Banks are prioritizing AI investments for several reasons, including streamlining operations, reducing costs and improving employee workflows.
National banks and community banks were equally likely to cite improving employee productivity as a key driver of AI investment, with 74% of respondents from each group identifying it as a priority. Credit unions (73%) and midsized banks (65%) also pointed to productivity gains as a major factor.
Financial institutions are also investing in AI to automate workflows and lower operational costs. Community banks (78%) and credit unions (73%) were the most likely to cite workflow automation as a reason for AI spending, followed by national banks (68%) and midsized banks (65%).
Reducing operational costs was another major factor behind AI investments, particularly among community banks (67%) and national banks (62%).
By comparison, enhancing risk assessment and strengthening cybersecurity ranked lower among the reasons banks are investing in AI. Fewer than half of national banks (45%) said they are using AI for risk assessment and compliance monitoring, while 30% said the technology is being used to improve cybersecurity.
Banks also said investments are being made to keep pace with competitors. Half of national bank respondents said they are investing to outpace their peers, while 35% of midsized banks reported the same.
Banks and credit unions are increasingly embracing artificial intelligence and encouraging employees to build related skills. Financial institutions surveyed said AI expertise is being developed primarily through internal training, informal knowledge sharing and partnerships with third-party vendors.
Most notably, banks said on-the-job learning and informal knowledge sharing are leading the way as institutions determine how to use AI effectively.
An overwhelming majority (76%) of national banks surveyed said informal knowledge sharing plays a prominent role at their organizations. Respondents from community banks (61%) and credit unions (60%) also cited informal knowledge sharing as a key way employees develop AI-related skills, while 57% of midsized bank respondents said the same.
Midsized banks (57%) are more likely than other institutions to rely on third-party vendors for AI training. By comparison, fewer than half of community banks (48%) said they partner with vendors for training, while even smaller shares of credit unions (33%) and national banks (30%) reported doing the same.
National banks (48%) and midsized banks (35%) are also more likely to offer formal internal AI training programs. Smaller shares of community banks (28%) and credit unions (20%) said they provide that type of training.
Despite the growing adoption of AI tools across the banking industry, some financial institutions said employees are not yet building AI-related skills. Respondents from credit unions (17%) and community banks (15%) said employees are not currently developing AI skills, though plans are in place to do so in the future. Smaller shares of credit unions (7%) and midsized banks (3%) said they have no plans for employees to build AI skills.
Credit unions, on average, plan to increase headcount over the next year.
More than half of respondents (53%) said they expect slight staff increases over the next 12 months. Midsized banks and community banks
The next-largest share of credit union respondents (23%) said they expect no change in headcount, while 10% projected either slight or moderate workforce reductions.
The findings offer a positive sign for employment in the financial services sector. The broader labor market has produced mixed signals in recent months, with
