AI is top of mind in many banking circles right now. What a leading intelligence platform shared in its annual banking industry AI Index Roundtable is that for those institutions that have prioritised AI
in their internal – and increasingly external – activities and operations, they’re widening the gap over those which haven’t. And it is getting tougher for laggards to make up the difference.
The top of the list of major AI adopters in financial services hasn’t changed much, with the largest bank in the world, JP Morgan Chase, leading the pack in aggregate across four categories measured, or ‘pillars’, with 8 of 10 of its fellow institutions
joining the US-headquartered bank from the 2024 list. The next five in order after JPMC included Capital One, Royal Bank of Canada, CommBank (Australia), and Morgan Stanley. Wells Fargo, which dropped a couple of spots this year, came in sixth, followed by
two Europe-based slight-decliners, UBS (Switzerland), and HSBC (UK), and two rapid US risers, Goldman Sachs and Bank of America.
When we last
wrote about Evident’s AI Index, the company had just posted its 2024 banking industry update, which it terms an “authoritative ranking” of “AI maturity” that has now expanded its scrutiny beyond the largest financial services firms into the insurance industry
as well. The bank index, now in its fourth year, shows clear trends are beginning to emerge in the UK-based firm’s market survey data, which they use to track which banks across the globe are ‘leading’ in AI adoption. Evident’s findings have highlighted which
institutions are beginning to achieve demonstrable returns on investment for their AI initiatives and programs.
In an online presentation helmed by Evident’s co-founder and co-CEO Alexandra Mousavizadeh, Colin Gilbert, VP, intelligence team, and Daniel Shackleford, managing director, banking, Gilbert began by explaining the methodology of the company’s rankings. He
noted that this year’s list combined publicly available research and statements (across more than 70 indicators in total) compiled from the banks involved on their AI-related activities and investments. Talent and Innovation were the two most heavily weighted
among the pillars studied and scored, at 45% and 30% respectively, while other factors reviewed included Leadership - or executive sponsorship and positive positioning of AI opportunities in reports and announcements, and Transparency - of investments and
use cases shared externally as indicators of commitment and progress in adoption of AI within their institutions.
AI Index shows steady progress forward in its fourth year
The index has moved forward each of the past three years, Gilbert noted, and the names on the list haven’t changed much over that time. But momentum overall and for certain institutions has picked up. “The index average is steadily increasing year over year,
from 30.4 points to 32.8 points to over 36 points today.” While there is consistency amid the leaders, Gilbert said, the front-runners among the world’s AI adopters and promoters “have remained very, very consistent year over year, and are also starting to
pull further and further ahead,” of the rest of the institutions profiled.
Why? Both Gilbert and Mousavizadeh pointed to several possible reasons, including the time required just to instill a novel AI plan, structure, and implementation framework in place in an institution, and the time it takes to make this happen. Plus, the
financial requirements, the investments in technology and talent required just to get started in the AI ‘game’ don’t happen overnight, they said, and the stakes are moving higher every day.
Everyone’s talking about it, some are doubling down on AI tech, testing, and talent
“In a very competitive space where everyone's doubling down, the leading banks are doubling down more than anyone,” explained Mousavizadeh, citing other factors including what she called a “relentlessness of focus on the operating model and continuation
of making AI spend a bigger proportion of the overall tech budget,” as well of constant innovation within banks leading the way in the AI race. In addition, she said many of the largest financial institutions are hiring new AI talent at levels well above their
competitors. “That does speak to the fact that we're in a next phase of adoption or the AI deployment cycle. There's been two and a half years of testing since the release of ChatGPT.”
That next phase, Evident’s co-CEO emphasised, is where the banks at the top of the company’s AI adoption rankings are focusing on “value creation, AI deployment at scale, completely reconfiguring, rewiring the organisation, thinking about all of the workflows
that can be touched by AI and so doubling down into that full on deployment phase, and that we're definitely seeing in the numbers,” to illustrate this, she said.
Evidence of ROI is starting to come in, more banks becoming more transparent on AI results
Do those ”numbers” include clear proof of returns on the investments made? Mousavizadeh says these are beginning to emerge, because, “with that deployment phase, you up your innovation even further. You up your talent pool, and double down on all aspects of
your deployment, but you also mature [and] we are seeing these ROI frameworks definitely mature among the leading banks,” which is shown in how they are “able to talk a bit more explicitly about what they're deploying, what they're rolling out,” when it comes
to AI solutions within their operations.
The hour-long event walked viewers through several slides showing the current state of AI among banks on the list, which the Evident AI trio agreed had really grown to a ‘top 15’ from the spotlighted ten institutions on the front page of the report that
went 50-institutions deep in scope. Though six of the top ten banks call North America home, reflecting the continent’s heavy emphasis on AI application development, Europe’s two members in the upper ranks, HSBC and UBS were joined by Spain’s BBVA when the
list is expanded five more slots. (One important point made by the presenters: there are certainly smaller institutions, “disruptors”, that have developed advanced AI applications, but this list focused only on the top 50 adopters by asset size.)
Noting that the top 15 institutions have increased their scores substantially on average from last year, and that one – Morgan Stanley – had jumped significantly in the rankings, Gilbert said, “there's no better demonstration of the ‘hockey stick’ (sharp
positive increase) effect than Morgan Stanley surging 12 positions in 24 months,” yet he and his colleagues said determining exactly why requires individual assessments of each bank’s moves, whether upwards or down on the list. In Morgan Stanley’s case, he
and Shackleford said, it’s the Wall Street titan’s strong move to hire more AI-proficient talent and its executive team’s major commitment at multiple levels to research and improvements through various internal AI rollouts. Also, the bank’s transparency score
on the index was boosted by the fact they openly shared the results of several internal AI programs including one, DevGen.AI, a coding agent “that saved 280,000 hours by reviewing over 9 million lines of legacy code – greatly accelerating the bank’s ongoing
software modernisation efforts.”
Key findings report: How the high achievers rose to the top of the rankings
Goldman Sachs and BofA strongly improved their rankings vs the prior year on the 2025 list. Goldman advanced thanks to their institution’s own huge executive-sponsored commitments to AI strategy and planning and by hiking their transparency pillar score
through publicly sharing the results of several AI use cases tested and demonstrated in the past year. BofA – with claims to many new patents in the AI field instituted by its team members - was cited for its significant progress in the leadership category
and in the innovation pillars of the rankings.
Capital One continues to hover right near the highest points of the rankings just behind the biggest spender and consistent global AI adoption and research leader JP Morgan Chase. Notable differences for Capital One from most of its much larger peers at
the top of the list include its leadership and transparency scores, which trailed the pack largely due to its reticence to openly share its plans or progress on AI initiatives from the executive level. However, it “continues to dominate the Talent pillar,”
said the Evident report, with an “unrivaled ‘density’ of AI talent found across its employee base.” It also achieved strong scores in the Innovation category with many new patents filed and demonstrations of several technical breakthroughs, “that accelerate
secure deployments of AI at scale.”
Key findings show regional differences shaped by location and operating environments
Beyond the top performer assessments shared, both the Index overview discussion and the ‘deeper dive’ details outlined in the accompanying
Key Findings report noted that regional leaders remained consistent across the globe for 2025. However, the strengths and approaches of the top scoring institutions in those regions differed in a number of
ways, according to the Evident report, highlighting “how location and operating environment shapes both strengths and weaknesses. For example, North American banks lean heavily on research and patents, whereas their European peers demonstrate more rigor (out
of necessity) in governance, regulation, and compliance frameworks.”
Of the top regional achievers, JPMC and Capital One headed North American institutions, HSBC was first among its UK peers, UBS led banks in the rest of Europe, and CommBank topped its APAC competitors.
AI adoption leaders rising faster and farther from laggards, on both global and regional FI lists
One takeaway from all the results, according to the report and the presentation by the Evident team, is that there is a “high degree of bifurcation” between the leaders and laggards on each of the regional lists of large bank AI adopters. This divide has
actually grown year-over-year, noted the company’s deeper-dive analysis of the index rankings.
“Nowhere is this more pronounced than among the US banks where the “spread” between the top-performing bank and the bottom-performing bank is not only the greatest, but also growing the fastest year-on-year.” Why? Because the largest of the bank players in
that region, they conclude, “have the resources to build research labs, patent portfolios, and talent pipelines – creating a sharp divide between leaders and mid-tier banks that cannot keep up.”
The London-based Mousavizadeh shared a few reflections on what the Evident team termed her ‘grumpiness’ about the UK government’s lack of strong support for its own AI development community. While noting a few positive signs and local success stories, and
expressing hope the situation might change, she lamented the potential ‘drain’ of home-grown AI talent to other, more activist, forward-thinking AI havens in regions around the globe.
The discussion of the index results wrapped up with Mousavizadeh’s thoughts on what current trends in AI adoption rankings might mean to the financial community at large, echoing her opening remarks. “This bifurcation that we are seeing really shows that those
banks that invested early, that really doubled down, are really now pulling away. So those that are behind really need to up their game quickly so that they can continue in the same trajectory.” But how to do so? And what might accelerate the tide of AI adoption
even more among larger banks, and eventually their smaller, less focused or nimble global and regional competitors as well?
The answer, Evident’s co-founder said, will be in the ROI, the proof of AI’s value to the institutions that deploy it, and then share the results of their progress, publicly. “I'd really like to draw the audience's attention to the Leadership chapter (of
the 2025 Index’s Key Findings report)” she said, “where we're seeing year over year, the number of banks disclosing the number of active AI use cases has doubled to 25 banks. The number reporting projected ROI on AI use cases in the future is up to seven banks,
and the number of banks reporting realised current ROI on use cases is up to four banks. And these numbers are changing really, really quickly.”