Banking on People: Why the Future of AI in Banking Depends on Technology That Stays Human

AI adoption is rising in financial services. But using it strategically to enhance human expertise is what will inspire business owners to fully embrace it.

This article first appeared on Reuters Plus and is republished here with permission. Read the original article on Reuters Plus.

Key Points

78% of Americans report using AI-powered tools daily, and 55% now use them to help manage personal finances.
Consumers are increasingly comfortable with AI for budgeting, savings, spending tracking, fraud detection and automation.
Trust remains critical: only 18% of Americans trust AI to make financial recommendations without human involvement.
Banks can build confidence in AI through transparency, strong governance, privacy protection and human oversight.
The future of banking will combine AI-driven personalization and efficiency with human judgment, accountability and trust.

A few short years ago, artificial intelligence (AI) was widely regarded as an accessory, helping users draft emails, generate meeting notes and perform other routine tasks, freeing them to focus on more complex or rewarding endeavors. Most people were unsure and often suspicious about what AI could do. But attitudes are changing rapidly.

Consumer confidence in AI is growing exponentially as machine learning’s capabilities accelerate and it shows its worth as an enhancement to, rather than a replacement for, human jobs. Now, not only is AI something most American consumers expect to interact with daily, it is something they feel increasingly comfortable with. AI proficiency is improving as a result and its usage is growing across generations – not just among digital natives, but Generation X and Baby Boomers too.

The results of a recent survey by TD, published in its 2026 AI Insights Report, show that 78% of Americans now use AI-powered tools daily, notably in managing personal finances. Only 10% of the 2,500 respondents were applying AI in this context 12 months ago, while the 2026 survey shows that 55% now do so. Fraud detections, alerts and automation are AI functions with which two-thirds of consumers feel comfortable, and a similar number say they have become more adept with AI since last year.

Businesses shift to AI

In the enterprise space, despite ongoing concerns around bias, accountability and regulation, and risks such as reputational damage, business owners’ confidence in AI-powered tools is also growing – about 78% of US workers are employed by firms that have already adopted AI. That adoption is accelerating as organizations move beyond experimentation, with measurable results being seen. A World Economic Forum report says the impact of consumers’ changing expectations around technology is helping to drive this shift in sentiment among business decision-makers and enterprise leaders.

Within organizations, the focus now has turned to where AI actually creates value, says Kiran Vuppu, U.S. Chief Information Officer, TD. “That means choosing the right business problems to tackle, not just applying AI everywhere.”

Through teams using relevant AI tools in their day-to-day work, questioning established processes and building familiarity, he says, small, practical changes are accumulating that continue to drive the bank’s transformation. Getting it right comes from having strong data, the appropriate infrastructure and clear controls, with human oversight throughout.

As an example of how AI is delivering value for customers while maintaining this human-centric approach, Jo Jagadish, Head of Digital, Payments and Consumer Deposits for TD Bank U.S., explains how the AI-powered tools on its Knowledge Management System (KMS) platforms help the people working in contact centers to surface necessary information quickly.

“Instead of searching libraries of data manually, a colleague can get a relevant, accurate response almost instantly, freeing up human bankers to handle more complex cases,” she says, adding that clients are increasingly comfortable with AI where they see it improve everyday financial tasks, like budgeting, savings and tracking spending.

While public confidence in AI is expanding, in financial services trust is not optional and must be earned every day. Unsurprisingly, at a time of rising AI data breaches, the protection of individuals’ data and privacy is the biggest concern around AI use for just over half of TD's survey respondents, followed by transparency about when and where AI is being used (36%). As the technology becomes more powerful, the human role consequently grows in importance. Keeping humans at the center is critical to maintaining trustworthiness, Vuppu says, as is the constant monitoring and updating of the bank’s strong standards of governance.

Also critical is users having faith in AI to make autonomous decisions about money on their behalf. Currently, only 18% of Americans say they trust AI to make financial recommendations to them independently, with no human intervention, while 48% would trust AI-driven recommendations if a human subsequently reviewed them. In order to build and maintain trust, banks can combine AI with clear human oversight and human visibility – for example by using AI tools that augment human roles, rather than replace them.

“We are human-led, AI-enhanced. Clients can be assured that what is ultimately shared with them has been reviewed, validated and determined by humans,” says Ted Paris, Head of Analytics, Intelligence & AI for TD Bank U.S., emphasizing that people remain accountable for decisions, judgment and outcomes. “AI gives employees better tools to move faster, make stronger decisions and deliver more value, responsibly.”

Getting personal

Personalization is another facet of AI that is transforming banks’ customer relationships. Americans have grown accustomed to personalization in other areas of everyday life, such as TV and video game streaming, so why wouldn’t they expect similar responsiveness in their digital interactions with financial services?

Banks can combine AI with customers’ data to analyze their needs holistically and with heightened accuracy, enabling the delivery of tailored products and advice to each person. Tools such as TD’s recently launched Spanish-language mobile app feature, for example, are built to directly address the needs of one of its core client groups. Gen AI accelerated the app’s Spanish language feature development without sacrificing trust. The result? The removal of a language barrier that can limit confidence with everyday banking in places where Spanish is widely spoken, says Jagadish.

Another innovation making AI more personal is TD’s natural-language tool, called “Conversational AI for Analytics,” which allows colleagues to ask a question in natural language and receive analysis, context and guidance, turning that query into an efficient workflow within 30 minutes.

The human role remains central, though, Paris reminds us. “AI can aggregate information, analyze data and surface recommendations, but our teams still need to ask the right questions, challenge the outputs, apply context and decide what action to take.”

Banking’s AI future

The transformation of the banking sector through AI is well underway. By 2030, it will likely be embedded throughout operations rather than layered onto existing workstreams. Agentic AI will see a move toward systems that can coordinate entire workflows across channels, which Vuppu describes as shifting from task automation to decision orchestration.

“We'll have agentic commerce, with AI systems that can act on behalf of clients. Client service will evolve from scripted interactions to more fluid, context-aware problem solving.”

This will also generate infrastructure enhancements, such as AI gateways that direct workloads to the right models for the right problems – and at the right cost.

Yet even as banking becomes more intelligent and increasingly predictive, the industry's competitive advantage will remain deeply human. “AI will make the client’s experience feel fundamentally different,” says Paris. “The bank will be better able to recognize patterns and address client needs earlier – while keeping people accountable for the moments that require judgment, empathy and trust. The institutions that succeed will be those that use AI not simply to automate experiences, but to strengthen relationships, build trust and help people feel understood.”

Frequently Asked Questions

How much do Americans trust AI?
The article reports that 78% of Americans use AI-powered tools daily, but trust varies by application. Only 18% say they trust AI to make financial recommendations without human involvement, while 48% would trust AI-driven recommendations if a human reviewed them first.

How are people using AI to manage finances?
The article notes that 55% of Americans now use AI-powered tools to help manage personal finances, up from 10% twelve months earlier. Consumers are increasingly comfortable using AI for functions such as fraud detection, alerts, automation, budgeting, savings and spending tracking.

What does human-led, AI-enhanced banking mean?
According to TD leaders quoted in the article, AI can help employees move faster, surface information and improve decision-making, but people remain responsible for reviewing information, exercising judgment and remaining accountable for outcomes.

Why is human oversight important in AI?
The article argues that trust increases when AI supports rather than replaces people. Human oversight, governance, review and accountability are presented as essential safeguards, particularly when AI is involved in financial decisions.

How can banks maintain trust while using AI?
The article identifies privacy protection, transparency, governance and human review as key elements of trust. It notes that consumers care about how their information is used and want visibility into where AI is being applied.

How is AI improving customer experience in banking?
Examples in the article include AI-powered knowledge systems that help employees find information quickly, personalized banking experiences, language-accessibility features and tools that provide analysis and guidance through natural-language interactions.

How are banks using artificial intelligence?
The article highlights several examples of AI in banking, including knowledge management systems that help employees quickly surface information, tools that support budgeting, savings and spending insights, personalized digital banking experiences, Spanish-language mobile banking capabilities, and natural-language analytics tools that help employees turn questions into actionable insights.

What is the future of AI in banking?
The article predicts AI will become embedded throughout banking operations, evolve toward agentic systems that coordinate workflows, and enable more personalized and proactive client experiences. Despite those advances, human accountability and trust will remain central.

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