The human side of AI financial advice
Researchers Dr. Daria Plotkina and Dr. Havva Orkut of EM Strasbourg Business School, and Dr. Meral Ahu Karageyim of the Center for Applied Research in Finance (CARF) recently co-authored the widely discussed article “Give Me a Human! How Anthropomorphism and Robot Gender Affect Trust in Financial Robo-Advisory Services.” We spoke with them to learn more about what makes the ideal robo-advisor and the strategies banks should adopt to build trust and engagement.
Researchers Dr. Daria Plotkina and Dr. Havva Orkut of EM Strasbourg Business School, and Dr. Meral Ahu Karageyim of the Center for Applied Research in Finance (CARF) recently co-authored the widely discussed article “Give Me a Human! How Anthropomorphism and Robot Gender Affect Trust in Financial Robo-Advisory Services.” We spoke with them to learn more about what makes the ideal robo-advisor and the strategies banks should adopt to build trust and engagement.
Could you please briefly describe your research, “Give me a human! How anthropomorphism and robot gender affect trust in financial robo-advisory services”?
Robo-advisors are becoming a major force in financial services. The global robo-advisory market grew from $14.25 billion in 2025 to $18.7 billion in 2026, representing a 31.3% CAGR. North America currently commands around 47% of the market, while Asia-Pacific is expected to be the fastest-growing region through 2030.
But growth does not automatically mean trust. Many consumers still hesitate to rely on automated financial advice, especially when money, risk, and long-term security are involved. Our research examines a simple but important question: Can the way a robo-advisor looks — more robotic, more human-like, male, female, or gender-neutral — influence consumer trust?
Across two experimental studies with U.S. consumers, we tested how different robo-advisor designs shape social presence, perceived competence, persuasiveness, and trust. The key insight is clear: people do not just evaluate the advice; they also evaluate the “advisor” that delivers it.
According to feedback I have received, a large number of retail investors trust robo-advisors more than human advisors. Is this a trend you are observing as well? How do you explain it?
Not necessarily.
There is a changing trend, but we cannot say this for all investors. Investors react differently to innovative digital technologies such as chatbots and robo-advisors.
Robo-advisors offer clear advantages: they are accessible, low-cost, available 24/7, and can provide standardized advice without human fatigue or judgment. But financial advice is a high-stakes service. Consumers are not only looking for speed and convenience; they also want reassurance, expertise, and confidence. This is why many people still prefer some form of human interaction, especially when decisions involve savings, investments, or retirement.
We may say that consumers still prefer human interactions in industries characterized by high consumer involvement, such as healthcare and financial services, despite rapid digitalization and automation. Several studies have shown that customers trust expert human advisors more. The future is therefore unlikely to be “human versus robo-advisor.” It is more likely to be human plus robo-advisor.
It is possible to give robo-advisors a physical appearance (such as robots, animals, or humans), as well as subcategories like gender or age? What type of appearance tends to be most suitable to the public for a robo-advisor?
Yes, it is possible to give robo-advisors a human-like appearance, name, avatar, and voice. These characteristics may affect customer perceptions. This is also closely related to the human tendency for anthropomorphism. Anthropomorphism entails attributing human-like properties, characteristics, or mental states to real or imaginary nonhuman agents and objects.
Our results suggest that human-like robo-advisors can increase trust, but the design must be handled carefully. A fully machine-like robo-advisor may feel too cold or distant. But a partly human, partly robotic design can also make users uncomfortable. In our study, the most successful design was not simply “more robotic” or “more futuristic,” but a clearly human-like advisor that increased perceptions of social presence, competence, and persuasiveness. In particular, it is unclear which level of anthropomorphism is optimal for financial services.
In other words, financial institutions should not humanize robo-advisors halfway. A confusing hybrid design can backfire.
Is there a gender bias in robo-advisors or AI-based investment tools, and if so, how can it be addressed?
Yes, absolutely. Our study shows a clear gender effect: consumers trusted human-like robo-advisors more when they were presented as male. This effect was explained by higher perceived competence and persuasiveness. This suggests that gender stereotypes still shape how consumers evaluate financial expertise, even when the “advisor” is artificial.
This is uncomfortable, but important. Financial services remain associated with masculine stereotypes, and these stereotypes can transfer to AI-based advisors.
We found that highlighting gender neutrality reduced the positive effect of human-like design on trust. For some users, gender neutrality made the robo-advisor feel less human or less socially present. This does not mean that firms should avoid inclusive design. But it does mean that gender-neutral AI design needs to be carefully tested. Simply removing gender cues may not automatically produce a better or more inclusive user experience.
A practical solution may be to let users choose the advisor’s voice, name, avatar, or interaction style.
Does the success of robo-advisors and approaches to robo-advisory services vary across different geographies or cultures?
Unfortunately, this is not an easy question to answer. From a theoretical perspective, the answer appears to be yes, as gender stereotypes differ across cultures. On the other hand, we need more empirical evidence from different cultural contexts before we can provide a definitive answer to this question.
Yes — robo-advisory success likely varies across geographies and cultures, because trust in automation, comfort with financial risk, expectations toward human advice, and reactions to gender or avatar cues are culturally shaped. Our study was conducted with U.S. consumers, so banks should not assume the same design will work everywhere. As the market expands globally — with North America leading and Asia-Pacific growing fastest — firms should test robo-advisor design locally. In short: the technology can be global, but trust is local.
An increasing number of retail investors are seeking advice from general-purpose AI tools, such as ChatGPT. What approach should banks take to regain leadership in investment advice?
Banks should not try to compete with general-purpose AI tools on convenience alone. Instead, they should reclaim leadership by offering what tools like ChatGPT cannot reliably provide: regulated, personalized, accountable, and context-aware financial advice. This means combining robo-advisory efficiency with the bank’s real customer knowledge, risk profiling, portfolio data, regulatory safeguards, and access to human advisors when decisions become complex. In our research, trust in robo-advisors depends strongly on whether the advisor is perceived as competent and persuasive, not merely friendly or human-like.
The winning model is therefore hybrid: AI for accessibility, speed, and routine portfolio guidance; human advisors for reassurance, explanation, and high-stakes decisions. Banks should design robo-advisors that feel professional, credible, and easy to escalate to a human expert. If they can make AI advice safer, more transparent, and better integrated into the customer relationship, they can turn general-purpose AI from a threat into a wake-up call.
Is there still a role for humans in providing investment advice to the general public? And if so, what is that role?
Yes, absolutely.
We know that with the rise of robo-advisors, investors now have a valid alternative to traditional human financial advice. We believe that both human advisors and robo-advisors will continue to be important in the future.
However, most research on social robots in banking underlines the importance of hybrid solutions. Trust is a critical factor in the adoption of robo-advisors and chatbots, and several strategies exist for building trust. A certain degree of human interaction can be effective in facilitating greater robo-advisor adoption.
A hybrid service model that combines human and robo-advisory expertise may facilitate adoption and support better financial decision making. Human advisors can provide explanations for complex financial products and tailor financial plans through face-to-face interactions with clients.
A collaborative relationship between human and robo-advisors may be more effective and beneficial for all parties involved.
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