Evident AI Index 2026 reveals accelerating AI adoption across global banks

The latest Evident AI Index for Banks has been released, benchmarking AI adoption and maturity across 50 of the world’s largest banks as the sector accelerates its deployment of the technology.

The 2026 Index assesses banks across North America, Europe and Asia-Pacific using 75 indicators and millions of data points spanning four pillars: Talent, Innovation, Leadership and Transparency.

This year’s results show that AI adoption across banking has accelerated more over the past 12 months than at any point since the Index was launched in 2023. The average bank’s Index score increased by 26%, or 9.6 points, over the past year – almost three times the average rate of improvement recorded between 2023 and 2025.

Despite the acceleration across the sector, leadership at the top of the ranking remains relatively stable. JPMorganChase retains first place, followed by Capital One and Royal Bank of Canada (RBC).

CommBank ranks fourth and is the highest-ranked Asia-Pacific bank, followed by Wells Fargo in fifth. UBS takes sixth place and is the highest-ranked European bank, with Bank of America, Citigroup, Morgan Stanley and TD Bank completing the top 10.

Every bank in this year’s top 10 has previously appeared in the leading group, while six have ranked in the top 10 in every edition. JPMorganChase ranks first or second across each of the Index’s four pillars, while Capital One leads globally for both Talent and Innovation.

Among UK-headquartered banks, HSBC ranks 11th overall, Lloyds Banking Group 15th, NatWest 17th, Barclays 19th and Standard Chartered 23rd.

Banks face growing pressure to prove AI returns

Evident’s analysis suggests that the focus of AI investment is increasingly moving from experimentation and capability building towards deployment, governance and measurable business impact.

However, a significant gap remains between deploying AI and demonstrating its financial value.

Only 12% of publicly reported AI use cases disclose an impact against operational KPIs, while barely 1% report a concrete financial return.

The Index suggests the leading banks are further ahead in demonstrating these outcomes. The top 10 account for 25% of use cases that include impact claims, with their representation increasing among use cases reporting higher levels of measurable performance and tangible return on investment.

More banks are also beginning to quantify the overall financial contribution of AI. Twelve banks now report either a realised or projected return across their AI activities, up from eight last year.

AI talent moves towards deployment

The composition of banks’ AI workforces is also changing as organisations move towards deploying the technology at scale.

Evident found that some of the fastest-growing areas of AI talent are now Model Risk, Product Management and AI Enablement roles, reflecting increased investment in integrating AI into workflows and managing the associated risks.

The nature of AI research is changing too. Among banks publishing the most research, work focused on evaluating models has increased from less than a quarter of papers to almost a third.

Research is increasingly concentrating on model performance, controls and costs, including assessing how much AI capability is required for particular tasks.

Governance is emerging as another differentiator between the sector’s AI leaders and the rest of the market.

Evident found that 80% of leading banks have adopted sophisticated AI control mechanisms, including automated guardrails and post-deployment monitoring, compared with 40% across the remainder of the industry.

The Index also found that leading banks continue to achieve stronger results from general productivity copilots, which Evident links to greater investment in employee training, reusable prompts, data integration and mechanisms for scaling best practice across organisations.

Evident said the findings indicate that the next stage of AI competition in banking will increasingly be determined by institutions’ ability to demonstrate the value generated by the technology while putting the governance and infrastructure in place to deploy it at scale.