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Written by: Adrian Johnstone | Practifi
It’s hard for advisors to avoid feeling like their technology takes more than it gives.
Advisors know, objectively, that the tools at their disposal are indispensable for managing workload and maintaining client relationships. But in day-to-day practice, those tools sometimes feel like glorified data entry.
Advisors create piles of data from client touchpoints that are fed into their systems to generate insights for operations teams, compliance functions, or leadership. These are important outcomes, but they are not benefits an advisor tends to feel directly in the moment-to-moment work.
This dynamic changed overnight with the arrival of generative AI.
For the first time, advisors can ask a question and get an answer without hassle. No more navigating across five different systems with varying degrees of connectivity. You get an answer immediately, and that feels like progress! But what works for the advisor in the moment does not necessarily work for the firm over time.
If the value created in that interaction stays inside the AI tool and never makes its way back into the system of record, the firm begins to lose visibility into its own data and processes.
Many advisors are now adopting AI tools that sit in a layer on top of their existing technology stack. These tools are conversational interfaces that pull from multiple systems and return answers in a clean, simple format. From the advisor’s perspective, they are a clear improvement because they reduce the friction between you and the information you need.
The issue emerges when that layer of AI interpretation becomes the advisor’s primary interface with the business. Advisors increasingly work through conversational AI tools instead of directly within core systems like CRMs, causing information to spread across planning software, email and AI interfaces. The result is a growing disconnect between how advisors work and how operations and compliance teams maintain oversight, consistency and accountability.
Many first-generation AI point solutions are designed around the individual advisor first, not the firm’s long-term operating model. The result is a system that optimizes individual interactions while weakening the centralized client record that operations, compliance and long-term relationship management depend on.
In other words, your meetings are not your client relationship. Your clients do not pay advisors to have meetings. They pay for your judgment and the continuity of a relationship with someone who understands them and what they want to accomplish.
Many AI point solutions are centered primarily on capturing and summarizing individual pieces of the relationship, like client calls.
(As an aside, I think we should acknowledge how far the industry has come, when we describe an AI notetaker as “only” collecting a near-instantaneous transcript of every client call.)
Over-reliance on AI point solutions will pull a firm away from a model anchored in a durable client record and toward one centered on a series of disconnected interactions. The industry risks solving one problem while quietly creating another.
The answer is to be deliberate about where AI lives inside the advisor’s toolkit. Adding another layer on top of an already complex technology stack is unlikely to produce the outcome that firms expect. Most firms have spent the last decade trying to simplify their technology environment, not add new layers of intermediation.
The real opportunity is to embed AI into the systems that already anchor the business, so that it can deliver value to the advisor without disrupting the structures that support operations and long-term accountability. That path is more difficult, and it is less visible in the market today. But it is the one that preserves alignment across the firm.
Advisors are finally getting tools they like. The question now is whether firms are prepared for what happens if those tools begin to pull them away from the systems they rely on.