will lose their C-level status. This puts pressure on CDAOs to demonstrate tangible business impact or risk being sidelined.
Gartner’s survey also shows the CDAO role becoming more strategic and established due to the increasing complexity and importance of data management and AI application.
The Future Paths for CDAOs
Gartner identifies three emerging directions for the CDAO role:
- The expert data and analytics leader: Focused on data authority, this leader manages business intelligence, master data, and reporting, often reporting to IT and ensuring an enterprise-wide data perspective.
- The connector CDAO: Acts as a bridge between the C-suite and data/AI teams, embedding analytics into products and services and driving AI initiatives forward.
- The pioneer CDAx: A transformation agent who leads across data, analytics, and AI, emphasizing ethical governance and cross-functional innovation.
Each path requires a mix of business savvy, communication skills, technical knowledge, and change management capabilities. Sarah James advises CDAOs to develop skills aligned with their chosen path to strengthen their leadership position in AI.
From Research to Action: What CDAOs Must Do
To succeed, CDAOs need to:
- Communicate the value of data and AI clearly in business terms.
- Build AI-ready data systems that ensure quality and reliability.
- Collaborate across departments to unify efforts and promote ethical, secure AI development.
The role of the CDAO has shifted from a behind-the-scenes operator to a key architect of AI-driven transformation. Executives in this role who adapt and acquire new skills will lead their organizations to measurable, sustainable success with AI. Those who don’t risk falling behind.
For executives looking to deepen their AI and data strategy expertise, exploring targeted training can provide a practical edge. Resources such as Complete AI Training's latest AI courses offer focused learning paths suited for current and aspiring CDAOs.
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