Understand the use cases for AI in banking and why human financial guidance isn’t going anywhere
There’s a lot of buzz in banking about artificial intelligence, and signs that financial institutions are beginning to pour significant dollars into upping their AI game. JP Morgan Chase CEO Jamie Dimon recently announced that his financial institution is preparing to spend $19.8 billion on tech in 2026, up 10% year-over-year. It’s a stunning investment that Dimon characterized as a core strategic priority and foundational to the bank’s plans to strengthen its position against both traditional competitors and emerging peer-to-peer networks. This commitment to AI is in addition to Chase’s significant and ongoing investments in branches.
Where AI goes, however, misconceptions follow. The rapid adoption of artificial intelligence is fueling a narrative across industries that automation means the technology will replace workers. The reality: bankers aren’t going anywhere. A new TD Bank survey of 2,500 consumers found that while people are open to using AI for some tasks, 81% want human interactions, especially for personalized recommendations and financial advice. In other words, AI is about augmentation, not replacement. “Generative AI is not going to rewrite the fundamental business of banking,” according to Accenture’s Banking in the Age of Generative AI. “But it is going to change how that business gets done.”
While artificial intelligence isn’t a substitute skilled and empathetic employees, the technology stands out as a tool for repetitive, data-heavy, rules-based work. “AI can instantly pull together all the relevant information about your application, verify documentation, assess risk factors, and flag potential issues,” says Sean Desmond, President and Chief Executive Officer at nCino. “Work that used to take days now happens in minutes.” Citizens Bank is also looking to implement AI for call center and engineering operations. According to Banking Dive, the aim is “to bolster customer experience and help the bank compete with larger lenders spending far more on technology.”
There are already strong use cases for AI in banking. For fraud detection and anti-money laundering, artificial intelligence enables real-time analysis across vast datasets, and machine-learning models can identify unusual transactions and other suspicious activity that traditional systems routinely miss. AI also dramatically accelerates data processing across core banking operations, strengthening risk management and operational efficiency. And in customer service, using AI to handle balance checks, password resets, and transaction lookups means these requests can be resolved instantly – reducing wait times for customers and operational costs for banks.
For all its promise-and value, AI models are only as good as the data they’re trained on and the people who build them. Biased, incomplete, or historically skewed datasets can lead to discriminatory outcomes, creating regulatory and reputational exposure. Similarly, over-reliance on automated decision-making can create dangerous blind spots, and systemic errors can spread long before an employee can flag the problem. More fundamentally, AI lacks context, emotional intelligence, accountability, or expertise – and customers know it.
Today’s banking consumers are seeking personalized financial guidance and embracing relationship-based banking more than ever. If AI can handle routine inquiries, that will free up employees to do the more high-touch work that fosters meaningful conversations and deepens customer connections. That shift towards AI for operational efficiency creates space for staff to devote to consultative conversations – the kind that build trust and position banks and credit unions as partners in customers’ financial lives. Indeed, 65% of people in a recent YouGov survey say they prefer human-led support and guidance.
“Customers don’t resent AI,” according to Gladly and Wakefield’s 2026 Customer Expectations Report. “They resent wasted effort. When AI loops, blocks access to a human, or forces people to repeat themselves, trust inevitably erodes – even if the issue is eventually resolved.” As with any new innovation, trust must remain a primary consideration. That’s why only 2% of people say they want to interact exclusively with a chatbot, as the YouGov survey finds. Despite this lack of confidence, consumers are “resigned about the role generative AI will continue to play in modern life,” according YouGov.
While AI can help power backend banking operations, the real advantage is using this technology to amplify human-led interactions. AI works best in the banking sector when it is deployed as a supplement – not a replacement – for real human expertise. A 2025 research study on human-AI interaction finds that “bank customers exhibit greater reliance on investment advice when they are aware of human involvement in the advisory process.” The authors also state that “human involvement increases the persuasiveness of AI-generated recommendations.” While artificial intelligence can support insights and efficiency, bankers are still critical to providing interpretation and guidance. Customers might value the AI for certain tasks, but they ultimately trust people to guide their financial decision-making.
McKinsey’s Economic Potential of Generative AI report posits that, across the banking sector, AI “could deliver value equal to an additional $200 billion to $340 billion annually if the use cases were fully implemented.” To realize this potential, banks should strive to use AI to remove friction, not relationships – and design for human-led journeys with AI support. The competitive advantage for financial institutions will not be in deploying artificial intelligence alone, but in how effectively banks can arm humans with AI tools that enable better, faster, and more human-centered decisions.
Accenture’s generative AI report notes that the technology can “be embedded within operations and existing tools and applications to supercharge employee productivity” and that it can transform back office operations by automating repetitive, routine tasks, freeing up employees for more meaningful and higher-value work. This leaves bankers to do what they do best: deliver advice and personalize offers based on what people need in the moments that matter most.
To learn more about how your financial institution can enhance experiences for customers or members, get in touch with Adrenaline’s brand-to-branch experts.
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.
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