If you aspire to be a chief data and analytics officer (CDAO) or a leader of your data team, you will be pleased to know these roles are gaining influence and meeting the challenges of the AI evolution.
These are some of the insights from Deloitte’s 2026 CDAO Survey, which asked data and AI leaders about how their influence is changing amid the AI revolution: 94% expect their influence to grow within the next 12 months, and 36% say this influence will expand significantly. Among these, 65% say AI adoption has made their role more critical and that the role of data leaders within their industry is growing in influence.
Data leaders also see their roles integrating well with their organizations’ needs in the age of AI. For 62%, their responsibilities have completely or mostly aligned with expectations, the survey finds. Another 23% believe their responsibilities are somewhat aligned. Only 15% feel the role they expected turned out to be different from reality.
AI has significantly boosted the profiles of data leaders. A majority (78%) say AI has led them to have more power as decision makers, and 63% state they are the primary drivers of data and analytics decisions. Unlike many technology leadership positions, almost all (94%) expect to be in their current roles 5–10 years from now. “They are the nation’s trailblazers, and bucking the revolving door theory …,” the survey’s authors stated.
Plus, the vast majority (89%) describe their role as one in which they can actively evolve or transform data and AI strategy with full executive support. Only 11% feel they are not the final authority on leading major initiatives.
A significant share of data leaders also report an increase in their responsibilities as AI adoption and demands rise within their organizations. A majority (56%) report they are overseeing larger groups of people involved in AI projects. Another 51% also report a rise in the projects they are managing.
However, when it comes to funding, they are being asked to make do with what they already have: Only 29% have seen increases in their budgets.
Data and analytics skills within the workforce is a problematic area, many data leaders state. One-third of survey respondents (33%) cite building and retaining high-performance teams as a top challenge.
While, as noted above, a majority of data leaders say they have the support of management, a majority (62%) also still believe their organization impedes their leadership efforts by not providing sufficient resources and tools to hire and retain top talent.
The top three skills data leaders seek are AI and data analytics, cited by 48%; product management and data initiatives, needed by 44%; and data science, a demand among 41%.
To ensure that AI generates value and meets expectations, data leaders in the survey recommend organizations take active steps to integrate AI and machine learning into key business processes, as cited by 53%. Another 46% urge improving metrics for AI and data-intensive initiatives, and 41% are in favor of developing a clear data strategy aligned with business objectives.
There’s good news in the data—data leaders have a solid grasp on the process to build such value. A majority (57%) report little or no struggle to build upon data and AI initiatives, while another 38% say there is somewhat of a struggle.
Metrics for measuring the value of AI initiatives are on the rise. Most data leaders (64%) work at companies that have key performance indicators for benchmarking AI success. More than half (53%) measure the business value of AI with direct monetary ROIs.
Governance in the age of AI is also a top concern among data leaders. Tellingly, fewer than one-third (27%) say their organizations have limited safeguards, and another 6% say their organization currently lacks any specific governance guardrails. In addition, only 19% say their organizations have robust policies and guardrail tools. Nearly half (48%) say their organizations have taken tentative steps toward governance. Data modernization has momentum—78% of organizations are actively implementing data modernization with AI, and 22% have plans but have not implemented them yet.