Data Privacy Is CFOs' Top Focus Over AI
Data privacy is CFOs' top focus, edging out artificial intelligence (A), cost-cutting, and even strategic planning for the third year in a row. AI keeps dominating boardroom conversations, but when finance chiefs rank what matters most for the year ahead, a quieter concern still wins out. That finding, drawn from Protiviti's 2026 Global Finance Trends Survey of 902 finance leaders across North America, Europe, and Asia-Pacific, says a lot about where CFO priorities really sit as automation and AI adoption accelerate.
Why Data Privacy Is CFOs' Top Focus
On a 10-point priority scale, survey respondents rated the security and privacy of data at 7.6. It’s the highest score of any finance responsibility, and the same top spot it has held for three consecutive years. That consistency matters. It shows that data privacy isn't a fleeting compliance checkbox; it's a standing operational demand tied directly to how finance teams handle sensitive financial, customer, and vendor data every day.
Part of the explanation is structural. As finance functions lean further into cloud platforms, SaaS tools, and AI-powered systems, they're pulling in more data from more sources, much of it flowing between internal systems and external vendors. Every new integration point is also a new exposure point. Data security, in other words, isn't competing with technology modernization; it's the price of admission for it.
Data Privacy vs AI: How the Two Priorities Compare
The data privacy vs AI comparison is where this year's survey gets interesting. AI adoption has clearly accelerated, with 77% of finance organizations now reporting using AI in some capacity, up sharply from prior years. AI itself jumped from 13th place in CFO priority rankings in 2025 to 6th in 2026, its biggest single-year climb.
Yet even with that surge, AI still trails data privacy, financial planning and profitability analysis, enhanced data analytics, process improvement, and strategic planning. Only 14% of organizations using AI say they're doing so under a formally defined strategy; the rest are experimenting without a clear roadmap. That gap between enthusiasm and structure helps explain why AI, despite the buzz, hasn't overtaken the fundamentals finance leaders have always cared about.
There's also a direct link between the two priorities. Much of finance's AI activity (and its broader automation push) depends on moving data across systems, which is exactly what raises privacy and security stakes. CFOs aren't treating data privacy and AI as separate agenda items, they see privacy risk as a natural byproduct of scaling AI and other digital tools.
CFO Priorities for the Year Ahead
Beyond data privacy, this year's rankings reveal a finance function still anchored in core responsibilities rather than chasing every new technology trend. Financial planning and profitability analysis and reporting came in second (7.3), followed by enhanced data analytics (7.0).
Process Improvement and Analytics Gain Priority
Process improvement held steady at 6.9, underscoring the continued investment finance teams are making in tightening workflows before layering on new tools. Enhanced data analytics, meanwhile, climbed from seventh place a year earlier to third. This signifies that CFOs increasingly see clean, well-organized data as the real differentiator behind better forecasting, profitability insight, and decision-making, with or without AI in the mix.
These two priorities reinforce each other. Process improvement clears out inefficiencies and inconsistent handoffs; enhanced data analytics then turns cleaner data into usable insight. Together they form the groundwork that AI initiatives need in order to deliver anything measurable.
Measuring AI Return on Investment Remains a Challenge
If there's one number that captures why AI still lags behind data privacy on CFO priority lists, it's this: just 35% of finance organizations say they're at least moderately effective at measuring AI return on investment, compared with 45% who say the same about broader business-transformation initiatives.
That's a meaningful gap. It suggests many finance teams are investing in AI tools without a clear read on whether those tools are actually paying off. Interestingly, 64% of organizations report having a formal methodology for measuring returns on technology investments in general, meaning the measurement discipline exists, it just hasn't caught up with AI specifically. Public companies are notably further ahead here than private ones, likely a reflection of tighter reporting requirements and closer investor scrutiny.
Until finance leaders can tie AI spending to concrete, dollar-denominated outcomes, it's reasonable to expect AI will keep trailing more established, easier-to-measure priorities like data privacy and core financial planning.
Data Governance for Finance as Foundation Behind Security
None of this works without solid data governance for finance. Data governance and data quality are the unglamorous groundwork that determines whether analytics, automation, and AI initiatives succeed or stall. Poorly governed data (duplicated records, inconsistent definitions, unclear ownership) undermines forecasting accuracy and makes it harder to enforce consistent security controls across systems.
Protiviti's report frames data governance as foundational to nearly everything else on the CFO's list: profitability analysis, strategic planning, AI deployment, and quality decision-making all depend on it. Strengthening data governance isn't a separate initiative from data privacy, it's the mechanism through which privacy protections actually get enforced day to day.
Privacy and Compliance Take Center Stage
Data privacy doesn't function in isolation from cybersecurity, information security, and regulatory compliance more broadly. As finance systems become more interconnected — spanning ERP platforms, cloud applications, and third-party vendors — the attack surface for potential breaches expands right along with it.
Privacy compliance obligations are also becoming more layered, with finance teams needing to satisfy a growing patchwork of regional and industry-specific rules while still moving fast enough to support the business. That combination of rising cyber risk and rising regulatory complexity is a big part of why information security consistently tops CFO priority lists, year after year.
Cloud and Finance Data Security in Digital Operating Model
Cloud adoption ranked among the top areas CFOs want to strengthen this year, and it's tightly linked to the privacy conversation. As finance organizations shift core processes (forecasting, reporting, reconciliation) onto cloud-based systems, cloud security becomes inseparable from finance data security more broadly.
This is part of a wider shift toward a digital finance operating model, where automation, analytics, and AI all run on shared cloud infrastructure. Protecting that infrastructure protects everything built on top of it, which is exactly why CFOs keep circling back to security and privacy even as they invest in new digital capabilities.
Operational Efficiency and Internal Controls
Finally, none of these priorities exist independently of operational efficiency and internal controls. CFOs are under constant pressure to do more with the same or fewer resources, and strong internal controls are what let finance teams pursue automation and AI without losing oversight over financial data.
Encouragingly, the survey found that proven, established technologies (automation tools, cloud-based systems, and technology rationalization) are currently delivering more measurable cost and efficiency gains than AI and machine learning. That reinforces a consistent theme: finance leaders trust what they can control and measure, and they're extending AI adoption carefully rather than all at once.
Why Trust Will Shape the Future of Finance
Data privacy is CFOs' top focus not because AI isn't important, but because privacy, security, and data governance are the prerequisites for everything else finance wants to accomplish with technology. Until AI's returns are as measurable and its risks as well-understood as those tied to data privacy, it's likely to remain an accelerating priority, just not the top one.
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