Savvy financial advisors know that mastering the most advanced technology on the market is essential to staying competitive, relevant and growth-minded. So, it’s no surprise that generative AI has seen meteoric adoption.
More than eight out of 10 advisors already have access to AI tools for use in some aspect of their practice, according to Advisor 360°’s 2024 “AI & the New Gen Advisor report.” Yet despite the widespread availability of AI tools, only half that number are actually using them. Many RIAs remain unsure of how to leverage generative AI tools like ChatGPT while staying within prudent and responsible guidelines.
With the “great wealth transfer” in motion and some $80 trillion set to trickle down to younger investors, RIAs need smart, AI-driven strategies to help capture this digital-first audience. Here are five ways RIAs can use generative AI to grow their business — followed by best practices to institute and caveats to heed.
Scenario forecasting
Generative AI tools can quickly analyze historical trends to forecast the potential outcomes of financial decisions.
By monitoring industry news and trends, RIAs can use AI to explore how market indicators have previously impacted securities, and by doing so build their reputation as insightful advisors while helping clients make smarter decisions.
READ MORE: From writing assistance to presentation builders: Top AI tools picked by wealth leaders
Portfolio analysis
RIAs can spot trends and opportunities to expand their business by turning AI tools inward to examine client rosters and portfolios.
Are your client demographics shifting? Are certain age brackets, geographic locations or other lifestyle factors becoming more prominent? AI can help identify trends or gaps in your practice.
Client prospecting
As RIAs move away from referrals and toward digital marketing, AI lead-matching tools can help advisors better understand client needs by filtering and sorting leads to meet target parameters. And AI-enhanced platforms can help source leads by sorting according to factors like net worth, years until retirement and geographic area.
Marketing materials
Generative AI can be helpful for crafting compelling copy for ads, social media, email outreach, blog posts and more.
You can even use AI to analyze the results of historical marketing campaigns in order to identify which copy prompted people to click, read, explore, download and convert most often — and then write optimized copy based on past success.
READ MORE: Using AI models for the greatest advantage to advisors
Faster fraud detection
Everyone has a digital footprint. Generative AI can mine this data to compile an investor profile that helps RIAs conduct faster lead qualification and determine whether the client is a good fit while filtering out scammers.
But while gen AI offers firms transformative opportunities, it’s essential for RIAs to employ best practices and keep the following caveats and best practices in mind.
Overcome data limitations with RAG
AI output is only as good as the input data, so RIAs must be confident in their data sources.
Yet most firms don’t have the massive datasets required to build their own large language model.
An RIA can overcome this data deficiency by implementing retrieval-augmented generation, or RAG. This AI framework combines a firm’s internal knowledge base with external sources to provide broader, more current and contextually appropriate insights.
Assemble a team
Prior to deploying any gen AI solution, assemble a team to craft a strategy and establish parameters. That team should include a technical expert well-versed in AI applications, APIs and implementation; an RIA with deep industry knowledge; and a regulatory and compliance expert.
Build a test environment
Deploy a prototype and provide limited access to a few key users first. Allow them to experiment in a controlled setting and collaborate with them to resolve any flaws or unexpected outcomes before rolling it out firmwide.
Train users in prompt engineering
Crafting generative AI prompts is an art and a science: You must learn to ask effective questions to get the right answers. Train users in prompt engineering, as well as the best use cases and limitations. Be clear that gen AI cannot be used to provide direct, unvetted client advice.
AI is not good at measuring temperament. In an industry where emotions can run high, a chatbot can’t respond with empathy during sensitive conversations.
READ MORE: Will smooth-talking AI avatars replace human advisors?
Eschew FOMO
Finally, don’t rush headlong into generative AI adoption without careful planning and some guardrails. Establishing a responsible policy, smart strategy and realistic expectations can help RIAs succeed in growing their business with AI while avoiding common pitfalls.
