With artificial intelligence seeping further into everyday business processes and use cases, it’s critical for CFOs to pay close attention to the data feeding the AI models that help them scenario plan, create forecasts and develop long-term strategies.
In the age of artificial intelligence, CFOs should demand the same audit discipline for data that they do for financials, according to Donna Dror, CEO of Usercentrics.
“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,” she told CFO Dive in an interview.
Developing a robust privacy infrastructure
Data is a crucial area of focus for CFOs today as they integrate AI tools more widely into their companies, with many finance chiefs’ prioritiesdirectly tied to the technology. Finance chiefs today are excited about the many ways in which AI could potentially benefit their companies, whether it’s improving forecasting or helping to cut down on the time it takes for the financial close.
However, one of the barriers CFOs today find themselves facing is “that enthusiasm outpaces data maturity,” Dror said. “I think the biggest disconnect I see is confidence…because CFOs have to trust a financial statement, but they can't say the same about data feeding into, for example, AI tools.”
Dror has served in the top executive seat for the Munich-based consent management platform since October 2022, first joining Usercentrics as its chief revenue officer in 2021, according to her LinkedIn profile. Her past experiences include an eight-year tenure at fellow software provider Similarweb, and she has acted as an advisor with New York-based private equity and venture capital firm Full In Partners since May 2019.
Untrustworthy or unclear data can contribute to a number of operational issues inside of a business — inflating or distorting forecasts, for example, or exposing companies to both material and reputational risks, which all ultimately impact the bottom line, Dror said. For CFOs, that puts a premium on ensuring clean data: finance chiefs build strategies around “accuracy, predictability,” and risk mitigation, Dror said. “I’d say all three of those things really depend on whether your data is consented, complete and defensible.”
Every financial decision must also be traced back to clean, legitimate data, “so if I'm CFO, I'm going to view privacy infrastructure as part of the foundation of financial accuracy and brand resilience,” Dror said.
Compliance as a growth driver
As finance chiefs take closer looks at their data, they need to be sure they are treating compliance as a core pillar, in a way that allows space for shifting regulations. AI privacy laws in the U.S. are still in their nascent phase both on a federal and state level, while global businesses need to grapple with a host of differing privacy and security laws across disparate markets.
The “truth of the matter is regulation always comes off the innovation, and we're not yet at the point where all of these data privacy laws are fully extending to every use case that now exists in the technological evolution that we're experiencing,” Dror said.
That means shifting how CFOs think about compliance — which, despite often being perceived as a barrier to expansion, can “fuel growth, Dror said. Keeping compliance in mind from the start can help businesses better create trust with their customers and build lasting relationships, for example, she said.
Additionally, “I think that the cost of retrofitting compliance later is always more expensive, so that's something that I think should be foundational to how these decisions are made now,” she said.
