JPMorgan Chase Rated as Most Advanced AI Bank

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Here’s the latest from JPMorgan Chase;

JPMorganChase has extended its lead as the world’s most AI-advanced bank in the Evident AI Index, the global standard benchmark for AI maturity in financial services. Across the 50 banks assessed, AI capabilities advanced nearly three times faster over the past year than the average across the previous three years – the fastest pace since the Index launched in 2023.

JPMorganChase ranks first or second in all four pillars of the Index and has widened the gap to its nearest challenger, Capital One, which retains second place and leads the Index for AI Talent and Innovation. Royal Bank of Canada holds third, with CommBank now close behind.

Below the top three, the pack is tightly bunched – and North American banks now dominate. UBS (#6) is Europe’s only representative in the top 10, and CommBank (#4) the only bank from Asia-Pacific.

Elsewhere, Citigroup (#8) and TD Bank (#10) re-enter after a year outside the leading group, and Bank of America climbs three places to #7. The next 10 are dominated by European banks, including four UK banks HSBC (#11), Lloyds Banking Group (#15), NatWest (#17) and Barclays (#19).

Based on the Evident AI Index, the ten banks leading the race for AI maturity are:

AI is moving deeper into the business at the leading banks

Over the past four years, banks have moved from defining their strategies, to building the foundations, to deploying AI across the enterprise. As a result, scale is no longer defined as simply giving 100,000 employees access to the same LLMs or tools. Instead, AI is diffusing, moving deeper into the workflows that underpin the top leading banks, with the top 10 demonstrating higher deployment rates than their peers across 8 of 9 application areas. That is speeding up and derisking some of banking’s biggest processes. At Capital One, an AI fraud tool embedded in its dealer platform, ProtectID, prevented approximately $150 million in potentially fraudulent auto loan applications in 2025.

Across that broad range of applications, the 50 banks in the Index have disclosed 1,107 AI use cases since 2021, with a growing number now able to associate use cases with a concrete impact. The top 10 banks account for a quarter of all impact-linked use cases, and half of all those with a direct financial outcome.

ROI frameworks are maturing too. The number of banks reporting a realized or projected return across their AI activities is up to twelve from eight last year, CommBank, Lloyds Banking Group and TD Bank among the new entrants. For example, CommBank expects its AI benefits to double to around AUS$400 million in FY27, the first year in which they are expected to exceed its AI investment. TD Bank generated CAN$195 million in AI value in the first nine months of fiscal 2026 against a full-year target of CAN$200 million.

Alexandra Mousavizadeh, Co-Founder and Co-CEO of Evident, commented:

“This was the year AI in banking went industrial. Banks across the Index are moving faster than at any point since we began measuring, but what separates the leaders is everything they have built around their models, from the data and the plumbing, to the guardrails, and the habit of building something once and scaling it everywhere. That foundation is what allows them to put AI into production at pace.”

AI is freeing up time, and banks are putting it back to work

Banks are still adding AI talent, but the mix is shifting from building the foundations for AI, to enabling the people who use it, and the fastest-growing pools are those sitting between technical capability and the wider business. The ten banks adding the most AI talent account for the majority of recruiting across all areas, with over a quarter of their new roles focused on enablement specifically, with JPMorganChase, CommBank and Royal Bank of Canada the top hirers.

Even software implementation roles – one of the first areas that banks concentrated deployment and where AI coding assistants are now in everyday use – grew 4.3% year-over-year across the 50 banks. Morgan Stanley has saved more than one million developer hours through its DevGen.AI platform and is reinvesting them in technology rather than cutting IT resources. Bank of America reports developer productivity gains above 20%, with the time redirected to higher-value work.

Elsewhere, leaders are using AI productivity gains to “increase the size of the pie” as well as driving efficiencies. JPMorganChase’s advisor tools have made advisors roughly 95% faster at finding relevant content for client conversations and helped drive a 20% increase in gross sales, and the bank has said its next generation of AI agents should allow bankers to cover around 50% more clients. UBS’s STAAT Insights tool gives its advisor teams back roughly 1,200 hours a week. Wells Fargo is training AI agents on 15 years of loan decisions so that the process can be automated going forwards, with underwriters brought in to make the final call.

Mousavizadeh added:

“Where AI is producing time savings, it is overwhelmingly being reinvested in serving more clients, launching more products, dealing with backlog and building the next wave of AI. This Index places more focus and weight on AI in production and its impact, and the Index leaders are adding the people who make that possible: AI scientists, AI product managers, engineers and risk specialists. Roles are changing, and some are not being backfilled, but the banks at the top of our Index are growing, and growing headcount. This could be the start of the largest net job creation we have seen in decades.”  

Strong controls are allowing the leaders to move faster

While public concern grows over whether increasingly powerful AI systems can be kept in check, the leading banks have long been investing in the tight controls and solid governance that are now allowing them to roll out agentic tools faster.

Responsible AI principles are near-universal, published by 49 of the 50 banks (up from 16 in 2023), and 62% explain how those principles work in practice. But sophisticated controls – including checks on what AI systems are fed and what they produce, limits on the tools they can use, and monitoring once they are live – are in place at 80% of the leading banks, against 40% of the wider Index. Meanwhile, AI governance talent across the 50 banks grew 33% year-over-year.

These measures function as more than a brake on risk – they enable innovation through agentic AI. CommBank’s system that proposes new fraud detection rules for human approval, is one example, and is now contributing to the development or modification of roughly three-quarters of its card-fraud rules.

Daniel Shackleford Capel, Managing Director of Banking at Evident, commented:

“Banking is the blueprint other industries are following. The leading banks are focusing on where AI will deliver the greatest impact and not using AI to cut their way to savings. But while most banks can now show that AI makes work faster, demonstrating what that means for the bottom line is a different story. Ultimately, those are the metrics every bank will need to determine which of its hundreds of AI projects to scale. With AI budgets at record levels, the banks that can prove their returns will keep the money flowing to the right places. The banks that can’t risk their AI programs stalling.”