March 17, 2026
Miohael Lacorrazza
CMO
Compound Growth: How U.S. Bank uses AI to drive revenue and results
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Artificial intelligence in banking has moved from experimentation to execution. According to industry data, 70% of commercial banks have now adopted AI in at least one core function, and 78% of those investing in AI have seen positive ROI within 18 months. Gartner projects that 90% of finance functions will deploy at least one AI-enabled technology solution by 2026. The question is no longer whether AI will transform financial services. It is whether individual institutions are moving fast enough to capture the value.
US Bank is answering that question with action. In a recent episode of The Speed of Culture podcast, recorded live at CES 2026 in Las Vegas, Matt Britton sits down with Michael Lacorazza, Chief Marketing Officer at US Bank, to explore how one of America's largest financial institutions is operationalizing AI across marketing, customer experience, and product innovation. The conversation reveals a blueprint that extends far beyond banking—one that applies to any enterprise leader navigating AI transformation at scale.
What makes Lacorazza's perspective particularly valuable is that he is not describing what US Bank plans to do. He is describing what it is already doing: cutting campaign development cycles in half through synthetic audiences, generating tens of millions of dollars through AI-powered personalization, and using behavioral data to transform customer service in real time. As Britton frequently emphasizes in his AI keynote presentations, the gap between companies that talk about AI and companies that deploy AI is rapidly becoming the gap between market leaders and everyone else.
One of the most striking revelations from the podcast is how US Bank is using synthetic audiences to fundamentally accelerate its marketing process. For the bank's "Power of Us" brand campaign, Lacorazza's team partnered with Supernatural AI to create digital avatars modeled after six core target audiences—including young affluent individuals, high-net-worth clients, and small business owners. These AI-generated personas were used to test campaign strategy and creative concepts before any traditional research was conducted.
The results were dramatic. Campaign development time was cut from approximately six and a half months to roughly three months—a reduction of more than 50%. When the team ran parallel human validation testing alongside the synthetic audience results, they found approximately 95% correlation in the responses.
Lacorazza frames synthetic audiences not as a replacement for human judgment, but as a powerful accelerator. The technology allows marketers to explore sensitive topics—like how couples divide their finances—without making real respondents uncomfortable. It enables rapid iteration on creative concepts. And it frees human decision-makers to spend more time thinking strategically rather than waiting for traditional research timelines to deliver results.
For enterprise leaders, the implications extend well beyond marketing. As Matt Britton explores in his national bestseller Generation AI, synthetic audiences represent a broader shift in how organizations can use AI to simulate, test, and validate decisions before committing resources. The technology is still evolving—Lacorazza is careful to note that humans must remain the final decision-makers—but the speed advantage is already transforming competitive dynamics in financial services and beyond.
While much of the enterprise conversation around AI centers on automation and cost reduction, Lacorazza makes a compelling case that the most significant opportunity lies in using AI to drive growth. He identifies three distinct vectors where US Bank is already seeing measurable returns.
The first is customer experience improvement. When customers encounter friction in US Bank's digital channels—getting stuck while trying to move money or complete a transaction—and subsequently call the contact center, AI now feeds behavioral context into the CRM in real time. The call center representative can anticipate what the customer needs before the conversation begins, leading to faster problem resolution, higher satisfaction, and stronger loyalty.
The second vector is personalization, which Lacorazza says is already generating tens of millions of dollars in value. With permissioned customer data and high consumer expectations, US Bank uses AI to deliver tailored content, advice, product suggestions, and offers on a near-individual basis. The bank's mobile app even allows customers to connect accounts from other institutions, enabling features like subscription tracking across all financial relationships—a small but powerful example of data-driven value delivery.
The third is the Smartly product suite, which bundles checking, credit card, and savings products together with escalating rewards based on relationship depth. Early results show larger initial relationships, higher retention, and greater customer satisfaction. The same bundling philosophy has been extended to the small business segment.
This growth-first orientation aligns with a pattern Britton frequently highlights in his keynotes to financial services leaders: the institutions that treat AI primarily as a cost-cutting tool will capture a fraction of the value available to those that embed it directly into their growth engines. McKinsey estimates that generative AI alone could add $200 billion to $340 billion annually to the global banking industry—the majority through revenue enhancement and customer experience improvement rather than operational savings.
Perhaps the most pragmatic section of the conversation addresses a challenge that stalls AI adoption at many large organizations: getting cross-functional alignment across teams with very different risk tolerances and incentive structures.
Lacorazza identifies the partnership with legal and risk teams as a critical early unlock. Rather than positioning these functions as gatekeepers who say "no," US Bank reframed the relationship around a shared question: "How do we get to yes?". The mental model shifted from risk avoidance to risk navigation—asking what considerations, safeguards, and adjustments would be needed to move forward responsibly.
This reframing is significant because in highly regulated industries like banking, the legal and compliance functions have legitimate authority to halt innovation. When those teams operate from a posture of enabling rather than blocking, the entire organization moves faster. Lacorazza credits this partnership as one of the biggest accelerants in US Bank's AI journey.
He also addresses the human dimension directly. When new technologies are introduced, people feel threatened—worried about job elimination, confused by unfamiliar tools, or quick to declare early imperfections as evidence that the technology does not work. Lacorazza's approach combines three elements: casting a compelling vision that gives people excitement about where the organization is headed, inviting employees to co-create the transformation rather than having it imposed upon them, and openly acknowledging the anxiety that exists without dismissing it.
Britton adds an observation that resonates across industries: today's AI capabilities represent the worst the technology will ever be. If an organization can achieve acceptable results with current tools, the results will be extraordinary as the technology matures. The companies that build their operations around where AI is going—rather than where it was—will hold an insurmountable advantage. As Britton discusses in Generation AI, this forward-looking orientation separates transformational leaders from incremental ones.
The conversation takes an interesting turn when Lacorazza discusses US Bank's investment in sports partnerships—a strategy that predated his arrival as CMO but one he has leaned into aggressively. The bank sponsors and banks for multiple professional teams including the Vikings, 49ers, Timberwolves, and Clippers.
The strategic rationale is rooted in a fundamental shift in consumer behavior. Streaming has made entertainment consumption almost entirely individualized and on-demand. Social media has fragmented attention into short-form clips. Even younger sports fans increasingly consume highlights rather than full games—Lacorazza's own teenage son sends him clips from games he never actually watched.
In this landscape, live sports represents one of the last truly communal cultural experiences. It is one of the few remaining contexts where large audiences gather simultaneously, emotionally invested in a shared outcome. For a brand like US Bank, that communal energy creates opportunities for cultural relevance and emotional connection that are nearly impossible to replicate through other channels.
This insight connects to a broader theme that Britton explores in his keynotes to Fortune 500 audiences: as AI automates more of the functional value proposition in financial services, the brands that differentiate through cultural relevance and emotional resonance will capture disproportionate loyalty. Data and technology create the floor. Culture and connection create the ceiling.
One of the most forward-looking moments in the podcast comes when Britton and Lacorazza discuss data as the primary competitive differentiator in an AI-powered landscape. The logic is straightforward: if every institution has access to the same large language models, the organizations with the richest, most permissioned customer data will be able to deliver the most personalized—and therefore most valuable—experiences.
Lacorazza agrees but adds a critical caveat. The moat is not just data. It is trust in the data relationship. Customers must have crystal clarity about what they are opting into, what data is being used, and what value they receive in return. Without that transparency, personalization feels intrusive rather than helpful—and in financial services, where the information involved is deeply personal, the stakes are especially high.
This perspective is supported by research from McKinsey, which found that 71% of consumers now expect personalized interactions and 76% express frustration when those expectations are not met. For banks specifically, AI-driven personalization has been shown to deliver five times more engagement on offers, with potential revenue increases of 5 to 15% and customer acquisition cost reductions of up to 50%.
The subscription-tracking feature in US Bank's mobile app offers a practical illustration of this value exchange. By allowing customers to connect all of their financial accounts in one place, the bank can surface insights about recurring charges that customers may have forgotten about—a small, tangible benefit that demonstrates the value of data sharing and reinforces the trust relationship.
For enterprise leaders across industries, Lacorazza's framing provides a useful mental model: data advantage is not a static asset. It is a dynamic relationship that must be continuously earned through transparency, value delivery, and respect for consumer expectations.
Lacorazza closes with career insights that are particularly relevant for emerging marketing leaders. His path—spanning automotive at Lexus and Toyota, hospitality at Marriott, real estate, agency work, a CEO role at a consumer technology company, a decade at Wells Fargo, and now US Bank—illustrates the value of cross-category experience.
He offers two pieces of advice that stand out. First, be willing to make lateral or even backward career moves that expand your capabilities, especially early in your career when you have less to lose. The temptation to optimize for linear upward progression can limit the breadth of experience that ultimately makes a leader more effective and more versatile.
Second—and Lacorazza considers this even more important—learn the business. Understand how the P&L works, how customers make decisions, what the competitive landscape looks like, and what levers drive growth. A marketer who speaks in impressions and clicks will struggle to earn credibility with a CEO whose metric is growth. A marketer who understands the business fundamentals can sit at the leadership table as a true strategic partner.
His personal mantra encapsulates a philosophy that extends beyond career advice: find gratitude in life every single day, especially during moments of stress and adversity. It is a reminder that the pressure of transformation—whether personal or organizational—is itself a privilege.
US Bank partnered with Supernatural AI to create digital avatars modeled after its six core target audiences, including young affluent consumers and small business owners. These AI-generated personas tested campaign strategy and creative concepts for the "Power of Us" brand campaign, cutting development time from six and a half months to approximately three months. Parallel human validation testing showed roughly 95% correlation with the synthetic audience results.
According to US Bank CMO Michael Lacorazza, the highest-value AI applications in banking are growth-oriented rather than cost-focused. These include real-time customer experience improvement through CRM intelligence, hyper-personalization of content and product recommendations that is generating tens of millions of dollars in value, and product bundling strategies informed by behavioral data. Industry-wide, McKinsey estimates generative AI could add $200 billion to $340 billion annually to global banking.
The key is reframing the relationship between innovation teams and risk, legal, and compliance functions. Rather than positioning these groups as blockers, successful organizations ask, "How do we get to yes?" This means identifying the specific considerations, safeguards, and adjustments needed to move forward responsibly. US Bank credits this cross-functional partnership as one of its biggest accelerants in AI transformation.
Live sports represent one of the last communal cultural experiences in an era of fragmented, on-demand media consumption. For banks like US Bank, which sponsors and provides banking services to multiple professional teams, sports partnerships create opportunities for emotional connection and cultural relevance that are difficult to replicate through digital channels alone. As AI commoditizes functional product differentiation, cultural resonance becomes an increasingly important source of brand loyalty.
The conversation between Matt Britton and Michael Lacorazza reveals an institution that is not waiting for AI to arrive. US Bank is already deploying synthetic audiences, real-time CRM intelligence, and hyper-personalization at a scale that is generating measurable growth—while simultaneously investing in the cultural connections that technology alone cannot replicate.
For leaders across industries navigating AI transformation, the blueprint is clear: deploy AI for growth rather than just efficiency, build cross-functional alignment around enabling rather than blocking, earn data trust through transparency and value delivery, and maintain the human judgment and cultural awareness that give technology its meaning.
Hear the full conversation on The Speed of Culture podcast, and for a deeper exploration of how AI is reshaping consumer behavior and enterprise strategy, explore Matt Britton's national bestseller Generation AI. To bring these insights to your next leadership event or industry conference, visit Matt Britton's speaking platform or connect with his team directly.
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