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Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →Chief data officers (CDOs) see their influence rising, but Deloitte’s 2025 UK survey reveals a gap between that expectation and their current authority: 87% of respondents report directly into the C-suite, yet 54% say they are less influential than other C-suite leaders. ITPro reports that 44% expect CDOs to become equally influential by the end of the decade. That is a forecast from surveyed CDOs—not proof that their budgets or decision-making power will grow.
What the survey says—and what it does not
Deloitte describes its 2025 report as the fourth annual Chief Data Officer Survey and dates its publication November 24, 2025. Its accessible summary says respondents expect CDO influence to increase over the next five years. ITPro gives the more specific figure: 44% expect CDOs to become equally influential by the end of the decade. “Pivotal” is a headline framing, not a finding that should be mistaken for a guaranteed outcome.
The survey is presented on Deloitte’s UK site. The visible summary does not establish the sample size, fieldwork dates, respondent mix, or whether the figures are directly comparable with previous editions. It also does not show that the findings represent companies without a CDO. Treat the percentages as reported views of surveyed CDOs, not as a universal forecast for every organization.
The contrast between C-suite reporting and perceived influence is more revealing than either number alone. A reporting line can confer access or status without giving a CDO control of budgets, business-unit decisions, or AI investment.
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Why AI is raising the role’s profile
AI makes data leadership more consequential because models depend on data that is reliable, discoverable, appropriately permissioned, and governed. Questions about provenance, privacy, model risk, and explainability also connect data decisions to regulatory and reputational exposure.
ITPro reports that half of surveyed CDOs are accountable or responsible for AI or generative AI, and that three-quarters have AI deployments or experiments operational. Those figures indicate involvement, not necessarily sole ownership or successful scaling. Deloitte reports that 64% saw data initiatives’ impact on AI and analytics improve over the previous 12 months, while budget and resource limits remain a major constraint on AI adoption.
Deloitte identifies data governance as the leading overall priority for the next 12 months, named by 51% of respondents. That helps explain why AI ambition does not eliminate foundational work: governance, data quality, lineage, and ownership can determine whether experiments become dependable operations.
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The CDO role is not one standard job
Deloitte cautions that there is no one-size-fits-all CDO model. The mandate depends on the organization’s maturity, goals, and operating model. In practice, the role may combine several distinct responsibilities:
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- Governance: standards, quality, metadata, lineage, privacy, policy, and compliance controls.
- Transformation: operating-model change, modernization, and data literacy across business teams.
- AI leadership: data readiness, responsible use, experimentation, and moving suitable AI work into production.
- Commercial data: data products, customer insight, personalization, pricing, and potential new revenue.
- Analytics and performance: decision support, measurement, experimentation, and translating analysis into business results.
- Information risk: coordination on provenance, retention, privacy, security, and regulatory exposure.
These responsibilities can be distributed among a CIO, COO, CTO, chief AI officer, privacy leader, risk team, or business-unit executives. A standalone CDO title matters less than whether those accountabilities are explicit and workable.
More data spending does not automatically mean more CDO power
Deloitte reports that 56% of respondents saw overall organizational spending on data increase. Yet the largest proportion said their own CDO budgets had stayed the same. Team growth is more visible: 54% reported an increase in data-team size over the previous year, and 63% expected further growth in the next 12 months. ITPro reports an average expected increase of 27% among respondents anticipating team growth.
Those measures describe different things. Organization-wide data spending may sit with the CIO, cloud infrastructure, AI programs, or business units rather than under the CDO’s discretionary control. More staff can expand delivery capacity, but it does not by itself give the CDO authority to set enterprise priorities or redirect investment.
What is holding CDOs back?
Deloitte reports that 47% identify competing organizational priorities as an obstacle to realizing data’s full value; 48% cite budget and resource limitations as a key challenge to AI adoption. These findings sit alongside reported progress, not in place of it. The likely tension is between rising expectations and the practical work of securing skills, funding, reliable data, and agreement across teams.
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Other common organizational friction points include fragmented ownership, difficulty demonstrating returns from foundational work, and blurred responsibilities among data management, analytics, AI, privacy, and security. If leaders demand quick AI results while deferring data quality and governance, the CDO can be held accountable for outcomes without the authority or resources to make them achievable.
How priorities vary by maturity and sector
The survey summary says more mature organizations give greater prominence to AI and data products, while less mature organizations focus more on governance and data strategy. Among higher-maturity organizations, Deloitte lists AI/generative AI as a priority for 67% and data products for 56%; among lower-maturity organizations, governance is a priority for 63% and data strategy for 41%.
Sector figures reported by ITPro also suggest different mandates: 66% of financial-services respondents named AI or generative AI a top priority, while data governance was a key focus for 50% of corporate CDOs and 70% of public-sector CDOs. These are secondary-source presentations of survey results; the accessible summary does not establish the exact question wording or denominators. They should not be read as a single prescription for every CDO.
Influence is about decision rights, not just access
For a CEO or board assessing whether a CDO has real influence, the practical questions are who can decide, who is accountable, and who controls the resources. Useful indicators include:
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- The CDO can set or enforce enterprise data standards, with named business owners accountable for data quality.
- The CDO participates in prioritizing AI and data investments, with authority to raise concerns about unsafe, noncompliant, or low-quality deployments.
- Data products have accountable owners and identifiable users rather than existing only as platform deliverables.
- Initiatives have agreed business measures, such as adoption, decision quality, productivity, risk reduction, or revenue where relevant.
- Governance and data quality are funded as ongoing capabilities, not treated as a one-time project.
- Accountability for AI outcomes is explicit, and the CDO has appropriate access to executive, risk, audit, or board discussions.
These tests expose trade-offs leaders need to resolve. Central standards can improve consistency, while business-unit autonomy can preserve speed and domain relevance. Strong governance can reduce risk, but controls designed without room for experimentation can slow learning. Likewise, a platform investment may be necessary without being sufficient: the organization still needs owners, adoption, and business outcomes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.CDOs are more likely to share power than replace other executives
The survey does not establish that CDOs will replace CIOs or create a universally independent power center. ITPro reports that 57% of CDOs report to a CIO or COO, compared with 39% the previous year. That points to a role often embedded in technology or operations structures, though the reporting-line figures do not establish how much authority those CDOs hold.
Effective data leadership usually requires coordination with the CIO on infrastructure, the COO on operational execution, the CTO on architecture or product engineering, and risk, privacy, legal, and finance leaders on controls and investment value. Some organizations may ultimately distribute CDO responsibilities across those functions or absorb them into broader roles. A small organization may not need a standalone CDO at all; a large one may have several overlapping data, analytics, digital, and AI executives.
What organizations should do next
- Define the mandate. Write down which standards, investments, policies, and deployment decisions the CDO owns, shares, or advises on.
- Name business data owners. Make quality and stewardship responsibilities part of the business, not solely the data team’s job.
- Connect foundational work to outcomes. Pair governance and quality measures with the decisions, services, or risks they are intended to improve.
- Clarify executive interfaces. Agree how the CDO works with CIO, COO, CTO, AI, privacy, risk, legal, and finance leaders—and how disagreements are resolved.
- Set realistic AI expectations. Prioritize use cases with a path to dependable data and accountable operation rather than treating experimentation as proof of enterprise impact.
- Review authority alongside resources. Track the CDO’s budget and staffing separately from total organizational data spend, and check whether the role can influence the spending that drives its commitments.
The central question is not whether CDOs will have a more prominent title. It is whether organizations will match growing expectations with decision rights, resources, and accountability for results.
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