In today’s volatile economic climate, organizations are increasingly turning to data-driven solutions to improve efficiencies and maintain a competitive edge amid uncertainty. This heightened focus on enterprise data is creating new opportunities for Chief Data & Analytics Officers (CDAOs) to deliver business value. As one CDAO community member noted, “Data and analytics will become even more important in decision making and strategic planning. AI and automation will become a necessity for labor efficiency.”
However, as enterprises accelerate toward an AI-driven future, CDAOs are encountering unprecedented challenges. Many report difficulties in managing expectations from executives and business partners, while budget constraints and limited resources continue to hinder progress.
Each year, we survey CDAOs within our communities to uncover their key priorities and challenges – both within their function and across the enterprise. In early 2025, 350 CDAOs identified AI, data and analytics strategy, and data governance as their top priorities. Today, with insights from more than 850 CDAOs, these priorities remain consistent.
Here, we provide an in-depth analysis of the top three priorities for CDAOs in 2025, based on findings from our Leadership Perspective Survey of 850 CDAOs.
Top Functional Priorities for CDAOs
The top three functional priorities for CDAOs in 2025 remain unchanged from 2024. For the second year in a row, Generative and Traditional AI tops the list, following its introduction to the survey in 2024. Since the launch of ChatGPT in late 2023, AI has become a central focus for our community members, with discussions evolving from early experimentation and use cases to realizing tangible ROI from AI initiatives.
Data and Analytics Strategy holds steady as the second highest priority. As organizations continue their journey toward becoming more data- and AI-driven, CDAOs are focused on developing D&A strategies that align with business objectives and deliver measurable outcomes.
Data Governance ranks as the third priority, maintaining its position as a top focus area for five consecutive years. With the growing complexity of the D&A landscape, establishing a robust governance framework has become more critical than ever to support enterprise transformation.
Rounding out the top five priorities are Data-Driven Culture and Fluency and Data Democratization and Self-Service. These priorities reflect CDAOs’ ongoing commitment to change management and the human side of data, ensuring that transformation efforts are both sustainable and scalable.
Next, we take a closer look at each of the top three priorities for CDAOs, examining the key opportunities and challenges they have identified in these areas.
Leading Generative & Traditional AI Across the Organization
As AI evolves from traditional models to generative and agentic AI, a Gartner survey shows that 70% of CDAOs are now responsible for their organizations’ AI strategy and operating models. With deep expertise in AI and a clear understanding of cross-functional data needs, CDAOs are uniquely positioned to lead enterprise AI initiatives – and many are embracing this opportunity.
Beyond the technical aspects, CDAOs are also taking on the role of AI “evangelists” within their organizations. As Matt Griffiths, CTO at Stanley Black & Decker and Co-Chair of the Boston CDAO Community, explains, D&A leaders must be the voice of AI as the “art of the possible.” Success, he emphasizes, depends on the ability to “communicate, communicate, communicate.”
CDAOs’ overarching goal with AI is to drive better business outcomes, but the rapidly changing AI landscape remains their biggest challenge. Additional goals and challenges cited by CDAOs include:
Goals for Generative & Traditional AI
64% Improving business outcomes
60% Improving processes and efficiencies
46% Delivering and defining value
Challenges around Generative & Traditional AI
46% Quickly changing landscape
42% Lack of skills
35% Competing Priorities
Following the survey, we held hundreds of follow-up conversations with CDAOs to gain deeper insights into their priorities and challenges. Here is a sample of what they shared about AI:
We’re focused on three things going forward: 50% of time on AI building and AI products, 45% for productivity and different tools and compliance, and 5% of time trying to figure out what is the unique thing that AI brings to the table.
There’s a desire for practical, short-term wins with AI and analytics – use cases that demonstrate value quickly, not just long-term transformation.
We have a strong organizational focus on increasing AI literacy, particularly among the board and executive leadership, to clarify the differences between traditional AI and generative AI and to foster a data-driven culture.
Building a Value-Driven Data & Analytics Strategy
In 2025, CEOs are focusing on driving growth through AI adoption, and as a result, the proportion of CDAOs reporting directly to the CEO has risen to 36%, up from 21% in 2024. With significant investments in AI initiatives, data and analytics leaders are aligning their strategies with broader business objectives to deliver tangible value.
As AI becomes increasingly integrated across the organization, CDAOs are collaborating with key business leaders – from IT and Finance to HR and beyond – to ensure the safe deployment of AI and return on investment.
Below are the primary goals and challenges CDAOs face in developing data and analytics strategies. Two-thirds cite improving business outcomes as a top goal, while competing priorities is the greatest challenge.
Goals for Data & Analytics Strategy
66% Improving business outcomes
59% Making data-driven decisions
52% Delivering and defining value
Challenges around Data & Analytics Strategy
42% Competing priorities
40% Siloed operating model
32% Company culture
After the survey, CDAOs shared further insights into their data and analytics strategies:
The ultimate goal is to embed data strategy and literacy so deeply that they become second nature, enabling colleagues to ask the right questions, utilize AI effectively, and dig deeper into data insights.
There’s a need to make analytics more business-savvy and proactive, rather than waiting for top-down requests.
Our strategic priorities are shaped by regulatory requirements, business outcomes, and the need for robust oversight. Effective data strategies require practical execution plans, including clear funding, capacity planning, and technology enablement.
Strengthening Data & Analytics Governance
As CDAOs face mounting pressure to advance AI and sophisticated data and analytics initiatives, there is widespread agreement on the need to reinforce foundational practices – particularly data governance. During a recent Town Hall on “Data Management for AI Success” with the Southern California CDAO Community, data governance emerged as the central theme. As one CDAO remarked, “You can have innovation and get more intelligent about your data – but data governance is at the core.”
Historically, data governance has been a significant challenge due to its complexity and the difficulty in demonstrating ROI for necessary investments. However, the surge in AI adoption has brought renewed attention to critical elements such as data quality, observability, and stewardship, which are essential for effective AI governance frameworks. This shift is opening the door to increased investment in governance capabilities.
For CDAOs, the primary goal of data and analytics governance is to improve processes and efficiencies, while their greatest challenge remains competing priorities.
Goals for Data & Analytics Governance
55% Improving processes and efficiencies
49% Improving business outcomes
48% Making data-driven decisions
Challenges around Data & Analytics Governance
40% Competing priorities
39% Siloed operating model
38% Company culture
CDAOs offered the following perspectives on enhancing data governance:
The focus is on practical, resource-conscious data management and governance. There’s a strong need for better documentation, metadata, and data stewardship, but with limited staff and budget, much is still manual or done in Excel. The intersection of IT and data governance is a challenge, especially in clarifying ownership and collaboration.
The transition from traditional data governance to AI governance is still evolving, with ongoing tension between innovation and regulatory controls.
Success requires aligning governance tasks with business objectives and performance measures, spreading adoption incrementally, and connecting governance to business value at every stage of maturity.
CDAOs’ Priorities Across the Enterprise
Each year, we ask executives across the C-suite to share their enterprise-wide priorities alongside their functional goals and challenges. This year, CDAOs joined their C-suite peers in identifying driving growth as their top enterprise priority. In 2024, increasing operational efficiency and productivity was the leading focus for all C-level leaders, and it remains the second highest priority for most roles, including CDAOs.
The third most important enterprise priority for CDAOs is optimizing or reducing costs – a reflection of the current volatile economic climate, which has led many organizations to face budget cuts and resource constraints. Rounding out the top five are increasing revenue and improving customer experience.
Below is a snapshot of the top enterprise initiatives for CDAOs and their fellow C-level executives.
The Outlook for CDAOs
CDAOs are at the forefront of driving enterprise transformation through data, analytics, and AI. As organizations navigate economic uncertainty and accelerate AI adoption, CDAOs are uniquely positioned to deliver business value, shape strategy, and foster a data-driven culture.
With a focus on advancing generative and traditional AI, building value-driven data and analytics strategies, and strengthening data governance frameworks, CDAOs play a pivotal role in bridging technology and business objectives. Achieving success will require CDAOs to effectively communicate the value of data and AI, collaborate across functions, and embed robust governance practices.
One CDAO captured this sentiment, stating, “We have aggressively implemented AI, with hundreds of use cases in the pipeline and dozens in active development. The challenge now is not just technical, but also organizational – ensuring robust AI governance, automating controls, and evolving team structures to keep pace with changing technology and business needs.”
The insights from over 850 CDAOs showcase a roadmap for the future: focus on business outcomes, invest in AI and data capabilities, and build resilient governance structures. As the data and analytics landscape continues to evolve, CDAOs will remain essential to driving enterprise success and shaping the strategic direction of their organizations.
Stay up-to-date with your CDAO peers on key topics and initiatives by joining the regional Gartner CDAO community near you. If you are already a community member, explore opportunities to connect with other CDAOs at an upcoming event.
This article is an update to a previous report, which you can find here: Top Priorities for CDAOs in 2024.
Based on 850 CDAOs’ responses to Gartner C-level Communities' 2025 Leadership Perspective Survey.
By CDAOs, For CDAOs™
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