Forrester: AI agents will drive financial services transformation, but only 5% of banks will execute successfully

Financial services firms face a pivotal moment as artificial intelligence agents and new operating models begin to reshape how they attract customers and deliver guidance. That's the core finding of Forrester Research's latest report, "Predictions 2027: Banking and Investing," which draws on survey responses from 915 participants across the U.S., U.K., and Canada.

The research highlights several critical transition points ahead. Automation will fundamentally alter how customers discover and receive financial guidance, yet Forrester's analysis reveals a stark reality: while one-third of banks plan to announce an AI transformation initiative, only 5% are expected to achieve meaningful success.

In 2027, financial services will enter a new phase in which intelligence becomes the primary source of value creation. AI assistants are reshaping how customers discover, evaluate and act on financial products; investment participation is expanding despite persistent economic anxiety; and banks are racing to determine whether AI will merely enhance existing operations or fundamentally transform them.

Forrester researchers

Scaling AI for financial services

Forrester attributes the low success rate to a widespread tendency among financial institutions to rebrand existing AI programs as AI-native without overhauling underlying operational infrastructure. Clinging to legacy processes and organizational structures will constrain the ability to deploy AI at scale—a capability that technology vendors like Dell Technologies Inc. are actively promoting to their financial services clients.

David Kennedy, chief financial officer of Dell, emphasized this challenge in a recent conversation with theCUBE, SiliconANGLE Media's livestreaming platform. "Ultimately, I think we've enough proof points now that AI works and it works really well and it gives you speed and efficiency in your company," Kennedy said. "The question is, can you do that at scale?"

Mergers and acquisitions represent one avenue through which financial institutions will pursue scale. Forrester forecasts that AI banking technology M&A activity will surge by 50% in 2027, driven by the need to acquire proprietary data assets, governance frameworks, and AI-native orchestration capabilities. Successfully integrating these acquisitions will require financial firms to navigate hybrid computing environments—a challenge that compute infrastructure providers such as Advanced Micro Devices Inc. are observing among their customer base.

Suresh Andani, corporate vice president of compute and enterprise AI at AMD, discussed this trend during an interview with theCUBE. "As a provider of AI compute, we want to make sure that we are enabling those enterprises to not only run their AI tasks through the frontier APIs in the cloud, but we are providing them infrastructure that they can host open-weight models very efficiently on-prem," Andani explained. "Every enterprise conversation I'm in, that's a key topic of discussion."

AI agents themselves will become increasingly central to financial services operations. Forrester predicts that 40% of banks will roll out AI assistants in the coming year. The real challenge lies in using these assistants to deliver distinctive guidance grounded in proprietary data, decision-making processes, and specialized expertise. Maintaining proprietary knowledge internally can provide a significant competitive edge, according to John Roese, global chief technology officer and chief AI officer of Dell.

"It doesn't mean you can't use frontier models and open models," Roese told theCUBE. "It just means that when you design your AI system, you need to realize that the thing that is your moat is not the actual tools. It's not even the models. It's the special knowledge that's now manifesting in these new forms that really captured what you know and do differently than your competitors."