The coming year will signal an abrupt transition from digital banking to intelligent finance, as AI agents and operating models reshape the ways that financial firms acquire customers and provide advice.

This is the central thesis of a new Forrester Research report, “Predictions 2027: Banking and Investing.” The findings were summarized from data involving 915 respondents in the U.S., U.K., and Canada.

Forrester identified several key points of transition. These included fundamental changes through automation in financial discovery and guidance journeys, as well as a belief that although one-third of banks will announce an AI transformation program, only 5% will succeed.

“In 2027, financial services will enter a new phase in which intelligence becomes the primary source of value creation,” said Forrester researchers in the report. “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.”

Scaling AI for financial services

Forrester’s prediction of a 5% success rate is based on a belief that many banks will rebrand existing AI initiatives as AI-native without significant changes in operational infrastructure. Retention of legacy processes and operating models will prevent an ability to scale AI deployment, a fundamental requirement that AI technology providers such as Dell Technologies Inc. are emphasizing to their clients in the financial services world.

“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,” according to David Kennedy, chief financial officer of Dell, during a recent interview with theCUBE, SiliconANGLE Media’s livestreaming studio. “The question is, can you do that at scale?”

One way that financial institutions will pursue scale is through mergers and acquisitions. Forrester predicts that AI banking technology M&A will increase by 50% in 2027. Acquisition of proprietary data assets, governance capabilities, and AI-native orchestration will require an ability to navigate hybrid computing environments, a need that compute providers such as Advanced Micro Devices Inc. has seen among its own customers.

“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,” said Suresh Andani, corporate vice president of compute and enterprise AI at AMD, in an interview with theCUBE. “Every enterprise conversation I’m in, that’s a key topic of discussion.”

Another key topic involves AI agents and their growing influence in the enterprise. According to Forrester’s findings, 40% of banks will launch AI assistants next year. The challenge for many financial institutions will be leveraging AI assistants to deliver differentiated guidance using proprietary data, decisioning and specialist expertise to guide customers. This is where keeping proprietary knowledge in-house can become a distinct advantage, 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.”

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