Given its reliance on sensitive personal data and its close regulation, banking is a sector that balances risk in its approach to artificial intelligence (AI) transformation with customers’ enthusiastic embrace of the technology. With AI in customers’ digital banking experiences and financial lives, the sector is positioned to drive adoption with bold intentionality.
Nearly half of Millennial and Gen Z respondents to a 2025 survey said they would like access to AI assistants to help manage their finances. Digital and AI adoption is high among this cohort: 79% use credit monitoring tools, 68% value fraud alert notifications, 34% use digital budgeting tools—and 62% say they couldn’t live without their mobile banking apps.
AI is not new to finance. The sector has long depended on AI’s power to rapidly identify trends and anomalies in massive data sets, improving risk management, fraud detection, and regulatory compliance.
“We’ve been using AI for years and continue to evolve with the technology and do the things we already do even better,” says Gill Haus, chief information officer at Chase. “AI is creating opportunities for everyone, such as using AI to anticipate customer needs, not just react to them.”
The stakes for AI have always been higher in finance than in most sectors. For customers and employees alike, security is nonnegotiable. On top of providing seamless, intuitive digital experiences, it’s critical that banks demonstrate relevance, transparency, and trust by using personal data with care and acting in everyone’s best interest.
For AI innovation to meet and exceed these exacting and accelerating expectations, financial leaders must keep customers and employees at the center of their transformation strategy by safely and securely deploying AI, using it to support the human workforce, and developing a culture that champions AI to lead change and growth.
To build and maintain trust, banking leaders must make sure all decisions to use AI—and all outputs AI delivers—are transparent and explainable. Customers need to understand why they’ve been approved or denied a loan, and employees need to be sure their AI-powered guidance is sound. This approach helps an organization build confidence, reduce bias, and assign accountability.
“Trust is built top-down and bottom-up,” says Haus. “Leadership has to set the vision and show that AI is here to empower people. But it’s the folks on the ground, the frontline employees, who make it real. Our customers want and value in-person relationships, even though they’re more digitally active than ever. AI can do a lot of amazing tasks for us, but it can’t replace the human connection that empowers our employees, our customers, and their relationships.”
Leaders can feel confident they’re making the right decisions on AI assistant technology by including their customers and workforce in creating, testing, and iterating AI at every step. Human expertise and insights are essential: AI tools can transcribe calls and recommend responses, but it takes human judgment and empathy to preserve accountability and compliance.
“It’s a feedback loop,” Haus says. “Customer expectations push us to innovate, but sometimes the technology unlocks possibilities customers haven’t even imagined yet. The key is to stay close to the customer to listen, learn, and adapt. The best AI adoption happens when it’s grounded in real needs, not just shiny new tech.”
For a sector as tightly regulated as banking, it’s crucial for AI initiatives to incorporate security and controls from the beginning—never as an afterthought to an otherwise innovative approach. Leaders must include all internal compliance, risk, and technology partners to build controls into the AI design, test the technology rigorously, and stay fully transparent with regulators.
At its best, AI technology should feel effortless, letting banks provide financial answers and solutions quickly, in plain language, on the platforms customers prefer. Employees can give up some traditional manual tasks to focus on applying their expertise to build stronger relationships and solve complex problems.
Users may not even notice when they’re using AI, but they can sense the heightened speed, accuracy, and empathy of their banking experience.
For AI transformation to succeed, trust must flow in both directions, between the C-suite and the front office. Company leaders need to build a vision for transformation and communicate AI’s value to the organization, but it’s up to the front line to make that transformation succeed.
That transformation requires a cultural shift. Leaders who invest in employees’ AI training and celebrate their wins empower them to explore AI’s potential safely, with the assurance they can experiment with it and speak up about any missteps.
In a large organization, AI innovation and transformation require patience, alignment, and advocacy, with leaders identifying internal champions who can help lead a cultural shift toward AI adoption. Building consensus will help ensure the AI initiative transcends early experimentation to drive strategic growth over the long term.
The One Chase Experience Platform Design team used the guidance of the frontline workforce and customers to upgrade a meeting scheduler tool, improving employee preparedness and decreasing no-shows. And behind the scenes, Chase builds AI agents to help its engineers, taking a huge weight off their shoulders, as with one AI agent that automates component testing. More broadly, JPMorgan Chase has democratized access to generative AI with its internal platform, LLM Suite, which helps employees expedite daily tasks, access and analyze data from across the firm, conduct research, and build customized tools.
The finance sector’s AI transformation journey has tremendous potential to support its customers by supporting their financial goals, anticipating opportunities, and offering personalized guidance proactively. And AI can help the banking workforce hand off routine tasks so they can better support customers and build their own skills.
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