A new report commissioned by KlariVis, a leading performance intelligence platform for financial institutions, and conducted by Cornerstone Advisors, has revealed a significant challenge facing community banks and credit unions: most are not yet prepared to fully leverage artificial intelligence. The study points to poor data quality and outdated infrastructure as the core obstacles holding institutions back.
The findings emphasize a critical truth AI can only be as powerful as the data fueling it. Many financial institutions are still relying on fragmented systems and inconsistent data practices, making it nearly impossible to generate meaningful results from AI initiatives.
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The report, titled “Improving Your Financial Institution’s Data Execution Quality (EQ),” surveyed more than 120 banks and credit unions to evaluate how effectively they manage and use data across essential business functions. The results show that the average institution scored just 241 out of 500 on Cornerstone’s Data Execution Quality (EQ) index—placing most organizations only halfway toward optimal data maturity.
Even though over one-third of community institutions have already adopted AI tools like chatbots, and another quarter are experimenting with generative AI, the research makes it clear that these efforts are unlikely to deliver value without stronger data foundations.
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“AI holds tremendous promise for community banks and credit unions,” said Kim Snyder, founder and CEO of KlariVis. “But institutions cannot expect meaningful results when working with fragmented systems and inconsistent data. Improving data visibility and data quality must come first.”
The report also highlights a direct link between a financial institution’s data EQ and its AI readiness. Banks and credit unions with higher EQ scores tend to treat data as a strategic asset, encourage data-driven decision-making, and regularly evaluate their data strategy.
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“There is no AI strategy without a data strategy,” said Ron Shevlin, Chief Research Officer at Cornerstone Advisors and author of the report. “Organizations that invest in better data quality, governance, and accessibility will be the ones positioned to unlock real value from AI.”
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