Trust: The Most Overlooked Factor in AI Adoption

Article by: Carmen Elio, Chief Revenue Officer, Helix

In an era of rapid digital transformation, it’s easy to get caught up in the “how” of artificial intelligence—how it’s built, how it’s deployed, how it scales. But the more important question is one we don’t ask enough: Do we trust it?

Trust, long the bedrock of wealth management, is no longer confined to relationships between people. It now extends to the systems, data, and insights guiding those relationships. As AI becomes embedded in decision-making, due diligence, and portfolio construction, the success of those tools will hinge less on what they can do, and more on whether people believe in them.

Three Dimensions of Trust in Wealth Management

  1. Client to Advisor
    Clients want to know their advisor understands them—not just their finances, but their goals, fears, and values. If AI is introduced into this relationship, clients will need to trust that it’s being used to deepen personalization, not automate empathy.
  2. Advisor to Firm
    Advisors want to know the insights they receive are credible, compliant, and aligned with their firm’s philosophy. When AI outputs contradict experience or lack transparency, adoption stalls—not due to technology failure, but because of a breakdown in trust.
  3. Firm to Provider
    Firms depend on third-party platforms and data sources to deliver solutions. But concerns about data security, regulatory exposure, and misaligned incentives can erode confidence before a single pilot even begins.

The Trust Gap Is Real—and Measurable

A 2024 Accenture report found that only 35% of financial services professionals fully trust the AI tools they use.1 Meanwhile, 67% identified lack of trust as the biggest barrier to broader adoption. This gap is costly—not just in dollars, but in missed opportunities to serve clients better and operate more effectively.

On the flip side, firms that build trust into their AI strategies—through explainable outputs, human-centered design, and secure workflows—are already outperforming. McKinsey data suggests that such firms can outpace peers by 20% in revenue growth and operational efficiency.2

Rebuilding Trust in the AI Era

So how do we get it right?

  • Transparency: Advisors and clients must understand how outputs are generated. Explainability is non-negotiable.
  • Consistency: Insights should align with firm philosophies and not contradict the advisor’s expertise.
  • Security: Data privacy must be foundational, not optional.
  • Collaboration: AI should enhance the human experience, not sideline it.

This isn’t just a tech strategy—it’s a leadership imperative. The firms that will lead the next chapter of wealth management are those who treat trust not as a soft concept, but as a hard requirement in every layer of their AI roadmap.

Because at the end of the day, it’s not the algorithms that drive value—it’s the confidence people have in using them.

To learn more about Helix, schedule a demo.


1Accenture, “AI in Financial Services: The Trust Imperative” (2024)
2McKinsey & Company, “The State of AI in 2024” (November 2024)

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