One of the biggest challenges in scaling up an advisory firm beyond the founder is figuring out how to ensure that all the new and future team members of the firm will deliver advice consistent with the founder's approach. Historically, this has meant training advisors largely through osmosis; associate advisors were expected to be part of client meetings alongside the founder, to not just capture notes for CRM, compliance, and follow-up purposes, but to be present and absorb and learn by seeing and hearing (and eventually, supervised doing). Yet with the arrival of AI notetakers, many advisory firms have begun to question whether it's even a good use of time for team members to still be in client meetings when notetaking can occur automatically. While at the same time, the question arises: if team members aren't in client meetings, how else can they possibly learn the founder's approach and planning philosophy? (Unless they go separately to the founder with each and every planning question, which ironically can take even more of the founder's time!)
In this guest post, Jake Northrup, founder of Experience Your Wealth, shares how his 3-person advisory firm built their own custom AI assistant, not as a means to replace team members but a way to teach, train, and support their advisors and ensure advice is delivered more deeply and consistently to clients… while reducing how often the team comes to Jake as the founder for direct input.
Of course, the starting point for any AI-related initiative in an advisory firm – especially when it involves client-specific situations and therefore client data – is how to do so securely. Which Jake ultimately solved for by transitioning to a new CRM system (Slant) that has securely integrated Claude directly into its own client database. Additionally, with support from the firm's outsourced IT and Cybersecurity provider, CyberSecureRIA, Jake was able to set up a secure private cloud environment – dubbed "Rocky" – where the firm's IP can be uploaded and utilized safely (after trying a smaller-scope setup with a contractor on Upwork that failed!).
Once the client and firm data was secured in a safe environment, Jake shares how he utilized Claude to develop a "Standard Operating Procedure" (SOP) document that could be used to teach their AI-assistant Rocky how the firm handles any particular planning situation based on the AI-generated notes and transcripts of various internal firm and client meetings (already held safely in their Slant CRM or secure private server), along with other firm data.
Once trained, Rocky is now able to act like a thinking partner for the firm, allowing them to more consistently create the deep advice that Experience Your Wealth provides to its clients while reducing how often the team needs to come back to Jake for input. With the caveat that Rocky isn't expected to be (and isn't) perfect, and some issues will still need to be escalated for input from the founder. Which means that from the team perspective, the focus can shift from memorizing what the firm's standard approach is for certain client scenarios (since Rocky can quickly make those connections), to exercising judgment about when to trust Rocky's output, when to push back, and when to bring it to the founder for further (albeit still less frequent and time-saving) input.
An interesting side-effect of Jake's efforts is to find that 'just' consolidating the firm's information into their CRM system has been enough to apply Rocky as their own AI assistant "lens" through which client scenarios can be analyzed. In other words, it wasn't necessary for them to go through the complexity of creating their own "data warehouse" as some larger firms have done; instead, Jake's firm achieved their AI unlock by switching to a new CRM system (Slant) that was able to bring together all of their client relationship and meeting data (e.g., AI notes and transcripts) into one central CRM location.
Ultimately, the key point is that building an AI assistant tool, trained on your firm's individual data, is something that can be accomplished even in a solo advisor or small team environment, as long as some outside help is used for the initial technical setup. And doing so is arguably especially helpful for smaller/solo advisors, where training team members – who otherwise crave the founder's input and time – can create growth bottlenecks that an AI trained on the firm's planning approaches can help to solve. Which in the long run doesn't only help the firm to train and develop team faster, but also helps them more quickly go deeper with each client, supporting the firm's ability to continue to grow without needing to hire additional team as rapidly, thanks to the technology support!



