Dive Brief:
- Financial firms want stronger AI governance to achieve measurable returns on investments in the technology, according to a FICO and Corinium Global Intelligence study published last week. The two companies surveyed more than 250 bank technology executives during Q2 2025.
- Nearly two-thirds of the 129 CIOs and CTOs surveyed cited lack of predictability as a barrier to scaling AI capabilities and more than half pointed to inadequate model monitoring. Almost three-quarters of the 125 chief analytics and AI officers surveyed said their organization lacked sufficient collaboration between business and IT teams.
- “Proper development and operationalization of AI is extremely hard,” FICO Chief Analytics Officer Scott Zoldi said in the report. “It actually makes software engineering look easy, because software has structure and well-established processes. Most companies haven’t built that for AI.”
Dive Insight:
Banks are bullish on the benefits of AI and wary of the risks inherent in rapid adoption. As proof-of-concept pilots proliferate, the industry is gravitating toward standards of practice and executive oversight to safely scale capabilities that bring a return on growing AI investments.
The number of use cases launched by 50 of the largest global financial companies shot up during the first half of the year, according to an Evident Insights report published last month.
Alongside experimentation, banks also worked on shaping oversight protocols and ethics guidelines, a March report by the analyst firm found. Hiring of AI governance professionals spread across the 50 banks tracked by Evident and 33 had filled executive-level AI positions.
“Governance is beginning to hit its stride,” JoAnn Stonier, fellow of data and AI at Mastercard, said in the FICO-Corinium report. “These committees really only got going at the end of 2023 or start of 2024 — so they’ve had about 18 months.”
AI governance has a lot of ground yet to cover, as agentic solutions join generative AI and machine learning on the automation menu.
Only 7% of the executives surveyed by FICO and Corinium said their organization has fully integrated model monitoring standards. Just a little over 5% of respondents reported strong alignment between AI initiatives and business goals.
The disconnect can extend into the technology function, according to State Street VP of Automation and AI Barbara Widholm.
“The fragmentation between chief AI officers and chief technology officers is a major barrier to value realization,” Widholm said in the report. “Tech-led solutions often lack strategic or data nuance, while AI-led initiatives can miss infrastructure constraints.”
AI and analytics leaders are on the same page with CIOs and CTOs when it comes to AI risks. Both groups registered high levels of concern about the consequences of AI deployments that fail or misbehave. More than 3 in 5 tech chiefs were worried that AI hype might lead their organization to lay off necessary staff.
The two groups also saw eye-to-eye on the areas that provide the most opportunity for collaboration: data security and AI governance. Managing business stakeholder expectations was another area more than half of respondents saw as ripe for ongoing alliance.
“Many organizations lack a clear line of demarcation around how AI decisions get made,” Zoldi said. “If you don’t have an AI board, if you don’t have AI governance, and you let each silo decide for itself — what you get is confusion.”
