In November 2022, when the release of ChatGPT kicked off the rapid proliferation of AI tools throughout the marketplace, one of the immediate follow-up responses was something like, "OK, this is cool… but what is it really useful for?". Because it's one thing to have a chatbot that can trawl the entire Internet and body of written literature to answer questions like, "What should I have for dinner tonight?", but it's another thing to turn those capabilities into something that will have a real day-to-day impact.
In the advisory space, the first truly useful AI tools were the first wave of AI notetakers like Jump, Zocks, and Finmate AI. With recording and scanning meeting notes, composing summary emails to clients, assigning follow-up tasks, and pulling previous meeting notes to prep for the next meeting taking up (per recent Kitces Research on Advisor Productivity) around one hour of time for every two-hour client meeting, the time savings of a tool that could expedite those tasks down to 15 minutes or so meant that advisors could reinvest that time into more meetings, deeper planning for clients, marketing and business development to bring in more clients, or simply feeling less harried from the onslaught of administrative tasks between each meeting. Advisors rapidly adopted meeting note tools, such that by 2025 our Kitces Research on Advisor Technology showed that around 30% of advisors used some kind of client meeting note tool – an impressive growth rate for technology that had barely existed two years prior, and a number that has surely increased further in the year-plus since that report was released.
But while AI meeting notetakers clicked with advisors almost immediately, other use cases for AI have been slower to catch on. Despite the addition of many new AI prospecting tools to the Kitces AdvisorTech Map, including FINNY, Wealthfeed, Wealthreach, and Aidentified, advisors haven't been as quick to adopt them (since few advisors actually engage in cold prospecting for business growth in the first place, and those who don't aren't likely to be convinced by technology to start doing so). The Investment Data/Analytics category of the Kitces AdvisorTech Map has similarly been flooded with new providers that use AI for everything from scanning for market signals to flagging and summarizing changes to SEC filings, but in reality most independent, retail-serving financial advisors don't engage in the kind of single-stock analysis that makes these tools useful. And while many providers are seeking to be the agentic AI "operating system" that connects the advisor's tech stack together and employs a swarm of AI agents to automate most daily workflows, it's been harder for those providers to articulate what makes them actually useful in an advisory firm context, where productivity tends to be impacted more by bringing in new clients and serving existing clients better than becoming more efficiently run on the back end.
In that vein, compliance has similarly been an area where advisors have been relatively slow to adopt a new generation of AI-driven tools. Which is curious because compliance would seem to be an area where Large Language Model (LLM) AI tools would be particularly useful: Rather than relying on the 'old' system of pulling random samples of client communications or trade records to look for suspicious activity, or even the relatively 'new' method of searching for specific keywords or text strings that could indicate malfeasance, LLM tools have the capability to sift through virtually all of a firm's data and analyze it in context, resulting in a much bigger likelihood of catching actual instances of bad behavior (and requiring much less sorting through false positives to get to the cases that really need attention).
But in contrast to AI notetakers, which had an immediate payoff for advisors in the time savings they allowed (that could then be reinvested into more productive activities), the benefits of better compliance technology are less tangible for advisors: It isn't likely to cause them to spend much less time on compliance, it just allows them to do compliance better. Which in the best case means that there's only marginal time savings to be achieved (which is what mainly matters in a world where most advisors view compliance as a "check-the-box" requirement instead of a productive, revenue-generating activity) – and at worst could actively dissuade some advisors from adopting it, since a more comprehensive scan of their firm's trades and communications might result in digging up issues that it will then become the firm's problem to deal with!
In that context, it's notable that the AI-powered compliance technology provider Hadrius announced this month a $22 million Series A funding round, shortly after its competitor Greenboard announced its own $15.5 million Series A round in May 2026 – suggesting that despite the relative slowness of advisors to take to AI compliance, there are signs that it could be one of the next categories of advisor AI technology to start gaining traction and adoption.
As Hadrius notes in its announcement of the funding round, the case for involving AI in compliance has grown as the volume of communication between advisors and their clients or the public has exploded. In the days when most communication was done via physical mail or faxes, it was relatively easy to perform a human review of what the advisor was saying to clients. As email and social media started to take hold, the amount of communications increased exponentially, yet it was still possible to review a representative sample of an advisor's output to infer that what they were saying was legitimate on the whole. But as we've entered an age of AI communication, where words, images, and even video can be generated cheaply at scale, the amount of potential output is virtually limitless – and given the wildly varying reliability of different AI tools to generate accurate (to say nothing of compliant) text, there's a strong case for a newer generation of more powerful tools to capture it all – or in other words, as Hadrius put it, "in a world of AI slop, everything is compliance".
But the question going forward is whether the prospect of doing 'better' compliance will move the needle with enough advisory firms to drive significant adoption beyond the relative handful of larger RIAs for whom compliance is enough of a cost center and liability risk that it's worth investing in tools to do it thoroughly and efficiently. The answer will probably lie in whether there end up being bigger consequences for firms that don't adopt AI for compliance. After all, since the tools for scanning advisory firm communications and flagging issues already exist at the B2B software level, it's almost certain that they're available for regulators doing the examinations as well. As an advisory firm owner, it's logical that you would want tools that are at least as powerful at flagging compliance issues as the ones used by the regulators, otherwise, it's virtually guaranteed that you'll end up losing time and resources addressing deficiencies flagged by the examiner's more powerful tools. So while firms may have been slow to adopt AI compliance tools because they don't feel like it serves an immediate need for them (or at least as immediate as expediting meeting notes and follow-up), they may nevertheless be driven to adopt them by the increasing risk that they won't be able to keep up with regulators using the same types of tools for enforcement.
Which ultimately goes to show how there are multiple avenues for gaining adoption as an AdvisorTech provider. You can provide an easy solution to a common problem, such that many advisors will be willing to pay $80-$100 per month for software to do it (although as has been the case in the AI notetaker space, that can quickly lead to an overcrowded category and leave the startup standalone providers vulnerable to being undercut by incumbents who add meeting notetakers to their existing tools). Or else you can provide something that will eventually be a virtual requirement for advisory firms, with the risk hanging over their heads of financial or reputational liability if they don't stay up to speed. Although the former might create more opportunities for rapid adoption, the latter also seems likely to pay off in the end – once advisors realize what's needed to keep up with their regulators.
This article first appeared on the Nerd’s Eye View at Kitces.com at https://kitc.es/advisortech-august2026, and has been reprinted here with permission.
Ben Henry-Moreland
Ben Henry-Moreland is a Senior Financial Planning Nerd at Kitces.com, where he specializes in writing and speaking on financial planning topics including tax, practice management, and technology. He also co-authors the monthly Kitces #AdvisorTech column. Drawing from his experience as a financial planner and a solo advisory firm owner, Ben is passionate about fulfilling the site’s mission of making financial advicers better and more successful.
Michael Kitces
Michael Kitces is Head of Planning Strategy at Focus Partners Wealth, which provides an evidence-based approach to private wealth management for near- and current retirees, and Focus Partners Advisor Solutions, a turnkey wealth management services provider supporting thousands of independent financial advisors through the scaling phase of growth.
In addition, he is a co-founder of the XY Planning Network, AdvicePay, fpPathfinder, and New Planner Recruiting, the former Practitioner Editor of the Journal of Financial Planning, the host of the Financial Advisor Success podcast, and the publisher of the popular financial planning industry blog Nerd’s Eye View through his website Kitces.com, dedicated to advancing knowledge in financial planning. In 2010, Michael was recognized with one of the FPA’s “Heart of Financial Planning” awards for his dedication and work in advancing the profession.
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