Earning Trust in the Age of Generative AI

_Paula Grieco is Senior Vice President at Commonwealth. _

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Conversational AI has the potential to be transformative, particularly for those living on low-to-moderate incomes (LMI). It can strengthen and enrich customer relationships and contribute to long-term financial health. As older, more limited customer support chatbots make way for advanced generative AI that can offer tailored financial support at scale, financial institutions will find themselves with unprecedented opportunities to better serve their customers earning LMI.

But here’s the rub: The potential for this technology is meaningless if people don’t trust it well enough to use it.

At Commonwealth, we recently examined how consumers living on LMI perceive conversational AI, what drives or hinders their willingness to engage with it, and how trust influences that engagement. Our findings, drawn from a national survey of 3,000 adults, in-depth interviews, and field tests, looked at five different aspects of trust:

*   trust in financial institutions 
*   trust in the effectiveness of AI 
*   trust in data privacy and security 
*   trust in oneself 
*   and trust in providers 

The insights from this research reveal both challenges and opportunities for financial institutions preparing to employ generative AI. The findings also point to this central truth: Trust is the principal currency of customer relationships. And in an era of accelerating technological change, earning it requires intention.

How Can I Help You?

One striking finding in our research is that institutional trust is strong. Ninety percent of respondents told us they trust their primary bank. National survey respondents who had high trust in their bank were also more likely to trust their bank’s chatbot. Financial institutions can build upon this trust as they introduce more sophisticated AI tools.

Despite this institutional confidence, however, consumers still expressed wariness in their chatbot interactions. Notably, their reservations revealed a concern about the technology’s helpfulness rather than its information accuracy:

*   More than half of respondents worried a chatbot wouldn’t understand them.
*   Others feared it would understand them but still fail to provide a useful answer.
*   Some felt it would simply take too much time and effort to engage.

This feedback points to a clear product opportunity rather than a credibility gap. In fact, 79% said they trust the accuracy of the information their bank’s chatbot provides. Customers are looking for relevance, responsiveness, and the feeling of being heard. These are the same qualities that define trust in any human interaction as well. For providers, this feedback underscores the need for AI-powered tools that feel capable, empathetic, and genuinely helpful.

The Human Safety Net Still Matters

As AI capabilities advance, consumers are clear about one thing: They do not want to feel trapped in a robotic interaction when they reach the limits of what a chatbot can do. The option to seamlessly transfer to a human agent remains one of the most powerful contributors to trust.

This doesn’t diminish the promise of AI; it clarifies it. Tools that integrate human support can allow customers to engage with more confidence. Blended service models send an important message to customers that they are not alone and someone—a “real” someone—is still there to help them.

In the long run, the financial institutions that pair advanced AI with human accessibility will be the ones likely to earn sustained customer loyalty.

Why Generative AI Changes the Equation

Today’s natural language chatbots are limited. They tend to provide generalized pre-written responses and cannot understand the complexity of real financial questions. But generative AI—properly governed and designed—has the potential to be game-changing, providing detailed and personalized responses to customers’ unique financial challenges with real-time guidance and support. Imagine co-pilots that could equip millions of people with a personal financial coach for the first time. Or generative AI support that could help households living on LMI navigate often complex and disjointed workplace and public benefits programs.

And for households living on LMI, the potential impact is significant. These customers are nearly twice as likely to want to bank through personalized conversations, yet they have less access to in-person branch services. Generative AI opens the door to high-quality, individualized guidance available to them at a time and place of their choosing.

If financial institutions can implement generative AI responsibly—with transparent data practices, clear safeguards, and human-first design—they have an opportunity to deepen relationships with this underserved population.

The Future Depends on Earned Trust

Trust is not a given; it is earned through consistent, reliable, and empathetic experiences. For generative AI to deliver on its promise, financial institutions must recognize trust as a strategic priority, not a byproduct of innovation.

This means:

*   Building AI that listens as well as it answers
*   Being transparent about how data is used
*   Providing easy access to a human when needed   

Generative AI is arguably the most exciting technology to watch in the financial sector. But its effectiveness—and its impact on financial health—will ultimately hinge on whether consumers believe it is working in their best interest.

Those who can earn trust through reliable generative AI tools will help usher in a new era of deep, value-creating customer relationships. The next chapter of financial services will be written by those who understand that technology alone doesn’t earn trust—people do.