Financial institutions are using AI across search, personalization, onboarding, customer service, marketing, and the branch, but the technology’s value lies in solving real problems for customers and staff
A new customer looking for a new savings account may now begin their search with an AI assistant instead of a traditional search engine that drives them to banking website or consumer comparison page. As AI search gets stronger, people can ask which institutions offer a strong rate, have branches near work or home, or provide a specific small-business service. Those behaviors are already showing up across the data. A 2025 Adobe study of more than 5,000 U.S. consumers found that 27% say they have used generative AI for banking and financial needs. Among those AI users, 42% cite using AI for checking and savings account recommendations.
The same study found that traffic from generative AI sources to U.S. banking sites rose 1,200% from July 2024 to February 2025, though the company noted that the channel remained modest when compared with more long-standing, established sources, like traditional search and site visits from referral links. For bank marketers, it’s essential to know that while AI is evolving, not every way AI is showing up for financial institution discovery is equally mature. The best practical applications of AI span how customers find an institution, manage money, and get help through a complicated moment.
Artificial intelligence is one of the channels a prospective customer relies on for identifying bank and credit union options, and AI-assisted discovery increasingly influences prospects’ decisions when choosing a primary financial institution (PFI). AI can also help someone identify a secondary option to provide a solution for a more tailored need.
AI search engines pull in information from across the internet. Because of this, financial institutions need to ensure that rates, fees, eligibility, locations, and service details are consistent across their website and other trusted sources so that users are being presented with the most accurate information. Sometimes AI answers can leave out specifics or misunderstand a prompt, so customers still need a direct source to verify details before acting.
When it comes to personalization, the value for customers is not that a marketing message simply calls them by name. Personalized interactions provide customers with something far more useful. One of the early iterations of AI in banking, Bank of America’s Erica offers a more mature use case. In August 2025, the bank reported more than 3 billion interactions and 1.7 billion proactive, personalized insights since launch. Recent upgrades to the virtual assistant include warning customers where their balance is trending over the next seven days, highlighting cash back offers based on spending, and appointment scheduling when the customer needs to speak with a banker. Those are different applications, but each gives the customer proactive, personalized solutions instead of rote alerts.
Some of the most useful examples of AI in banking are behind the scenes work. Citi says it is using AI to automate manual parts of their Know Your Customer program and client onboarding, with the goal of reducing cycle times. The bank also reports AI-supported underwriting and credit review in wholesale lending. These complex workflows are still being upgraded, and they’re not a promise that every application is now instant. On the credit union side, Marine Credit Union reports that its AI lending model handled 55% to 60% of consumer loan decisions. Using AI, straightforward approvals can arrive within minutes, while roughly 40% to 45% of applications still receive human review. Lenders can request an override, and the credit union checks approval, default, and manual-review results each month.
That balance of human versus AI interface matters. Faster onboarding or lending only improves the customer or member experience when the end user understands what is needed for approval, does not have to submit the same information twice, and can reach a human when their individual case does not fit the institution’s standard operating model. But it’s not only lending or account applications where AI is ramping up processes. Routine answers to questions and speedier resolutions are making everyday banking better for customers and staff alike.
Bank of America says more than 18,000 customer-service representatives use EricaAssist to receive contextual generative-AI guidance in under three seconds. According to the bank’s July 2026 announcement, the tool has reduced average call time by nearly one minute, giving employees a faster starting point while they remain responsible for the customer conversation. Credit unions are applying the same idea at a different scale. In a 2025 CreditUnions.com webinar, Interra Credit Union reported a 90% reduction in calls sent to an overflow provider after introducing an AI chatbot, then expanded the technology into voice and internal knowledge assistants.
The customer outcome is the point: less waiting, fewer handoff errors, and more employee time for questions that need expertise or empathy. Efficiency should improve the service, not become a way to cut access to people.
Using AI in bank marketing means more than generating ad copy or segmenting lists. Predictive systems can identify an optimal audience, customer need, preferred channel, or ideal time for message delivery. Generative AI can produce and test message variations, because marketers understand that more content does not automatically mean better communication. Education Credit Union in Amarillo, Texas, offers an example. In a 2025 ProSight article, ECU said AI-based targeting models narrowed a pool of 100,000 potential prospects to just under 10,000 high-propensity prospective members for a checking-account campaign. The credit union reported a 270% lift in conversion rates compared with the prior year, showing how AI can help a smaller marketing team focus its outreach instead of simply producing more content.
Beyond marketing to new members, AI is being effectively leveraged for more pressing purposes. After Hurricanes Helene and Milton in 2024, BCU used AI-supported outreach to respond to urgent community needs. The credit union says it made more than 55,000 AI-driven calls about fee reimbursements, emergency loans, and insurance claims in the aftermath of unprecedented devastation, connecting with 45% of the members contacted. This type of outreach is a good reminder that better AI targeting should mean better timing and utilization, not simply more automated contact. Used thoughtfully, AI technology can help financial institutions identify not only who to reach, but when that outreach can make the most difference.
Public data on AI-specific branch and digital signage deployments is thinner, with many systems described as smart signage still using scheduled screens, routine sensors, or ordinary analytics. But some financial institutions are piloting useful programs in AI-assisted staff support. Pittsburgh-based FNB reports that generative AI-enabled apps now help branch employees answer questions and handle day-to-day procedures. In its 2025 annual report, FNB describes a branch-based tool that can quickly surface product details, onboarding policies, and security or compliance information that employees might otherwise have to search for manually or call another internal resource to find.
While employing AI as an internal resource may be less flashy than other use cases, this type of program shows where AI can make a physical banking experience more efficient and informative. The opportunity isn’t the digital screen itself, but how AI can give branch employees faster access to the information they need while keeping the customer conversation customized. Tailored AI can reduce the time employees spend searching for answers and allow them to focus more attention on the person in front of them, making both the customer and staff experience better. In that role, AI enhances the value of human interaction in the branch rather than trying to replace it.
Effective AI should always have a clear purpose. The technology might help someone find the right financial institution, finish an application, get a faster answer, or connect with the right person in a branch. The strongest AI applications solve a defined problem or remove friction from an existing experience rather than adding technology for its own sake. Accuracy, privacy, fairness, and security still matter, as does a clear path to human support when technology falls short. The CFPB has warned that poorly deployed banking chatbots can trap customers in repetitive loops or provide inaccurate information, underscoring the difference between simply deploying AI and using it effectively.
This article was authored by Jonah D’Ambrosio, Marketing Intern at Adrenaline.
Believe in Banking is Adrenaline’s insights-led resource, created to inform, educate, and inspire leaders in financial services. Delivering credible content rooted in research, the platform highlights the forces shaping the future of banking. From perspectives on emerging trends to podcast interviews with industry trailblazers, this purpose-driven channel helps banking leaders learn, lead, grow, and thrive.
Related Insights
We use cookies to improve your experience on our site. To find out more, see our Privacy Policy.
