KEY POINTS
Financial services are investing heavily in generative AI, but outdated infrastructure and data silos pose significant challenges.
A Broadridge study shows 72% of financial leaders plan substantial AI investments, yet foundational tech like cloud and cybersecurity remain top prerequisite priorities.
"As financial services firms modernize their operations and move away from legacy systems, many are realizing that the right data management strategy has the power to break down silos and achieve the level of data quality needed to realize the potential of AI"
The financial services industry is chasing the transformative promise of generative AI, but the pursuit is forcing an expensive reckoning with aging infrastructure and fragmented data.
While investment in AI capabilities is surging, a new study from global Fintech leader Broadridge Financial Solutions reveals banks’ struggles. The report finds that financial institutions are simultaneously doubling down on foundational cloud, data, and cybersecurity upgrades, acknowledging that the path to AI runs through modernizing entire core systems.
AI spending surges, but foundations first: The focus on fundamentals comes as institutions like Bank of America begin reporting tangible efficiency gains from early, practical AI deployments, even as broader transformation remains hampered by legacy constraints. Planned investments in generative AI are soaring, with 72% of financial services technology and operations leaders globally planning moderate to large investments this year—nearly double the 40% reported in 2024—according to the fifth annual Digital Transformation & Next-Gen Technology Study .
The study, which surveyed over 500 executives, found high expectations for returns, with 68% believing GenAI will primarily boost employee productivity and 35% expecting ROI within six months. However, despite the GenAI buzz, foundational technologies remain the top spending priorities, with over 80% of respondents ranking cybersecurity, analytics, and cloud platforms as key investment areas.
"Cloud is king and there’s still a heavy emphasis on foundational technologies,” Broadridge Chief Product and Strategy Officer Germán Soto Sanchez told Cybersecurity Dive.
Confronting the legacy drag: This continued focus on the basics underscores a crucial challenge: many firms are realizing their AI ambitions are capped by outdated systems and siloed information. The Broadridge study found that 46% of executives feel legacy technology is hurting their operational resiliency, and nearly half (41%) grapple with data silos, while 2 in 5 report data quality issues.
"As financial services firms modernize their operations and move away from legacy systems, many are realizing that the right data management strategy has the power to break down silos, and achieve the level of data quality needed to realize the potential of AI," said Chris Perry, President of Broadridge, in a company press release. Over half (58%) identified data harmonization as the ideal driver for maximizing ROI.
"Firms are starting to recognize that they cannot realistically rewrite every single asset they have"
Pragmatic paths yield results: Illustrating the potential for targeted AI applications, Bank of America announced that it is directing approximately $4 billion of its $13 billion annual technology budget toward new initiatives, including AI, in 2025. In a news release, the bank detailed significant efficiency gains from AI tools already deployed. Its internal AI assistant, Erica for Employees, is used by over 90% of staff and has cut IT service desk calls by more than 50%.
Meanwhile, software developers using a GenAI coding assistant experienced efficiency gains exceeding 20%, and other AI tools are streamlining tasks like summarizing client feedback calls and preparing materials for business client meetings. "AI is having a transformative effect on employee efficiency and operational excellence,” said Aditya Bhasin, BofA’s Chief Technology & Information Officer.
Modernization is a prerequisite: The challenge lies in integrating AI effectively across complex organizations still reliant on older systems. "Firms are starting to recognize that they cannot realistically rewrite every single asset they have," Broadridge Global Head of Engineering Jason Birmingham noted in the company’s report. The focus is shifting towards building robust data platforms and leveraging the cloud not just for AI, but for overall operational resilience and efficiency – a foundational necessity before the full potential of AI can be unlocked across the financial services landscape.
