
Evident AI Outcomes Report
Delivering value, Scaling GenAI, Anticipating Agents
ABOUT THE OUTCOMES REPORT
The Evident AI Outcomes Report is a comprehensive analysis of how 50 major banks are generating value from generative and agentic AI deployment.
The report provides data-driven insights into:
- GenAI trends: where and how GenAI is being rolled out across businesses
- AI returns: how banks are measuring and disclosing the value of their AI use cases
- Agentic AI in action: which banks are ahead of the curve in deploying agentic AI
The report combines data from our Use Case Tracker with insights from our private Outcomes Benchmark to provide a data-driven view of how banks are deploying generative AI, experimenting with agentic AI, and translating these into tangible business value.
Read more in our Key Findings below. To learn more about the AI Outcomes Report, or to discuss how Evident could support your firm in its AI adoption journey, contact us here.
Explore the key findings below or get in touch for information on the full report.
KEY FINDINGS
1
AI USE CASES SURGE IN H1, PROPELLED BY GEN AI
Over the past 12 months, 47 of the 50 banks tracked in the Evident AI Index have announced a grand total of 173 new AI use cases. In H1 2025, these disclosures more than doubled over H2 2024, fueled by expanding deployments of GenAI tools.

2
LESS THAN A THIRD OF AI USE CASES REPORT OUTCOMES
While nearly every bank is talking about their use cases, they remain highly selective when it comes to disclosing actual outcomes. At present, less than a third (30%) of the 173 use cases disclose any associated impact metrics.

3
OUTCOMES EXPANDING BEYOND EFFICIENCY
Despite limited reporting of outcomes, the types of KPIs shared across H1 2025 are quickly diversifying beyond efficiency and productivity measures. Specifically, reports of revenue uplift – including enhanced sales conversion, cross-selling opportunities, and customer acquisition – surged to 16% of all use cases reported in H1.

4
BULK OF GEN AI USE CASES CATER TO INTERNAL USERS (FOR NOW)
85% of GenAI use cases are restricted to internal functions, underscoring the high level of scrutiny and oversight baked into early deployments. This prioritization of employee-facing applications also helps explain the continuing focus on efficiency and productivity metrics within the banks.

5
BANKS ARE PUTTING GEN AI INTO THE HANDS OF RETAIL CUSTOMERS FIRST
Among the 15% of GenAI use cases categorized as externally-facing, over half are concentrated in retail banking. This line of business is adopting a deliberate, incremental approach to enhancing the customer experience – by upgrading legacy chatbots, deploying virtual avatars, and experimenting with agentic workflows.

6
COLLECTIVELY, 10 BANKS HAVE DEPLOYED AI ASSISTANTS TO OVER 800K WORKERS
Over three-quarters of the 50 banks we track have rolled out AI-powered assistants to their workforce, but only 10 banks have detailed the extent of these rollouts (with even fewer providing figures on employee uptake and utilization). Among these, implementation strategy is split between those deploying AI tools to the widest possible workforce vs. a targeted selection of priority users.

7
FRONT OFFICE & IT/SECURITY APPLICATIONS LEAD ON OUTCOMES
68% of use cases with reported outcomes are concentrated in just two areas – Front Office and IT & Security – functions where sales advisor assist, developer augmentation, and fraud prevention applications are starting to yield clear benefits for banks.

8
CAPITAL ONE, JPMC, AND BNY DEMONSTRATE HEADSTART ON AGENTIC
Only 9 of the 50 banks we track have documented an agentic AI use case in production or pilot stage. Three of these (Capital One, JPMorganChase, and BNY) have further detailed the supporting architecture for agentic workflows – a critical prerequisite for scaling promising solutions amidst ongoing scrutiny from both internal and external stakeholders.

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OUTCOMES REPORT
Evident AI Outcomes Report 2025
The Evident AI Outcomes Report is a comprehensive analysis of how 50 major banks are generating value from generative and agentic AI deployment.

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