A vast majority of financial services firms are now leveraging generative AI (GenAI) for real-world applications like customer support and content generation, but they’re still wrestling with the infrastructure and talent required to make it truly work at scale.
That’s the key takeaway from Nutanix’s newly released 2025 Financial Services Enterprise Cloud Index (ECI), its seventh annual survey on global enterprise cloud adoption in the sector.
According to the report, nearly every financial institution surveyed is already deploying some form of GenAI in their workflows. Yet while enthusiasm is high, execution remains uneven. A striking 97% of respondents admitted their organisations need to do more to secure GenAI models and applications, highlighting rising concerns around privacy, data leakage, and the risks of poorly governed AI deployment.
“Financial services organisations are turning to containers and hybrid cloud not just as technology upgrades, but as strategic enablers of customer value,” said Lee Caswell, SVP of Product and Solutions Marketing at Nutanix. “These technologies are delivering measurable ROI by powering GenAI applications that enhance fraud detection, strengthen cybersecurity, and elevate customer engagement.”
However, Caswell noted that while GenAI is still central to most firms’ current strategies, some are already moving beyond it. “Our customers are telling us they have moved to adopt agentic AI and are looking to harness its potential across their organisations,” he added—suggesting the sector is evolving faster than the tooling around it.
Infrastructure and integration challenges
The survey, conducted by UK research firm Vanson Bourne in late 2024, polled 1,500 IT and platform engineering leaders across industries and geographies. It was found that 92% of respondents in the financial services sector believe their current IT infrastructure needs improvement to support cloud-native applications and containers effectively.
Although Kubernetes and containerisation are already being used to run GenAI workloads, data silos and a lack of application portability remain roadblocks. These infrastructure limitations are not only slowing AI innovation but also making it more challenging to manage risk and meet compliance requirements.
The skills gap is real—and growing
Despite increasing investment, scaling GenAI from experimentation to production remains a significant challenge. Close to 98% of respondents cited difficulties in operationalising GenAI due to a shortage of skilled personnel. Although 62% are actively recruiting for AI-specific roles, many also see upskilling and training as long-term necessities to sustain momentum.
“The success of AI in financial services won’t come down to tools alone,” said one senior infrastructure leader quoted in the report. “It’s about teams—building, securing, and integrating systems in a way that supports trust and performance.”
Long-term ROI and security concerns
While 58% of respondents expect to see gains from GenAI investments within the next one to three years, 39% anticipate potential losses in the next 12 months, suggesting short-term volatility even as longer-term optimism remains.
Security continues to dominate boardroom conversations. Close 96% say GenAI is reshaping how they approach data security and privacy. Additionally, 90% express concern about the broader IT vendor ecosystem, indicating that third-party risk and data governance are emerging as strategic imperatives.
As financial institutions double down on hybrid cloud and containerisation to enable GenAI, they’re also facing a reckoning around AI safety, skills, and scalability. Nutanix’s findings paint a picture of an industry on the move—but not without friction. In the year ahead, the winners may not be the firms with the flashiest AI tools, but those that invest in the hard work of building trustable, secure, and scalable digital infrastructure.
