CB Insights noted that AI is now considered to be a universal focus area for retail banks, with various generative AI use cases increasingly emerging across operations, from fraud prevention to enhancing a range of customer service solution. CB Insights also mentioned that as agentic AI systems gain traction, the “bar is rising.” Banks are no longer judged on experimentation alone, but on their readiness “to deploy production-grade AI systems that can operate safely and at scale across the enterprise heading into 2026.”
To assess this shift, CB Insights’ AI Readiness Index for Retail Banking ranks the top 20 retail banks in North America and Europe based “on how actively they are building, partnering, and hiring to operationalize AI.”
CB Insights has explained that the index reportedly aims to accurately “evaluate earnings transcripts, partnerships, investments, acquisitions, and patent filings.”
Their analysis indicates a widening gap.
A small group of professionals has built the capabilities, infrastructure, and ecosystem leverage required to “scale autonomous AI workflows repeatedly and safely.”
Others remain active but fragmented, with AI efforts “that struggle to translate into bank-wide impact.”
Some of the main takeaways from the recent analysis carried out by CB Insights are as follows:
- JPMorgan Chase is using AI spend to turn scale into a durable moat. Its coordinated AI strategy across internal builds, partnerships, and equity investments allows it to deploy and scale AI across the bank without fragmentation. This level of integration is difficult for peers with fewer resources or weaker operating models to replicate.
- Citigroup is narrowing the gap between AI investment and measurable value. By pairing proprietary tools with targeted investments, the bank is building the foundational infrastructure needed to support agentic AI experimentation and future scale.
- Internal builds are emerging as the control layer for large banks. Among top-tier institutions, AI readiness tracks closely with proprietary development. Bank of America and Wells Fargo are leaning into patents and internal builds to keep maximum control over governance as AI systems move closer to autonomy.
- Ecosystem partnerships offer a fast path to AI maturity. Lloyds Banking Group and BNP Paribas show how targeted alliances with LLM developers, point solutions, and infrastructure providers can close readiness gaps without matching the spend of global giants.
- LLM developer partnerships are becoming a key competitive lever for agentic AI. BNP Paribas and HSBC show how deep, cross-bank collaborations with LLM developers drive aggressive scale. By tapping Mistral AI’s technology and ecosystem, the banks can ship use cases faster, moving to the front of the AI race.
- Signals from earnings transcripts, patent filings, and partnership data all point to the same inflection point: banks that bring agentic AI into production in 2026 will extend their lead, while those still confined to pilots will struggle as autonomous workflows become table stakes.