The financial services sector is poised for a major transformation with generative AI (GenAI). When it comes to managing finances, today’s consumers and businesses expect fast, convenient, and personalized services at their fingertips. But while AI promises to revolutionize the digital experience with capabilities like conversational banking or advanced fraud detection, many financial institutions are not yet prepared to implement such initiatives without significant investment in infrastructure and data management.
Couchbase’s recent survey of 500 global IT leaders uncovered that while financial services organizations will increase IT modernization investment by a third (33%) in 2024, they still feel unprepared for growing data demands.
The rise of GenAI is unlocking new opportunities in the financial sector, with organizations exploring large language models (LLMs) and machine learning to interact with customers in a more personalized, empathetic, and context-aware way. The study revealed that virtually all financial organizations are planning to implement GenAI in 2024 to transform the way they operate. However, almost half (47%) are worried their organizations’ ability to manage data won’t meet the demands of GenAI without significant investment.
GenAI-powered applications can provide the flexibility necessary to meet constantly evolving customer financial needs and goals. Successful implementation hinges on having a reliable data infrastructure capable of providing immediate access to accurate and trustworthy data, or organizations risk making critical errors.
The Couchbase study showed that while there’s a significant push toward AI investment and IT modernization, financial services organizations face infrastructure challenges and concerns, such as legacy systems, AI readiness, and the risk that can accompany fast AI adoption:
- Meeting data demands of GenAI: 44% of financial services organizations do not have all of the elements in place to ensure an all-encompassing data strategy that’s suitable for GenAI. Capabilities such as real-time data access and sharing, vector search for accuracy, and consolidated database infrastructure for trustworthy data management and storage of GenAI conversations are critical for building a strategy that meets GenAI’s data demands.
- Legacy technology hinders modernization efforts: Outdated systems cause project failures, delays, or cancellations, resulting in an average $4.7 million wasted annually and 20-week delays on strategic initiatives at financial organizations.
- Making strategic investments: 76% are increasing investment in AI tools for faster development, and 61% say edge computing is critical to enable new AI applications.
- Rushed AI adoption raises concerns: 68% of financial firms believe most enterprises have rushed to adopt GenAI without proper understanding of what’s needed to use it effectively and safely. Alarmingly, this rush has come at the expense of other critical areas – 46% of enterprises diverted spending from other key areas like IT support and security to meet AI goals.
- Boosting productivity is necessary: 71% of IT departments at financial organizations face pressure to do more with less. With a 32% productivity boost needed simply to stay competitive, this likely contributes to why 98% of respondents have specific goals to use GenAI in 2024.
- Investing in infrastructure: 59% of respondents worry about insufficient compute power and data center infrastructure to support GenAI, while 64% cite corporate social responsibility and environmental responsibilities as adoption barriers. Many are unaware of potential solutions – 64% believe they need multiple databases to have all necessary capabilities for GenAI, despite the existence of solutions that support all multipurpose access needs including vector search features within a single platform.
- End users need adaptability: 53% of financial services firms report being under pressure to continually improve user experiences. The study found that the average consumer-facing application falls behind expectations in 19 months, and the average employee-facing application in 20. To counteract this, 20% of respondents say adaptability – the ability to change what an application offers based on a user’s immediate context – will be the key attribute for applications.
The convergence of GenAI and digital financial services experiences can open new doors for organizations. To fully leverage GenAI, organizations must make strategic data infrastructure investments and choices, which can include multipurpose data platforms. Those who can implement data management strategies that can meet the fast data analytics AI requires will be able to deliver the adaptive, highly personalized, and context-aware experiences that users demand.
Access the full report: Digital Modernization in 2025 – Are data strategies ready for the AI age?
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