As artificial intelligence further permeates daily business processes and application scenarios, CFOs must pay close attention to the data that underpins the AI models supporting their scenario planning, forecasting, and long-term strategy development. Data quality is directly related to the reliability of decisions, so audit discipline over data becomes crucial.

In the age of AI, CFOs should apply the same audit discipline to data as they do to financial data—this is the view of Donna Dror, CEO of Usercentrics. Usercentrics is a consent management platform provider headquartered in Munich.

"If you treat data as a financial asset—and I believe every CFO does now—then privacy and data trust are the governance mechanisms that protect and enhance the value of that asset," Dror said in an interview with CFO Dive.

Building robust privacy infrastructure

Currently, as companies integrate AI tools more broadly, data has become a core focus area for CFOs. Many finance executives' priorities are directly related to AI technologies, such as improving forecasting capabilities or shortening financial close times. However, Dror noted that a major obstacle for CFOs is that "enthusiasm exceeds data maturity." She explained: "I think the disconnect I see is about confidence... because CFOs must trust financial statements, but they cannot place the same trust in the data fed into AI tools."

Dror has served as CEO of Usercentrics since October 2022, having previously joined the company as Chief Revenue Officer in 2021. According to her LinkedIn profile, she spent eight years at software provider Similarweb and has served as an advisor at Full In Partners, a New York private equity and venture capital firm, since May 2019.

Dror said that untrustworthy or ambiguous data can trigger a variety of operational issues within a company—such as exaggerating or distorting forecasts, or exposing the company to material and reputational risks, all of which ultimately impact the bottom line. Therefore, ensuring clean data is crucial for CFOs: finance executives develop strategies around "accuracy, predictability," and risk mitigation. She said: "I think all three of these actually depend on whether your data is consented, complete, and defensible."

Every financial decision must also be traceable to clean, legitimate data. "So, if I were a CFO, I would view privacy infrastructure as the foundation of financial accuracy and brand resilience," Dror said.

Treating compliance as a growth driver

When finance executives examine data more closely, they need to ensure that compliance is a core pillar and leave room for evolving regulations. AI privacy laws in the United States are still in their early stages at both the federal and state levels, while multinational companies must navigate numerous disparate privacy and security laws across different markets.

"The fact is, regulation always lags behind innovation, and we have not yet reached a stage where all data privacy laws fully cover every use case that emerges in the current technological evolution," Dror said.

This means shifting how CFOs think about compliance—although it is often seen as an obstacle to expansion, it can actually "promote growth." Dror cited examples where considering compliance from the outset helps companies better build trust with customers and maintain long-term relationships.

Moreover, "I think retrofitting compliance later is always more costly, so it should be a foundational consideration in current decisions," she said.