Independent advisors lag in AI adoption. How to catch up

Independent financial advisors are adopting artificial intelligence more slowly than advisors employed by large firms. About 42% of independent advisors reported actively using AI, compared with nearly three-quarters of employee advisors, according to a J.D. Power study.

AI use among independent advisors rose from 19% to 42% in one year. The difference between the groups is linked to how firms select, integrate and govern technology rather than to a lack of access to AI tools.

Large firms, including wirehouses, generally have more resources to connect AI with existing systems, set usage rules and train employees. Wirehouses “have the ability to really build out this technology, integrate it into their platform, establish the rules and train the advisors,” said Joe McQuaid, chief operating officer of Concurrent Investment Advisors in Tampa, Florida.

Independent firms often make those decisions with smaller budgets and fewer technology and compliance employees. Basic AI systems that protect client information can cost thousands of dollars per month, adding to the expense for smaller practices.

DeepVest recently launched Day One, a package of AI tools for smaller firms. Dan Eyre, the company’s chief operating officer, said the tools are intended to give independent advisors a lower-cost entry point. He said advisors with sufficient time and access to appropriate technology can serve clients more efficiently.

Integration remains another issue. Some firms add AI features separately to customer relationship management, financial planning and other software. These systems may not share data, requiring advisors to enter the same information more than once.

“If AI is added to every one of the tools that we use, it still doesn’t solve the problem,” McQuaid said. “The data doesn’t flow back and forth between one system and another system.”

An integrated layer connecting several systems could reduce that problem, according to McQuaid. He recommended that firms identify specific operational problems before choosing technology, rather than buying multiple tools without a defined use.

Governance policies can specify which AI systems advisors may use and what information they may enter. McQuaid advised firms not to place personally identifiable information in AI models that are not designed for enterprise use.

Independent firms can review AI vendors through procedures similar to those used for customer relationship management and financial planning providers. Reviews can cover whether a vendor trains its models on client or firm data, how it has handled data incidents and what safeguards it offers for sensitive information.

Training is another difference between the groups. Large firms can add AI instruction to existing employee programs. Independent advisors may need to learn how to use and supervise the tools without dedicated training staff. Without clear rules, advisors may not know whether they can enter a client’s name or other confidential information into a particular system.

James Spinelli, founder and chief executive of Great Valley Advisor Group in Berwyn, Pennsylvania, leads a firm with 215 advisors and just under $15 billion in assets under management. He described standardizing some technology systems as one way to increase adoption, while noting that removing all technology choices could reduce flexibility.

Spinelli expects independent advisors’ AI use to increase as firms establish clearer policies and procedures. McQuaid recommended that smaller firms consider established, off-the-shelf products instead of building AI infrastructure from the ground up. After deployment, firms can measure whether the technology saves time and improves client service.