Over one-third of financial services institutions say infrastructure performance consistently hinders operations, highlighting challenges in scaling AI across highly regulated environments
Cloudera, the only data and AI platform company that brings AI to data anywhere, today released financial services findings from its latest research report, The Data Readiness Index 2026. The report reveals that while financial institutions are rapidly advancing AI initiatives, many continue to face operational and governance challenges that limit their ability to generate value from data at scale.
Financial institutions are under increasing pressure to modernize operations, combat fraud, strengthen risk management, meet evolving regulatory requirements, and deliver a consistent and personalized customer experience. As institutions expand the use of AI across customer service, compliance, fraud detection, and analytics workflows, success depends on the ability to securely access and govern data across increasingly complex environments.
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The research found that 83% of financial services institutions report having visibility into where their data resides, reflecting significant progress in data management efforts. However, operational barriers remain – 38% of respondents say infrastructure performance consistently hinders operational initiatives, underscoring the challenges of supporting AI and analytics workloads across distributed data environments. Additionally, 20% of respondents identified weak integration into workflows as the leading reason AI and analytics investments fail to deliver expected returns.
Governance remains another area of focus. While 61% of financial services institutions report that all or nearly all of their data is governed, many still struggle to establish the consistency and control required to support AI initiatives while maintaining regulatory compliance.
Despite these challenges, financial institutions remain committed to AI-driven transformation. As institutions move from experimentation to production, data readiness is becoming a critical differentiator, enabling teams to accelerate innovation while maintaining the trust, transparency, and oversight required in highly regulated environments.
“For financial institutions, lasting AI success depends on more than models. It depends on giving AI the context it needs to make accurate and consistent decisions based on trusted, accessible, and well-governed data,” said Jake Bengston, Sr. Director, Industry AI Solutions at Cloudera. “As institutions scale AI across fraud prevention, risk management, compliance, and customer experience, they need the flexibility to bring AI to governed data wherever it resides. That approach improves AI outputs, reduces complexity, strengthens compliance, and accelerates time to value.”
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