American Banker's 2026 AI Talent Shift Survey
American Banker’s 2026 AI Talent Shift survey was fielded online during March of 2026 among 206 banking professionals who occupy a variety of positions across banks, credit unions, neobanks and payments firms.
Top findings from the report- Half of all institutions surveyed said they are at least moderately literate in AI.
- A lot of respondents don’t have a metric in place for measuring AI literacy yet, while others track usage and skill levels.
- Informal knowledge sharing and on-the-job learning are the most prevalent ways institutions are building AI-related skills.
- Being able to understand what AI tools can do and how to use them is the top skill in demand by banks and credit unions.
Results from the report are highlighted below using interactive charts. Mouse over each section for more detail, click on the chart labels to show or hide sections and use the arrows to cycle between chart views.
This item is the end of a series diving into new research from American Banker. Click the links below to read the other parts of the overall research.
Which institutions boast the most AI literacy?
Key takeaway: Half of all institutions surveyed said they are at least moderately literate in AI.
As new AI models and tools become more readily available for financial institutions, executives are working to bridge employees' knowledge gaps.
National bankers were most likely to say their organizations were moderately to very literate in AI (73%); only 22% said they had low AI fluency.
More than half of executives at midsize banks (57%) reported that their organizations are moderately fluent in AI versus 38% who said their firms have low to very low levels of AI literacy.
Roughly 61% of community bankers said their organizations were moderately to highly fluent in AI, versus 39% who reported low levels of AI literacy.
Among credit union respondents, 57% said their organizations were moderately to very literate in AI. This cohort had the largest share of responses for low AI literacy at 43%.
At a departmental level, 75% of respondents said they are at least moderately literate/fluent in AI, while 23% said their department has a low level of AI fluency and 2% were unsure. Looking at organizations as a whole, 64% said their company was at least moderately fluent in AI versus 33% who said literacy was low, while 3% didn't know.
Along with developing internal training programs, some banks
Arvind Purushotham, head of Citi Ventures, told American Banker that the bank is exploring how AI can be applied to "frontline businesses, as well as some of the middle-office and back-office functions."
"The nature of the transformation of AI is so substantial that every startup company has an AI story, or needs to, for it to have a chance, for it to be sustainable, for it to have a promising future," Purushotham said. "There is no non-AI company that's being funded and started in this environment."
How are banks and credit unions tracking AI literacy?
Key takeaway: A lot of respondents don't have a metric in place for measuring AI literacy yet, while others track usage and qualitative efforts.
More than a quarter of respondents (27%) don't have a metric in place for measuring AI literacy among the workforce, while 23% measure progress through qualitative efforts and 21% track usage and adoption.
Other measurement methods include training or certifications (14%), by ear/informally (10%), productivity tracking (9%), tool-specific tracking (9%) and ad-hoc (6%).
Specific metrics to track the efficacy of AI and how knowledgeable employees are about the technology can vary on an institutional basis, so knowing what output to look for can help steer banks and credit unions toward the best measurements.
During a February panel at the National Association for Business Economics conference in Washington, Federal Reserve Gov. Lisa Cook said that the long-term impact of generative AI is yet to come, but some early indicators such as job demand for certain roles are already apparent.
"It is very difficult to measure labor productivity and total factor productivity," Cook said during the panel. "So we should be patient, and we should be nimble and thinking about the rollout of AI."
The pathways for developing AI talent internally
Key takeaway: Informal knowledge sharing and on-the-job learning was the most prevalent way institutions are building AI-related skills.
Building AI competency is not a straightforward process, with methods from formal training programs to learning on the job yielding different levels of success.
When it comes to building an internal AI knowledge base within departments, 63% of respondents said informal knowledge sharing combined with on-the-job learning was the most prominent method. Close behind were training programs offered through vendor partnerships (42%), formal internal training programs (35%) and hiring external talent (25%).
About a fifth (21%) of respondents turn to external training providers or certifications.
Looking at the findings broken down by institution class, informal knowledge sharing and on-the-job learning was the top training method across national banks (76%), midsize banks (57%), community banks (61%) and credit unions (60%).
Last year, Citi announced that it launched a
"As colleagues learn to use AI, there is a natural process of testing how to write prompts to produce the best results," Peter Fox, head of learning at Citi, told American Banker. "This training is about teaching our colleagues the possibilities of great prompting versus basic prompting."
What are the top AI skills in demand?
Key takeaway: Being able to understand the functionality of AI tools and how to use them is the top skill in demand by banks and credit unions.
Banks and credit unions getting more involved with AI are building the foundation for doing so by ensuring employees have a basic understanding of the technology.
General AI fluency (understanding how AI tools work and how to use them) was the most vital skill identified by 73% of respondents. Critical thinking/judgement (64%), data literacy (58%) and prompt engineering/AI tool proficiency (39%) were also among the top skills identified as most necessary.
Broken down by institution, AI fluency was the most valuable skill across national banks (82%), midsize banks (65%), community banks (78%) and credit unions (70%).
The same was mostly true when looking at responses according to the respondent department. AI fluency was the top skill for retail/SBB (82%), corporate/commercial (75%), payments (72%) and risk/legal/compliance (69%).
AI has become a controversial topic for talent in the banking world, as employees juggle the possibility of being outmoded against the promised reskilling opportunities that come with the technology.
"If you use AI smartly you can free up time to not just create a document or crunch numbers, but to start asking why you're creating the document and numbers," Ngeow said. "AI can be a huge advantage and should be viewed that way for newer staff."
