While conversations about AI in wealth management focus on capability, as a sociologist, I’m interested in what happens when clients are asked to trust advice generated, at least in part, by machines.
Wealth management has always depended on relationships, and trust is central to that because clients rely on the expertise involved in financial planning. AI doesn’t remove this dependence, and understanding how trust works in the bigger picture of wealth management can help advisors navigate the relationship between AI and their clients.
In this article, I explain how AI shifts the main source of trust from just humans to both humans and AI systems.
Trust Has Always Been the Foundation of Advice
Sociologist Anthony Giddens suggested that everyday life increasingly depends on what he called “expert systems”. These are networks of professional knowledge and technical expertise that ordinary people rely upon without fully understanding how they work.
Healthcare is an example of an expert system. We trust that doctors are qualified, lab tests are accurate, and medicines have been tested and approved. We might not understand exactly how MRI scans work or how drugs are developed, but we place our trust in this system.
In everyday life, most of us rely on a variety of expert systems involving expertise beyond our own knowledge, and this trust enables modern society to function efficiently.
Our lives therefore involve both trust and risk.
Trust and Risk
Because we rely on expert knowledge, we may find it hard to act without trust, since we lack the expertise to evaluate every system we encounter.
Wealth managers see this often – A surgeon may understand medicine but rely on an advisor to structure their retirement plan. A successful entrepreneur may understand business operations but depend on an advisor for estate planning. Clients follow recommendations because they trust their advisor, and trust enables them to make major financial decisions.
Giddens’ perspective clarifies that wealth management involves more than just technical skills and highlights how AI integration alters this dynamic.
AI Changes the Object of Trust, Not the Need for Trust
These systems are changing who clients are asked to trust. Financial advisors serve as what Giddens called an “access point” to expert knowledge. Clients rely on them to explain complex concepts, so they don’t need to understand every detail themselves.
AI is also helping create new ways for clients to access services alongside advisors. Wealthtime recently conducted research by speaking with 175 advisors. Many advisors reported that clients are using AI to prepare questions before meetings and to check their advisor’s advice afterwards.
So, AI is now becoming part of the expert system itself and is emerging as a source of ‘cognitive authority’. This is the ability to influence what people regard as credible knowledge. They still see advisors as important, but they are no longer the only gateway to financial expertise.
Clients now have to decide how to balance trust between human expertise, algorithmic systems, and their own judgement. This changes the advisor-client relationship as clients are now required to trust the technology behind the advice they receive.
So, how do advisors build trust in a system that most clients cannot see?
Research suggests this is already happening. In a 2025 survey, researchers at Stanford Graduate School of Business found that more than half of Americans had asked AI for financial advice. Only around 40% had worked with a human advisor.
When generative AI talks about money, many people are willing to listen. Trust is therefore moving beyond traditional professional relationships. People still seek financial advice, but a key question we should be asking is who or what they trust to provide it.
What Trust Looks Like in Practice
Imagine an ultra-high-net-worth client receives a recommendation to reduce exposure to public equities and increase allocations to private markets. The recommendation comes from an AI-powered platform that has analyzed market conditions, liquidity needs, historical patterns, and the client’s broader financial goals.
The client’s first question is likely to be about credibility rather than technicality:
- “Why are we doing this?”
- “Can you explain the reasoning?”
- “How confident should I be?”
The client examines how the recommendations are made instead of focusing on the recommendations themselves. These questions tell us something important about AI-powered advice.
The Hidden Risk Is Over-Trust
Over-trust in AI systems is also a concern due to the potential for automation bias. This is the tendency to place excessive confidence in automated systems because they appear objective, data-driven, or modern. Ian Stanley’s 2025 research found that people are more likely to trust AI suggestions when they believe they are credible, clear, and genuine.
The IIF-EY Annual Survey on AI use in financial services highlights the importance of governance, oversight, transparency, and risk management in AI adoption. These are factors that are likely to influence users’ confidence in these systems. Sophisticated outputs can create an illusion of certainty and lead to automation bias.
An algorithm may present precise recommendations, and a model may generate a seemingly definitive answer, but markets are still unpredictable, and wealth planning still depends on careful judgment. It’s still important to think critically and rely on human judgment, especially since it is easy to mistake AI’s polished, seemingly confident outputs for accuracy.
Why AI Could Increase the Value of Human Advisors
We may worry that technology will replace the need for human advice, but this is not the case. An advisor’s role is increasingly about communication. For example, when planning for a family business succession, AI can estimate taxes and compare ownership options. However, it can’t help family members agree on their shared legacy or sense tension in a room.
Similarly, AI can calculate retirement plans for someone who has recently lost a spouse, but it can’t offer comfort or empathy during a difficult life change.
These human qualities are still essential, and so skills like understanding and connecting with people are becoming even more important. Human touch and understanding matter more than ever.
The Advisor as Interpreter and Translator
Industry research shows clients are increasingly using AI alongside advisors. As expert systems become more complex, clients need guides who can make them understandable and trustworthy, and this is an important sociological insight.
As AI becomes more sophisticated, advisors become more important because they help clients understand these complex systems. They act like translators, turning computer algorithms into conversations and probabilities into decisions.
Firms must combine technological capability with human trust, and advisors will be valued less for producing information and more for helping clients make sense of it.
Trust Remains the Competitive Advantage
The wealth management industry is right to be excited and worried about AI. The technology can improve efficiency and analytical capability. Sociology reminds us that financial advice is both a technical process and a social one.
Instead of acting because a model produces an answer, clients are more likely to do so when they trust the people and systems behind it. A challenge for wealth management is less about persuading clients to trust advice and more about helping them understand when to place that trust in people, technology, or both.
