LOOKING BACK | Is Financial AI the Choice of a New Generation?

We are not just a child of the Cold War, we're a child of the Cola Wars, too. 

We were born into and grew up during an age where Pepsi-Cola actually competed closely with Coca-Cola for market share. Where an alternative soft drink to King Coke attempted to capture a "Pepsi Generation," even calling itself the "choice of a new generation," and for a time, succeeded, with a gap in market share measuring a mere percentage point or two apart. 

PepsiCo became an impressive conglomerate, but it lost the Cola Wars. Today, Coca-Cola boasts an 18.5% to 19.2% share of its market, while Pepsi-Cola has fallen to around 8.1% to 8.3% of the soft drink market. While Coke has asserted its dominance, Pepsi has floundered further by losing long-time restaurant partners like KFC. 

While its sweeter flavor often won them over in taste tests, Pepsi never really became the choice of young people because soft drink brand preferences are more based on household loyalty and familiarity than age or generational identity. 

Similarly, we've been told in the past that crypto is a currency for younger people, but as a middle aged parent, I spend quite a bit of time around younger people who are entering or who have just entered the workforce, and not one of them seems to care a lick about anything cryptocurrency related. The cryptocurrency universe feels like Pepsi—it's actively trying to market itself towards younger people, but age and generational identity are only one of the factors impacting the decision to access a currency or banking service. Today, we're being told that prediction markets are for the young. 

We'll leave the ethical issues of these appeals to younger, less-experienced audiences with caffeine-saturated beverages, crummy financial products and awful bets for a later diatribe. There's probably a cryptocurrency version of Joe Camel out there, folks. 

Anyway, what about financial artificial intelligence? We assume that younger people are more likely to use financial AI, and as a matter of fact, we do have plenty of research that seems to bear that out. But we believe that there might also be forces stronger than age or generational identity working on our preferences for technology and financial advice itself, and these will carry over into people's thoughts and feelings about AI. 

We already know that younger Americans are increasingly comfortable consulting AI chatbots about budgeting, investing, borrowing and other financial decisions, while older consumers are more inclined to rely on established financial institutions and human advisors. Yet younger consumers are not universally enthusiastic about AI, older Americans are not uniformly resistant to it, and financial institutions risk misunderstanding their customers if they assume that age alone determines technological preferences. 

The divide is especially important because it intersects with an older and more consequential imbalance: the distribution of wealth. Baby Boomers and older Americans control a disproportionate share of household assets, while Millennials and Generation Z are building financial lives around digital services, mobile applications and increasingly conversational AI. The consumers most comfortable with emerging financial technologies are often those with the least accumulated wealth, while those who control the greatest assets may have less interest in turning their financial decisions over to algorithms. 

This creates a strategic dilemma for financial institutions. Should they develop AI-first services to attract younger customers, preserve human-centered advice to retain older ones, or attempt to combine both approaches? And will the distinction between AI enthusiasts and skeptics persist as younger generations age and older generations become more familiar with the technology? 

The answers suggest that generational preferences matter, but that financial institutions should resist building their technology strategies around generational stereotypes. 

The Generational Divide in Financial AI 

Generation Z, generally defined as people born between 1997 and 2012, is the first generation to enter adulthood with widely accessible generative AI. Its members are accustomed to obtaining information through digital interfaces, social media, mobile applications and, increasingly, conversational assistants. For some, asking ChatGPT or another AI system about an investment is no more unusual than searching Google for a mortgage rate. 

Millennials, born between 1981 and 1996, occupy a somewhat different position. They experienced the transition from traditional internet services to smartphones, mobile banking, robo-advisors and generative AI. Many are now managing mortgages, retirement accounts, education expenses and growing investment portfolios. Their interest in financial AI often reflects a desire to simplify increasingly complicated financial responsibilities. 

Generation X, born between 1965 and 1980, is generally more selective. Its members have adopted online banking, electronic trading and digital investment platforms, but may approach generative AI as another tool rather than an entirely new way to manage financial relationships. Many are simultaneously preparing for retirement, supporting children and assisting aging parents, making reliability and security particularly important. 

Baby Boomers, born between 1946 and 1964, are generally the most cautious about using generative AI for financial decisions. They are more likely to have longstanding relationships with banks, financial advisors and other professionals, and may be less interested in replacing those relationships with unfamiliar technology. 

The differences appear in research about financial AI. Survey findings summarized in recent industry discussions suggest that approximately 45% to 48% of younger investors are comfortable receiving direct financial guidance through AI-enabled services. Meanwhile, one set of survey figures indicates that 72% of Boomers and 56% of Gen X respondents have never used AI to ask a financial question. The figures come from differing research contexts and should not be treated as directly comparable measures of adoption. 

The pattern is nevertheless consistent: younger adults are generally more willing to experiment with AI as a source of financial information, while older adults tend to place greater value on human judgment, institutional credibility and established relationships. 

Importantly, using AI for financial information is not the same as trusting it with financial decisions. A 25-year-old might use a chatbot to explain exchange-traded funds, compare credit cards or model retirement savings without allowing the system to execute transactions. Similarly, a 65-year-old might distrust chatbot-generated investment recommendations while benefiting from AI-powered fraud detection, tax analysis or portfolio monitoring. 

Age is also entangled with education, income, occupation, digital literacy and access to technology. A 60-year-old technology executive may be considerably more comfortable with AI than a 23-year-old whose employment provides little exposure to it. An affluent retiree with an established advisor may have little incentive to experiment with AI financial planning, while a younger worker unable to afford professional advice may view a chatbot as an indispensable resource. 

The critical distinction is therefore not simply between young and old, but between consumers who see AI as an accessible solution to unmet financial needs and those who see it as an uncertain alternative to services they already trust. 

Generational Differences in Financial Needs and Access to Advice 

The financial AI divide cannot be understood without examining the distribution of wealth and access to financial advice. 

Older Americans control most of the country's household wealth. Federal Reserve distributional data consistently show that households headed by older adults hold a disproportionate share of financial assets, retirement savings and home equity. Baby Boomers benefited from decades of asset appreciation, while many younger households are still accumulating wealth and confronting substantial housing, education and borrowing costs. 

These circumstances create very different financial needs. 

Gen Z consumers are often concerned with student debt, credit building, budgeting and establishing emergency savings. Millennials are increasingly focused on homeownership, family finances, retirement accumulation and competing financial obligations. Gen X faces more immediate retirement planning decisions, including healthcare expenses, college funding and caring for aging parents. Boomers are generally more concerned with retirement income, taxes, estate planning, healthcare and transferring wealth to younger generations. 

These differences help explain why financial AI may appeal to younger consumers. Traditional financial advice can be expensive or inaccessible, particularly for households with modest assets. Many wealth management firms impose minimum investment requirements or charge fees that make comprehensive advice difficult to justify for consumers with relatively small portfolios. 

Generative AI changes the economics of obtaining basic financial information. Someone with $2,000 in savings can ask a chatbot about budgeting, compound interest or retirement accounts without meeting an advisor's asset minimum or paying an hourly consulting fee. 

However, the availability of information does not necessarily produce sound financial decisions. AI systems can generate inaccurate recommendations, misunderstand tax rules, overlook personal circumstances and present uncertain information with unwarranted confidence. Consumers with limited financial literacy may have difficulty recognizing these problems. 

Conversely, older and wealthier consumers frequently need the type of sophisticated advice that AI cannot reliably provide independently: coordinating estate plans, evaluating concentrated stock positions, managing retirement withdrawals, addressing family disputes and navigating complex tax obligations. 

Still, the assumption that younger consumers prefer AI instead of advisors is increasingly questionable. 

A September 2026 survey from Betterment Advisor Solutions provides particularly revealing evidence. The study surveyed 1,001 U.S. investors who had worked with a financial advisor for at least a year. It found that 75% used AI at least occasionally for financial tasks, but only 3% would consider replacing their advisor with an AI-powered alternative. Moreover, 76% said they would still want a human advisor even if AI could answer most of their financial questions. 

Younger clients were especially engaged. Betterment reported that 65% of Gen Z clients were influenced by AI, while 83% contacted their advisors monthly. Rather than replacing the advisor, AI appears to be helping some investors become more informed and demanding clients.  

The implication for wealth managers is substantial. Generative AI could democratize financial education and basic planning while simultaneously increasing demand for professional judgment. A younger investor who has already researched retirement strategies through AI may expect an advisor to provide more sophisticated analysis, personalization and reassurance. 

Financial AI could therefore expand the market for advice rather than simply cannibalizing it. 

How Generational Fintech Preferences Carry Over to Financial AI 

The generational divide in financial AI is partly an extension of longstanding differences in financial technology adoption. 

Gen Z and Millennials have grown accustomed to mobile banking, digital wallets, electronic payments, automated investing and financial applications that provide immediate access to account information. Services such as Robinhood, Chime and Revolut illustrate how financial services have increasingly moved beyond conventional banking relationships. 

For these consumers, the financial institution is not necessarily a branch, a banker or even a single application. It may be an interconnected collection of services handling different financial needs. 

A February 2026 Deloitte analysis challenged conventional assumptions about differences between Gen Z and Millennials. Based on a survey of 2,027 U.S. banking customers, Deloitte found that the two generations were becoming increasingly similar in their digital banking behavior, willingness to share financial data and expectations for convenience. 

The researchers suggested that differences between the two groups often reflected financial life stages rather than distinct generational identities. A younger worker and a Millennial homeowner may need different products, but both increasingly expect seamless digital access, personalization and integrated financial information.  

This matters because AI can become another layer within the fintech ecosystem, connecting services that previously operated independently. 

A conventional budgeting application might categorize transactions and display spending patterns. An AI-enabled application could explain why spending increased, identify potential savings and answer follow-up questions in ordinary language. Similarly, an investment platform could move beyond displaying performance figures to explaining portfolio exposures, tax considerations and alternative scenarios. 

Gen X consumers, meanwhile, have already demonstrated considerable willingness to adopt financial technology when it provides tangible benefits. Digital bill payment, online brokerage services, retirement planning software and account aggregation are well established among middle-aged consumers. AI adoption may follow the same trajectory if its benefits are obvious and the technology is trustworthy. 

Boomers also use fintech extensively, although their priorities can differ. Secure account access, fraud prevention, reliable customer service and understandable information may be more important than experimental features or highly automated financial decision-making. 

Research released in September 2026 by Alkami Technology and the Center for Generational Kinetics reinforces these distinctions. The study of 1,500 digital banking consumers found that 57% of Gen Z respondents sought financial education from their primary provider, while 65% of Millennials were comfortable with AI-enabled experiences supporting spending, security and everyday financial management. 

Among Gen X respondents, 91% considered telephone support important and 87% prioritized online virtual assistance. For Boomers, 92% emphasized protecting their financial data against fraudsters and hackers. 

Across generations, 85% said digital banking quality was important or essential when evaluating a new primary provider.  

These findings suggest that financial institutions should not equate older consumers with resistance to digital services. Instead, they should recognize that customers of different ages may prioritize different outcomes from the same technology. 

For a Millennial, an AI assistant might be most valuable when coordinating bills, savings and household finances. For a Gen X customer, it could help analyze retirement readiness or identify unusual account activity. For a Boomer, it might provide understandable explanations of retirement distributions while helping identify suspicious transactions. 

The underlying technology could be nearly identical. Its presentation, safeguards and purpose would differ. 

How Attitudes Toward AI Generally Shape Financial AI Adoption 

Generational differences in financial AI also reflect broader attitudes toward artificial intelligence. 

Younger adults have been quicker to experiment with generative AI, often using it for education, writing, research, workplace productivity and personal decisions. Millennials have also embraced AI for professional and personal tasks, while Gen X and Boomers have generally adopted conversational tools more selectively. 

However, the divide is narrowing. 

Research published in June 2026 by the Pew Research Center found that 49% of American adults had used AI chatbots, up from 33% in 2024. Among adults ages 18 to 29, usage reached 66%, compared with 61% among those ages 30 to 49, 42% among those ages 50 to 64 and 23% among those 65 and older. 

Perhaps the most important finding is that adoption increased across every age group. Adults in their 30s and 40s have nearly caught up with those under 30, challenging the notion that AI is primarily a Gen Z technology. 

Pew also found that daily chatbot usage was reported by 31% of adults ages 18 to 29 and 34% of those ages 30 to 49, compared with 19% of those ages 50 to 64 and 7% of those 65 and older. 

The difference between occasional experimentation and habitual use matters for financial services. Consumers who regularly use AI may become comfortable providing detailed prompts, evaluating responses and incorporating the technology into their workflows. Others may need more explanation, guidance and reassurance before trusting it with sensitive financial questions. 

Yet younger users are not necessarily uncritical AI enthusiasts. Pew found that majorities across age groups believed AI was advancing too quickly, with responses ranging from 61% to 65%. Younger adults may simultaneously be heavy AI users and concerned about employment displacement, misinformation or the broader consequences of automation.  

These concerns become particularly consequential when AI enters financial services. 

An inaccurate restaurant recommendation may cause inconvenience. An inaccurate retirement withdrawal strategy, mortgage recommendation or tax calculation could cause lasting financial harm. Even consumers comfortable using AI for everyday tasks may hesitate to entrust it with investment decisions or sensitive account information. 

Trust also depends on how AI is delivered. A consumer might distrust a general-purpose chatbot's stock recommendations while accepting AI-assisted analysis delivered through a regulated financial institution with clear accountability and human oversight. 

Financial AI adoption may consequently depend as much on the credibility of the institution providing it as on the consumer's generation. 

Is Financial AI Really Just for the Young? 

The evidence suggests that financial AI is not exclusively for younger generations, nor should financial institutions treat it as such. 

There is a meaningful distinction between offering AI technology and requiring customers to interact directly with it. A Boomer who never opens ChatGPT might nevertheless benefit from AI-powered fraud detection, portfolio risk analysis or retirement income modeling. A Gen X client might receive more personalized financial planning because an advisor uses AI to analyze tax documents, account information and alternative financial scenarios. 

Even among younger customers, enthusiasm for technology should not be confused with enthusiasm for eliminating human assistance. 

Betterment's 2026 findings illustrate the point. Nearly two-thirds of Gen Z and Millennial investors said poor technology or a cumbersome digital experience could influence their decision to change advisors, compared with 28% of Boomers. Yet the survey also found that trust in an advisor's expertise was the leading reason clients remained with their advisors.  

The opportunity is to use AI to strengthen human relationships rather than replace them. 

Financial institutions should also distinguish between generational effects, age effects and economic circumstances. A generation may develop enduring preferences because of its formative experiences, but consumers' financial needs change as they age. A 30-year-old who currently relies on AI for basic financial education may eventually seek comprehensive estate planning, while a 70-year-old who has avoided chatbots may become an enthusiastic user of AI-powered retirement tools. 

Moreover, technology adoption is influenced by income, education, professional experience, accessibility and financial complexity. Age-based segmentation alone can obscure these factors and lead institutions to underestimate entire groups of potential customers. 

A more effective strategy is to offer adaptable services. Customers who prefer digital self-service should have access to understandable AI tools. Those who want human assistance should be able to obtain it without unnecessary friction. Financial institutions should also provide clear disclosures about AI limitations, protect sensitive information, maintain appropriate supervision and establish accountability for consequential financial recommendations. 

For wealth managers, the arrival of financial AI creates another challenge: clients increasingly have access to much of the same general financial information that advisors once provided. As AI makes basic explanations and preliminary analysis widely available, the advisor's value proposition must increasingly emphasize judgment, contextual understanding, behavioral coaching and the ability to help clients act on complicated financial decisions. 

The same principle applies to banks and fintech companies. Financial AI should be evaluated by its ability to improve financial outcomes, not merely by the number of consumers interacting with a chatbot. 

Ultimately, generational differences provide a useful starting point for understanding customer expectations, but they are a poor substitute for understanding individual financial needs. 

The future of financial AI is unlikely to be defined by a permanent contest between digitally adventurous young consumers and technology-resistant older ones. Instead, the industry may discover that the most successful applications are those that make financial services more accessible, accurate, secure and personalized for everyone. 

Researched by DWN Staff