Weak foundations hinder banks’ AI value

Strategy, data, and talent determine AI returns.

Financial institutions risk missing the full value of artificial intelligence unless they strengthen their strategic clarity, data foundations, regulatory controls, and talent readiness, according to EY’s Nitin Datta, Financial Services Technology Consulting Partner, speaking at the sidelines of the Singapore FinTech Festival 2025.

Datta said organisations must evaluate AI success through both financial and non-financial measures. “There are a few metrics that banks and insurance companies and financial services are looking at, measuring return on investment or returns on future. It's both financial and non financial,” he said. 

Financial impacts include “new business growth, cost of delivery, as well as in terms of the productivity gains,” while non-financial indicators focus on adoption. “It's more in terms of how the change management has happened with the adoption of AI Gen AI,” he added, noting that firms should compare baseline employee usage with current levels to measure cultural shift.

According to Datta, institutions that succeed with AI distinguish themselves early through clarity of purpose. “It would be the strategy and the clarity in terms of the ambition in which they want to achieve from Ai Gen AI… that clarity is very, very key,” he said. Scalable, high-quality data is another differentiator, along with embedding regulatory controls into AI platforms. He noted that “practically implementing regulatory controls and guidelines… has also been another key differentiator.”

Talent strength remains a critical determinant of impact. Success depends on “the availability of talent… from an adoption perspective,” Datta said, adding that organisations with strong collaboration between business and technology teams achieve better outcomes. He stressed that AI should be seen as an enabler, not an end goal.

To maximise business value, firms must first establish a clear baseline. “Identify the baseline from where they exist today… and then with using Gen AI, how do they really calculate the incremental benefit,” Datta said. Achieving maturity across strategy, data, talent, governance, and execution, he emphasised, is essential: “Getting to that state of maturity across these five parameters are very important in order to get maximum value.”