Recognizing the surging impact of artificial intelligence in wealth management, the Financial Planning Association (FPA) has launched
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The platform aims to help financial advisors better understand the opportunities — and challenges — of AI, said FPA CEO Dennis Moore. Created in partnership with
But the launch is “just a starting point,” said Moore.
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The plan is to feature frequently updated content that keeps members informed on key AI developments, he said.
“As we work through this, we will try to ascertain the information our members want to see to help inform future content that will be made available,” Moore said.
William Trout, director of securities and investments at technology data firm Datos Insights, said he sees both promise and gaps in the platform’s content structure. The platform’s focus on governance and risk management is essential, he said, as advisors need frameworks for vendor evaluation, data privacy protocols and regulatory compliance before they deploy any AI tools.
“The emphasis on practical application over theoretical understanding also aligns with what advisors actually need,” he said.
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Making sure the content is meaningful
Trout said the platform should address the practical implementation questions advisors face when their compliance department asks, “Can we use this tool?”
Moore said the FPA believes providing demonstrations of how AI tools and platforms function is important.
“Many planners need to see how these operate and the opportunities they provide to be more productive and efficient,” he said.
But demos are just one part of FPAi Authority, said Moore.
“We want to use this to help members understand what’s trending and happening within this dynamic space,” he said. “There are certainly going to be opportunities to help members understand the potential dangers and challenges with AI, which will be part of this program.”
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Opportunities to go deeper
Even with the important topics and demos in the platform’s initial release, Trout said there are many areas that could be useful for advisors to explore further.
One such area is communication and disclosure frameworks, which he said could include guidance on how to explain
“When does AI assistance require explicit client notification versus being treated as internal operational tooling?” he said.
Liability and professional responsibility boundaries are another area of paramount importance, said Trout, especially identifying where advisor judgment ends and algorithmic recommendation begins.
“If an AI tool suggests a strategy that proves suboptimal, what’s the advisor’s liability exposure?” he said. “The program needs explicit case studies on E&O insurance implications and fiduciary duty when using AI tools.”
Data quality and model limitation recognition should also be addressed, Trout said, as advisors need to understand what their AI tools don’t know. Understanding training data vintage, recognizing when models are operating outside their design parameters and identifying situations where human judgment should override algorithmic output are all key components, he said.
“This is especially critical for specialty planning scenarios like special needs trusts, concentrated equity positions and business succession,” he said.
Evaluations of vendor platforms could also help advisors understand which tools really deliver and which are just marketing hype, Trout said.
Moore said the platform will evolve to include more content and has the flexibility to adjust as needed, he said.
“We will be able to view back-end metrics to understand what members are engaging with — and what they are not — to decide what new content needs to be added to meet the needs of the membership,” he said. “This will be an iterative process.”
