More than two-thirds (76%) of financial services operations leaders in the U.S. believe that using AI would enable them to make faster, more effective decisions, but 62% lack the data management capabilities and data environment to capitalize on the technology’s potential. That is according to a new international study commissioned by ActiveOps, a leading provider of AI-powered decision intelligence for service operations.

According to the Censuswide survey, which gathered insights from Chief Operating Officers, Chief Financial Officers, and senior heads of operations within the U.S. financial services sector, roughly 50% are unable to access real-time data, and two-thirds have legacy data environments that aren’t suited to AI. Data is often poorly classified and siloed across the organization, making it difficult to derive insights and make decisions.

The findings, which are shared in an ActiveOps report titled Ready Or Not AI Is Here, reveal that too many financial services leaders in the U.S. struggle to get any meaningful insights from their operational data. Around 80% believe it takes “significant effort” to derive meaning from their data, and one in four are basing critical business decisions on data that is two to three weeks old. This is leading to what the report calls “decision paralysis”, and is holding businesses back from adopting AI and using it to its fullest potential.

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AI cannot function effectively without the right kind of data environment. Data must be current, contextualized, and classified in order for AI to perform, and must be accessible holistically throughout the organization. While interest in AI among financial services leaders is soaring, roughly half lack access to this kind of data and two-thirds have data environments that are not AI-ready.

Summary of key findings:

76% believe that if they were using AI, it would enable more effective decision-making
62% don’t have the data and environment to fully capitalize on AI
4 in 5 believe it takes significant effort to get insights from their operational data
1 in 4 base their decisions on data that is at least two weeks old

This friction when it comes to AI adoption is not unique to the U.S. The same study, which looked at several countries including Canada, New Zealand, Australia and the United Kingdom, found that, globally, 98% of respondents face significant challenges when adopting AI for gathering, analyzing, and reporting data.

“These findings clearly demonstrate a willingness to embrace AI among financial services operations leaders in the U.S.,” comments Spencer O’Leary, CEO North America at ActiveOps. “However, in order to truly capitalize on AI, organizations must lay the groundwork and ensure that their data environments are organized and well optimized. There is a long road ahead, even for early adopters, and there is a real risk that bad data could leave some behind the AI curve. AI will change the game, but only if we play by the right set of rules.”