Stephen Harris, Field Chief Data and AI Officer for Thoughtspot in the Americas, stated that CFOs must ensure their 'decision intelligence skills' are top-notch to drive strategy and innovation within their enterprises, especially in the era of AI where data interpretation is receiving more attention. According to its official website, Thoughtspot provides an agentic analytics platform that uses AI to deliver data-driven insights for businesses.

In an interview, Harris pointed out that modern CFOs need to fulfill a dual mission: being 'opportunity-minded leaders' capable of driving innovation, while also serving as a counterbalance in financial control, and becoming 'the core for steering toward the best outcomes.' To achieve this, they must 'heavily rely on the North Star—data.'

Laying the Foundation

As AI continues to permeate enterprises, honing data interpretation skills hasclimbed to the top of CFOs' priority lists. According to previous reports from CFO Dive, financial executives now must determine the best use cases for technology while closely monitoring potential risks from AI, making top-tier data skills essential.

Harris stated that to achieve these two goals, financial executives need to rely on a trusted data foundation, and enterprise data leaders must be able to accurately communicate any challenges to the finance department.

Harris is an experienced data professional. According to his LinkedIn profile, he joined Thoughtspot, headquartered in Mountain View, California, in June as Chief Data and AI Officer. Previously, he served as Global Vice President of Cloud Data Science and Growth Analytics at Microsoft; he also held CDO roles at companies such as VMware and Wells Fargo, and held several executive positions at Facebook (now Meta) and Capgemini.

He emphasized that finance and data leaders must have a shared understanding of enterprise priorities, including a unified view of the enterprise data infrastructure, to ensure correct strategic decisions can be made.

In recent years, as enterprises continue to solidify the role of the Chief Data Officer (CDO)—a position still relatively new in the C-suite—building this unified view has become easier. According to MIT Sloan Management Review, citing data from a recent Data & AI Leadership Exchange survey, about 84% of enterprises reported having appointed a CDO or Chief Data and Analytics Officer in 2025 (up from just 12% in 2012), but only about 48% classify the role as mature and successful.

Although the role is still evolving, there is now 'a higher level of respect and clarity' between CFOs and CDOs, Harris said. 'Now, the emergence of AI has created more opportunities for both.'

For example, enterprises that have identified data challenges are often investing 'significant resources' in data governance, quality, and readiness, and such investments can be shaped and led by the finance department.

Harris said: 'I clearly see this as a finance-led opportunity to drive innovation and avoid wasting money on shiny AI initiatives that consume messy, incorrect data and produce poor outputs.'

Reducing Pressure

However, maintaining focus on data is crucial when effectively leveraging new tools like AI. When Harris works with financial leaders to identify data challenges or gaps, 'I try to reduce their pressure.' For example, he does not view data silos as IT nuisances but presents them as profit and loss (P&L) risks.

Harris believes the biggest challenge in fixing poor data infrastructure is leaders trying to solve all problems at once.

Instead, data professionals need to understand the problem and how to achieve the desired strategic outcomes, so as to 'combine structured and unstructured data, identify gaps, and then use that to gain CFO support and drive scale,' he said.