Tech stacks with AI core for growth-minded RIAs

Artificial intelligence in advisor tech is about to get very interesting.

Several years after the AI tech boom, I believe we can lay to rest the fears that these tools will replace human financial advice. However sophisticated the models become, generative AI can’t replicate the work advisors do any more than robo-advisors could in the 2010s. But the scope of what AI tools can do in an effectively integrated advisor tech stack is poised to expand dramatically.

I think it’s fair to say most applications of generative AI currently target a well-defined slice of financial planners’ work. We see a lot of tools that transcribe meetings, suggest insights and next steps or rapidly draft customized client communications or marketing material. These are efficiency plays. It’s valuable to draft an email in 30 seconds instead of five minutes. 

It is never a bad thing to give an advisor more time to spend in front of their clients and prospects. Such advances push a firm toward better outcomes because they create more client-facing time. 

But increased efficiency won’t massively change the way RIAs run their businesses. For many advisory firms, the real value of AI won’t come from better summaries or faster transcripts. It’ll come from tools that pick up where those services leave off. 

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For instance, imagine an advisor meeting with a longtime client who mentions she’s updating her family trust to include her new grandchild. A traditional AI note-taker might transcribe the conversation and ahead of the next meeting insert a prep note saying, “You discussed a trust update on your last touchpoint.” That’s helpful context, but it still relies on the advisor to take the next step.

Now imagine an AI tool that surfaces that same insight, but also recommends the next actions based on the client’s trust update: “Trigger the estate planning workflow, assign a task to follow up with her estate attorney and schedule a check in for 30 days. Ready to begin?” 

The first produces useful insight. The other takes insight and creates action.

Tools talk

Generative AI, by its nature, can pick up on the subtleties and shared connections that rules-based, if/then workflows might completely miss. But to take full advantage of what gen AI has to offer, the problem of tech stack fragmentation must be resolved.

I’ll explain. Currently, most RIA tech stacks have a customer relationship management system serving as the hub of point solutions for financial planning, estate planning, tax tools and everything else the business needs to serve its clients and support its operations. 

Now, these point solutions can and do build their own AI integrations and innovations within their own scope — but only with the data they have on hand. This is what I mean by fragmentation: The pieces of a tech stack get smarter, but only about the data they directly touch. And even though the pieces have gotten much better at “talking to each other” in recent years, none of them can see the full picture of the client relationship.

In order for all the pieces to work together to yield a more complete picture of clients and prospects, AI needs to move into the core of the tech stack. It must become the central capability that understands the firm’s entire book of business. 

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This requires a tech platform that uses client data such as satisfaction, profitability and service adoption to identify which clients deliver the most value to the firm. By understanding what makes these relationships successful, the platform can help uncover and engage similar prospects. The platform should also support internal processes, such as assigning leads to the right advisor, triggering follow-up tasks or coordinating service requests across teams.

From there, generative AI can handle everything from drafting outreach and scheduling appointments to transcribing conversations, summarizing interactions, initiating workflows and sending client follow-ups. 

Such a system will also prompt advisors and client service teams when to reach out to clients and prospects, offering context not only from internal data but also from portfolio changes, areas of interest and major life events gathered directly from a platform that is fully integrated with the firm’s tech stack. 

Investing in AI

Now, building or rebuilding a tech stack that fully integrates AI is no simple matter. It often involves evaluating legacy systems, consolidating data sources, retraining teams and working closely with vendors to ensure integrations actually deliver on their promises. It takes time, budget and buy-in across the firm. 

That said, the payoff is likely to be especially significant for midsize RIAs that have outgrown patchwork systems but aren’t yet large enough to justify heavy internal tech investment. For these firms, a unified, AI-enabled platform can create real lift by turning business data into action, driving consistent client engagement and freeing up advisors to focus on relationships, not administration.

In my view, success depends on full integration. Without it, multiple tech solutions will only offer advisors a disconnected experience that results in inconsistent client outreach. The firms that make this investment are the ones most likely to see generative AI deliver on its promise as not just a time-saver, but a true business enabler. The AI-powered RIA platform of the (near) future will handle the organizing and thinking, freeing up advisors to focus on delivering a standout client experience.