Donna Dror, CEO of Usercentrics, warns that a foundational element is being overlooked: trusted data, as finance chiefs race to adopt artificial intelligence.
In the boardrooms of today, CFOs are increasingly betting their strategic forecasts and long-term plans on the power of Artificial Intelligence. But this enthusiasm is running into a hard operational truth: the output of an AI model is only as reliable as the data fed into it.
According to Donna Dror, CEO of the consent management platform Usercentrics, this disconnect poses a significant risk. “The biggest disconnect I see is confidence,” Dror explained in a recent interview. “CFOs have to trust a financial statement, but they can’t say the same about data feeding into, for example, AI tools. In many cases, the enthusiasm for AI outpaces data maturity.”
Dror, who has led the Munich-based company since 2022, is advocating for a fundamental shift in how finance leaders view corporate data. She argues that in the age of AI, data must be treated with the same rigor as financial assets.
“If you think of data as a financial asset, which I believe every CFO now does, then privacy and data trust are the governance mechanisms that protect and enhance that asset’s value,” Dror stated.
ALSO READ: THECFO MAGAZINE’S CFO OF THE WEEK: GWEN MUTEIWA OF LETSHEGO HOLDINGS LIMITED
The consequences of ignoring this principle are not merely theoretical. Dror points to a direct impact on the bottom line, where untrustworthy or poorly governed data can inflate forecasts, expose companies to material and reputational risk, and ultimately lead to flawed strategic decisions.
For a CFO, whose role is built on “accuracy, predictability, and risk mitigation,” this is an unacceptable vulnerability.
“I’d say all three of those things really depend on whether your data is consented, complete and defensible,” Dror said.
Her solution is a call for a new discipline in the C-suite. Just as CFOs demand strict, regular audits of their financials, they must now demand the same level of scrutiny for the data fueling their most ambitious AI projects. It’s no longer just a technical issue, but a core financial governance imperative.