Your Customers Are Already Deploying AI Agents. Are You Ready to Respond?
By Morgan Smith, Reporter at The Financial Brand
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Executive Summary
- The crux of “generative engine optimization” is creating content that’s not just readable to people or traditional search engines like Google Google, but also to AI agents acting in customers’ stead.
- Data from Alkami’s Perceptions Research show 82% of regional and community financial institutions believe AI will have had more of a positive than a negative impact on the industry overall and are experimenting with new AI technologies — including agents.
- Despite the excitement around AI agents and the technology’s potential to improve online banking experiences, bank marketers shouldn’t rush in blindly.
Artificial intelligence is becoming rapidly embedded in our daily lives, from fast food drive-thru screens to voice assistants. Nearly a third of U.S. adults interact with AI “almost constantly,” or at least several times a week, according to The Pew Research Center.
AI isn’t just changing how consumers order groceries or answer emails. It’s also transforming how they manage their finances. People are increasingly bypassing traditional search engines for AI-powered tools like ChatGPT to find information on checking accounts, credit cards, mortgage rates and more.
The rise of AI marks a fundamental disruption in how financial institutions attract and influence customers. AI agents, able to perform tasks, make decisions and even complete purchases autonomously, can potentially transform online banking. Instead of clicking through websites or ads, consumers are starting to rely on AI bots to do the legwork for them.
“Financial institutions should consider AI agents and generative search tools like ChatGPT or Google’s Gemini as the influencers of the future — they’re constantly learning and serving up content from the brands they find most helpful,” Sharon Cook, vice president, marketing strategy at Vericast, tells The Financial Brand. “This is a paradigm shift for bank marketers, and those who move early can gain a real competitive edge.”
It’s a step change that will require financial institutions to rethink the way they advertise, post on social media, describe their offerings online — and even price them. In the past, bank marketers might have focused on optimizing content for search engines. But in the era of AI agents, visibility depends on how clearly and accurately a financial institution’s website and social media content can be understood and retrieved by AI bots.
Or, as Cook puts it simply: “Bank marketers must learn how to influence the AI influencer.”
Generative Engine Optimization Is the New SEO
Some marketers call this next frontier “generative engine optimization” — creating content that’s not just readable to people or traditional search engines like Google, but also to AI agents acting in customers’ stead.
Melissa Stevens, CMO and EVP at Fifth Third Bank, compares this moment to the early mobile era — when banks had to overhaul their websites for smartphone use. Today, the challenge is structuring those same sites for AI.
”Financial institutions are going to have to get better at making sure their search engine optimization is ideal, that they’re pithy in the way that they are talking about and positioning their products, their services, their differentiators,” she says.
It’s an initiative Stevens and her team at Fifth Third Bank have been working toward for “years,” she adds. Fifth Third is among the traditional banks leveraging AI via its chatbot, Jeanie, to manage customer inquiries.
“While it’s still a relatively new world for marketers, the idea of generative engine optimization — of the way Gen AI is going to cull all that data and produce it even in Google search results — is something that if people are not paying close attention to, they need to,” Stevens explains.
But before banks can optimize for AI, they need to clean up their data, Allison Cerra, chief marketing officer at Alkami, a digital banking solutions company, tells The Financial Brand.
Dig deeper:
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“Getting your data house in order is crucial because data is the oil to any of these models,” she says.
That includes identifying and fixing duplicated records, filling in missing data, ensuring product information is accurate and written in clear, simple language, and standardizing key terms so AI tools can easily understand and categorize the information.
AI agents rely on structured, specific content: FAQ pages, clear, keyword-rich product breakdowns, and localized descriptions, Cook explains. She recommends bank marketers do an “AI audit” of their financial institution’s website, experimenting with different prompts on free generative AI tools like ChatGPT to assess whether or not information can be easily extracted and understood by these tools.
“If you ask ChatGPT to recommend a local bank for you, what it comes back with depends entirely on what content that bank has made available publicly and how that content is structured,” Cook says. “Many financial institutions haven’t thought about this yet.”
Why Hyperlocal Content Matters
This shift could actually give smaller banks and credit unions a competitive advantage in the ever-crowded digital banking space — if they act quickly.
“Consumers still care about proximity, even if they’re not visiting a branch every week,” Cook says. “So when an AI agent is deciding which bank to recommend, the one that has the most clearly structured, localized content will likely win.”
Recent research from Alkami indicates that while larger financial institutions often lead in AI adoption, a noteworthy segment of smaller banks — those with assets under $500 million — are emerging as progressive adopters of AI technologies.
A separate report, Alkami’s Perceptions Research, found that 82% of regional and community financial institutions believe that AI will have had more of a positive than a negative impact on the industry overall and are experimenting with new AI technologies, including agents.
“We’re in the early innings of AI adoption, and there are a lot of large banks that have been slowly implementing AI in their digital storefronts for years,” says Cerra. “But success with AI agents isn’t about being the biggest, it’s about being the best.”
Cook encourages smaller financial institutions to lean into what makes them unique: things like specialized local programs, financial literacy initiatives, and community ties.
“If your website says, ‘We’ve served Atlanta for 100 years and here’s what we offer students and first-time homebuyers,’ when well structured, that’s information an AI agent can use to surface you to potential customers,” Cook says. “You want to be found by the machine, but you want to talk to the human… that’s the crux of where bank marketing is going next.”
Personalization Is Evolving Into Anticipation
Personalization has long been a pillar of financial marketing, but generative AI is pushing that concept further. Now, it’s not just about responding to needs, but anticipating them.
“At its best, predictive AI agents should be able to anticipate your needs with little to no direction and make banking transactions more seamless,” Cerra says. “It can flag upcoming bills, help you manage your own debt, and stay in control of your finances.”
Still, limitations remain. Stevens notes that while Fifth Third’s AI assistant Jeanie is powerful, it’s built to support — not replace — the human experience.
“Jeanie handles over 150 intents … and does it seamlessly,” she says. “But we want AI to be an augmentation to the human banking experience.”
As banks push further into AI, model explainability and regulatory compliance become paramount.
“Beyond cleansing and codifying your data, you must ensure the AI model is compliant with banking regulations,” Cerra says. “The most data-fluent FIs are moving into the domain of model transparency. They’re confronting higher-order data challenges: making sure these AI agents are nonopaque, that they’re ethical and non-discriminatory.”
Strategy Over Hype
Despite the excitement around AI agents and the technology’s potential to improve online banking experiences, bank marketers shouldn’t rush in blindly.
“Applying an autonomous agent for the sake of applying AI is not the right path for bank marketers,” Stevens points out. “Ask instead: How do I make things simpler and more efficient for customers, and where does an agent make sense? Those that introduce an AI agent just to do it and brag about it, are not actually making things better for the consumer.”
Bank marketers should begin by identifying the outcomes they want to achieve, and only then explore how AI agents, or an AI-focused marketing strategy, can enable them. “Some institutions get swept up in the hype of new technologies,” says Cerra. “But you have to flip the script. Start with the business strategy, then look at how AI can support it — not the other way around.”
