Executive Summary
With each passing decade, not only does technology evolve at an ever more dramatic pace, but each new wave comes faster than the last. From the advent of the computer chip in the 1950s to the rise of the personal computer nearly 25 years later in the early 1980s, to the emergence of the internet just 15 years thereafter in the late 1990s, to mobile smartphones only 10 years after that in the late 2000s, to 'robos' less than a decade later in the 2010s, and most recently to AI, which 'suddenly' went mainstream in late 2022 when ChatGPT burst onto the scene – the pace of technological change seems to be accelerating inexorably. And with the advent of AI in particular, questions have emerged about whether technology will replace many human jobs, including financial advisors.
Yet now, two years later, AI has not driven a mass wave of unemployment. Instead, it's being allocated to far more specific – but still very relevant and helpful – use cases that don't replace professional service providers and instead simply leverage their time to be even more efficient. In the case of financial advisors in particular, this has included everything from using ChatGPT as a brainstorming buddy for developing an advisor marketing plan, to generating a first draft of a client newsletter (as it's far easier to edit something already there than to write on a blank slate), to adopting what has quickly become the hottest AI-driven solution in advisor technology: AI Notetakers to support the client meeting.
In practice, rapid adoption of AI Notetakers has been expedited both by the media's fixation on Artificial Intelligence (which has highlighted a wide range of AI solutions like Fathom, Fireflies, and Otter) and by the rollout of AI Notetakers within existing platforms (from Microsoft's CoPilot to Zoom's AI Companion). But when it comes to financial advisors, our own Kitces Research on Advisor Productivity shows that while some of the "generic" solutions have gained market share the fastest, it turns out that the industry-specific solutions like Jump and Zocks lead in advisor satisfaction (while ironically, #1-adopted Zoom AI Companion actually ranks the lowest!). This is largely because, for financial advisors, it's not 'just' about capturing notes from the client meeting itself, but also about managing everything that follows: recording meeting notes in the CRM for compliance purposes, assigning post-meeting tasks to the team, and sending the client a post-meeting recap email. For which industry-specific providers are building the entire advisor-CRM-integrated workflow.
Yet the irony is that for many advisors, saving time on client meeting notetaking is difficult when those tasks have already been delegated – to the team's Associate Advisor. In fact, as our Kitces Research data shows, adoption of AI Meeting Notes tools has been most common amongst "pure solo" advisors, who have no one to delegate to (and instead find great leverage in delegating to an AI Notetaker). Nonetheless, AI Notetakers are not just for solo advisors; instead, they're also increasingly popular amongst larger (e.g., four to five person) teams, where it's easier to share out the AI's post-meeting notes to get everyone on the team (who may not have been in the meeting) up to speed. In addition, AI Notetakers are increasingly popular as advisors' financial plans get increasingly comprehensive; not surprisingly, the more detailed financial planning conversations happen in client meetings, the more there is to capture and share out.
At the same time, AI Meeting Notes tools themselves continue to evolve rapidly. What wasn't even a category of software just two years ago has now raised tens of millions of dollars in just the AdvisorTech domain alone, for what is not only nominally "notetaking" software, but increasingly covering the entire client meeting lifecycle (meeting notes → record notes in CRM → queue up post-meeting tasks → draft post-meeting recap email →→→ pre-meeting agenda for the next client meeting), and then leveraging the cumulative data to provide even more recall details for advisors about what happened in prior meetings.
In the long run, it seems clear that AI Meeting Notes tools are here to stay. In fact, with their increasingly comprehensive coverage of the entire client relationship, perhaps the biggest question is simply whether they'll remain standalone tools or, instead, if CRM systems for financial advisors will eventually offer their own built-in versions (since that's where the rest of the data about client relationships already resides!?).
Either way, the landscape of AI in advisor technology continues to evolve fast. And we're committed to keeping track of it with our Kitces Research. Which is why we're also launching our latest Kitces AdvisorTech survey, to collect data on the latest in how advisors are actually using technology. So if you have a few minutes, please take our AdvisorTech survey linked at the end of this article!
It was just over two years ago that AI erupted onto the scene, as OpenAI released ChatGPT in November of 2022 and, within three months, it had become a viral sensation. As more and more people tried it out, and realized how 'intelligent' it seemed to be as it answered the questions it was prompted, the predictions came fast and furious: If this is how good AI is already, it's only a matter of time before ongoing iterations of their Large Language Models (LLMs) make the tools capable of doing 'everything' that humans do now. Which led to predictions that AI would soon spur a potential wave of mass unemployment across multiple industries… and a veritable explosion of massive investments into the future of AI, as Microsoft made a huge investment into OpenAI, Google unveiled its own AI tool Bard and followed with its new AI capabilities in its search tools, Amazon invested into Anthropic's Claude competitor, Nvidia catapulted to a $1T+ market capitalization on the basis of how many high-end computer chips would be needed to fuel all the AI data centers, and tens of billions in venture capital and private equity poured into AI platforms.
As we now fast forward two years later, it turns out the mass wave of unemployment has not come. It turns out that AI is 'pretty good' at a lot of things, but not necessarily good enough to replace humans in most cases. Which isn't entirely surprising – while an AI tool's LLM is remarkably good at 'having conversations' and interacting with human language because they can organize information well, it literally isn't 'intelligent' in a logic-and-reasoning manner the way actual humans are; thus, for instance, why ChatGPT-4 was able to achieve a nearly-top-decile score on a question-and-answer exercise like the LSATs (the qualifying exam for prospective law school students), yet infamously couldn't figure out how many times the letter "r" appears in the word "strawberry".
Nonetheless, while the reality is that AI doesn't appear to be replacing financial advisors anytime soon, the truth is that AI is good at certain more focused functions that are relevant for financial advisors. The tools can be very effective as a brainstorming partner, whether to come up with prospective titles for a blog post or to talk through what an optimal marketing plan would be to reach your ideal client persona. ChatGPT and its brethren are also very good at solving the 'blank slate' problem, where it's easy to get writer's block – for instance, while writing a newsletter for clients or even an email to a particular client to talk them off the ledge – but no one has 'editor's block' (as it's much easier to edit the initial output from an AI tool to customize for the client, than to write from scratch).
And most notably – in terms of actual adoption of AI in the advisor marketplace – it turns out that AI tools are especially good at summarizing large chunks of information, such as the transcript of a client meeting in order to document meeting notes.
The Rise Of (Generic And Advisor-Specific) AI Meeting Notes Tools
As the capabilities of AI to summarize information became clear, a number of AI-driven 'Meeting Notes' tools began to emerge for consumers to try out, including Fathom, Fireflies, and Otter. The core functionality of each was substantively similar: The tool could be invited as a 'meeting participant' to popular online meeting platforms like Zoom or Teams. Upon arrival, the tool would record the meeting, create a transcript of the meeting, and, at the end of the meeting, generate a summary of the key points and highlights of what was discussed at the meeting.
The caveat in the case of financial advisors, though, is that we don't 'just' need to summarize a client meeting. A record of what was covered needs to be captured for compliance purposes, typically as a note in the advisor's CRM system. It's a best practice to send a follow-up email to the client after the meeting, recapping what was said and decided as well. And if action items came from the meeting, those tasks need to be created and workflows need to be assigned out to the team to ensure nothing falls through the cracks.
As a result, a number of advisor-specific 'AI Meeting Notes' tools have emerged over the past two years, promising not only to record the essence of what was said in the client meeting (ideally, with a tool that is trained to capture the most salient points an advisor would want to know about a client meeting), but also to help fulfill the post-meeting obligations that follow. These include CRM capture of the notes, creation of tasks to be assigned to the team, and preparation of a post-meeting recap email to the client (which aligns with one of the other key functions that ChatGPT and other LLMs do so well: generating starting text to fill a blank page that the advisor can edit to their needs and satisfaction).
Kitces Research Scoring Of Emerging AI Meeting Notes Tools For Financial Advisors
In order to better understand the emerging technology, the Kitces Research team added a number of questions to its bi-annual Advisor Productivity Research study in the fall of 2024 to learn more about the adoption of the various AI Meeting Notes tools tracked in the "Client Meeting Support" category of the AdvisorTech Map. We included both the "generic" participants in the category – like Fathom, Fireflies, and Otter, along with the then-recently-launched AI Companion functionality built into Zoom – along with a plethora of industry-specific participants, including Jump, Zocks, Zeplyn, Finmate, Vega, Pulse360, and more.
As the results reveal, financial advisors have initially skewed toward utilizing the 'generic' solution providers, particularly Zoom's AI Companion, which is built right into the meeting software that they are already using. This isn't surprising, given both the sheer convenience – Zoom's AI Companion requires little more than a toggle switch to default it to participate in meetings, and at no additional cost beyond already having a paid Zoom account. Notably, Microsoft's CoPilot adoption is much lower, owing likely to the combination of its additional cost as an add-on to an Office 365 license and, more substantively, the fact that relatively few advisory firms use Microsoft Teams for client meetings in the first place.
In turn, to the extent that advisors went beyond in search of an alternative solution (or, in practice, adopted before Zoom's AI Companion even rolled out), 'generic' providers such as Fathom and Fireflies also gained traction. These tools hit the marketplace with heavy marketing in 2023 and 2024, and are offered at a relatively low cost.
On the other hand, while 'generic' solutions have gained the highest adoption thus far, a different picture emerges when evaluating advisor satisfaction with the solutions. As with our Advisor Productivity research, we not only asked which AI Meeting Notes tools advisors were using, but we also asked whether they liked the tools! And from the perspective of "which tools are doing the best job in supporting client meetings" (and, ostensibly, in the subsequent post-meeting tasks), it turns out that the industry-specific providers have a much stronger showing… and Zoom's AI Companion, with its #1 adoption, actually ranked last in advisor satisfaction!
And with literally tens of millions of venture funding into advisor-specific solutions, many more tools have emerged that were even too new (with too limited adoption) for us to collect data on last fall! Which is why, as we field our upcoming 2025 AdvisorTech Survey, we'll be looking to collect even more data on advisor adoption and satisfaction ratings across the ever-widening range of tools!
Delegating Client Meeting Notes: AI Meeting Notes Tools Or Associate Advisors?
As our prior Kitces Research on Advisor Productivity has shown, the average financial advisor spends more than one hour in meeting preparation and follow-up client-servicing tasks for every hour they spend in client meetings. Which both means that advisors spend a lot of time in the aggregate on meeting prep and follow-up… and that the prep/follow-up obligations of client meetings can themselves become a significant constraint on a financial advisor's overall client capacity.
In other words, for financial advisors approaching capacity, the biggest reason they can't take on more clients isn't that there are 'too many meetings', but that they can't even fit in any more meetings around the prep and follow-up work that has to be done for their other clients' meetings!
Historically, most advisory firms have solved this by simply expanding the service team with the hire of an Associate Advisor who can sit as the 'second-chair' in client meetings. This role is responsible for taking notes, recording those notes in the CRM, assigning out servicing tasks for the team to implement, drafting the post-meeting follow-up email (either to send directly or at least to prepare for the lead advisor to review and send themselves), and doing the meeting prep for the subsequent/next meeting with that same client (based on all the information they previously collected). Thus why our Productivity research has long shown that financial advisors with any kind of team structure – whether as multi-advisor ensemble teams or 'just' solos with a support team around them – substantively outperform 'pure solo' advisors who have no Associate Advisor at all.
Which raises an interesting question as it pertains to the emerging use of AI Meeting Notes solutions: Do financial advisors even need AI software to capture client meeting notes if they already have an Associate Advisor to delegate to instead?
Advisor Use Of AI Meeting Notes Tools In Teams Vs Solos
When it comes to the use of AI Meeting Notes software, our Kitces Research data reveals there is a strong tendency for financial advisors who already have an Associate Advisor to forgo the use of software and simply rely on the Associate they've delegated to, as the adoption rate of such tools is about 1/3 lower amongst 2- or 3-person advisor service teams than it is amongst 'pure' solo advisors.
Notably, though, the data also reveals that AI Meeting Notes tools are becoming more popular amongst larger teams as well – while usage drops precipitously as the advisor goes from being a solo to having a 1–2-person support team (a total team size of 2–3), AI Notetakers are just as common amongst 5-person teams as they are amongst solos! In such cases, though, the use case appears to be somewhat different: The goal is not to alleviate the lead advisor of the need to capture meeting notes for compliance purposes and a post-meeting recap; instead, it's to help a larger team stay aligned on everything happening with the client when not everyone on the team will be in the meeting in the first place.
In turn, our results also reveal that the deeper the financial planning process with clients – and the more there is to record and not lose track of (and subsequently communicate to a larger team) – the more likely it is that AI Meeting Notes are being used as a part of the process (regardless of team size and structure). Such that advisors who create the Most Extensive comprehensive financial plans use AI Meeting Notes tools at nearly 4X the rate of those who create the narrowest and most Targeted financial plans.
Which further reinforces that, in practice, advisor adoption of AI Meeting Notes tools is less about 'just' whether the advisor has an Associate Advisor to delegate notetaking to or needs to do it themselves (and wants to delegate it to software instead), and more about the breadth of the advisor's financial planning process and the number of team members that must be coordinated in the subsequent servicing of the client (and, for team members, this can mean saving time by not needing to be in the meeting and being able to see an internal post-meeting recap from the AI Notetaker instead!?).
Yet at the same time, there comes a point where the needs of an advisor's clientele become so in-depth and complex – such as with ultra-high-net-worth clientele – that the advisor has relatively few clients whom they serve more deeply… and at that point, it turns out that AI Notetakers are once again less popular. Which means, in practice, advisory firms seem to have substantively different use cases for AI Meeting Notes software depending on the revenue they're generating per client, the number of clients they must serve, and the team it takes to service them.
Such that advisors working with a large number of small clients (where it's not cost-effective to even have an Associate Advisor in the room) rely most heavily on AI Meeting Notes tools, while those focused in the Mass Affluent segment (where it is affordable to hire and bring an Associate Advisor into the meeting) more often rely on the Associate for notes. Yet those working with millionaire clients – where financial planning tends to be more in-depth, requires larger service teams, and involves more team coordination around an expanded breadth of planning information – once again utilize AI Notetakers more.
Once clients reach an ultra-HNW stage – where the revenue per client is high enough that the advisor has far fewer clients (and thus can focus more on, and remember the details of, each individual client), and it becomes cost-effective to have more team members in the meeting (such that they don't need a post-meeting recap) – there is a precipitous drop-off in the usage of AI Meeting Notes tools amongst this segment of clientele.
(The Lack Of) Best Practices When Using AI Notetakers In Advisor Teams
As our Kitces Research on Advisor Productivity data reveals, there clearly is a use case for AI Meeting Notes tools to help pure solo financial advisors capture meeting notes and facilitate the post-meeting wrap-up process (record notes in CRM for compliance, kick off post-meeting tasks, send post-meeting recap email to client). As a result, advisors without any support team have the highest adoption rate of these tools (especially amongst those who serve a high volume of smaller-dollar clients, where it's not cost-effective to bring a second person into the client meeting in the first place).
However, the reality is that AI Meeting Notes tools are being used amongst larger teams as well – and the larger the team, and the more the firm delivers the most comprehensive financial plans to millionaire and multi-millionaire clients, the higher the adoption rate. Yet, in such scenarios, the implementation of AI Meeting Notes is substantively different – less about 'just' capturing compliance notes and preparing a post-meeting recap, and more about keeping track of the sheer depth and breadth of financial planning (and other information), while sharing and coordinating that information amongst more and more team members who all need to be up to speed on the client's situation. (That is, until the firm serves clients who are so affluent that multiple team members can sit in on the meeting directly with those ultra-HNW clientele.)
Still, at least thus far, there does not appear to be any standard 'best practices' about how such tools are used when there is an Associate Advisor (or more members) on the team. For instance, a recent informal social survey poll of 350+ advisors found that amongst service teams with an Associate Advisor that are also using AI Notetakers, there is a remarkably even split between whether the Associate is replaced by the notetaker, sits in the meeting alongside the notetaker, or is the one using the notetaker themselves.
Arguably, to the extent that it is the Associate Advisor in an advisory service team who has the accountability to ensure that good meeting notes are captured (by whatever means), it would make sense that the answer here with the slight plurality lead becomes the best practice in the long run: that it's the Associate who uses the AI Notetaker themselves.
The Associate Advisor is the team member accountable to ensure good meeting notes are captured, so it seems most likely that AI Notetakers will become a tool for Associate Advisors themselves in the long run!
Which helps to address the concern that Associate Advisors 'need to' be in client meetings and capture meeting notes in order to learn the fundamentals of advice delivery in the first place. Just as Associates no longer have to manually calculate financial planning projections with a calculator – relying instead on financial planning software – while still being required to ensure that 'the plan' is crafted appropriately, AI Notetakers may similarly become the calculator-style tool to facilitate client meeting notes, replacing manual notetaking on a notepad. However, the Associate Advisor remains accountable for ensuring meeting notes are accurately captured and post-meeting follow-up occurs, which means being in the meeting to be present for what is said (and editing the meeting notes summary for accuracy and detail thereafter). And for a subset of advisors who find it difficult to manually capture the breadth and depth of notes required in an in-depth client meeting, perhaps the use of AI Notetakers by Associate Advisors will even free up more mental bandwidth – allowing them to remain more fully present and practice their active listening skills in the meeting itself?
Ongoing Evolution And Use Of AI Meeting Notes Tools For Advisors
With tens of millions of angel and venture capital raised to support the launch of more than a dozen different advisor-specific AI Notetaker tools in under two years, the reality is that the world of software to support client meetings is evolving very rapidly. While ultimately there will only be a handful of tools that succeed – as our Kitces Research on Advisor Technology shows, it's extremely rare for any category of advisor technology to have more than three providers with significant market share in the long run – the capabilities of the providers will inevitably continue to expand from 'just' creating a summary of the meeting itself, to more and more beyond.
In fact, most of the leading AI Notetakers have already gone far beyond simply summarizing client meetings and are now expanding into the entire client meeting life cycle. Which may start with summary notes of the client meeting itself, but then proceeds to recording the notes directly in the client's CRM record, queuing up post-meeting tasks to be assigned to the team, and preparing the post-meeting recap email. And once the software captures all that information from each client meeting, it can be used to prepare the agenda for the next client meeting… and then when the next client meeting comes, the process repeats again.
And as AI Notetakers collect more and more data from an ever-growing volume of client meetings – and integrate themselves more deeply into CRM systems where that data (and the subsequent workflows) are commonly interfaced – it seems only a matter of time before the data can be leveraged in other ways to support advisor service teams as well.
For instance, Zocks is building Client Profiles that coalesce all of the data from various client meetings into one centralized place. Jump has been implementing an "Ask Anything" feature that allows advisors to query against their prior meetings with a particular client to recall specific information that might have been mentioned months or years ago (e.g., "Did we discuss college funds in this meeting?" or "What did we commit to do re: QSBS?"). Filenote turns the growing volume of client meeting information into a Mind Map visual for the advisor and client to reference. Thyme is looking to collect documents from new clients and extract data from them to enrich the data gathering process for Client Discovery meetings. And Warmer is positioning itself not as an 'AI Notetaking' tool, but as a "Client Relationship Intelligence" solution (which happens to also handle all the advisor's client meeting notes needs along the way).
Are AI Meeting Notes Tools On A Collision Course With Advisor CRM?
Perhaps the biggest question when it comes to AI Meeting Notes tools in the long run is not whether they're going to survive (it seems clear they will), who's going to use them (solo advisors for themselves, Associate Advisors on behalf of their teams?), or what they're going to evolve into (an increasingly holistic tool that spans all client meetings and incorporates other client data to help advisors go deeper?)… it's whether all those capabilities will remain the role of a standalone 'AI Notetaker' tool, or if advisor CRM systems will eventually roll out their own versions of the software instead.
As the fact that advisors use AI Notetakers not 'just' to capture what happened in the meeting itself – but also to queue up post-meeting client notes, meeting recaps, and subsequent pre-meeting agendas – suggests, 'generic' AI Notetakers or those attached to meeting platforms are probably not the best fit in the long run. Already, our Kitces Research on Advisor Productivity finds that the tools directly attached to meeting software (e.g., Zoom's AI Companion) are the lowest rated of the solutions, because they don't do the rest of what needs to occur beyond the meeting itself. Meanwhile, all of the industry-leading AI Meeting Notes tools have integrated with the leading advisor CRM systems (Wealthbox, Redtail, Salesforce, etc.) to fulfill those post-meeting actions.
Which again raises the question: If the primary function of standalone AI Meeting Notes tools is to extract the recording or transcript of a client meeting and transform the data into something that appears in the advisor's CRM (in the client record, in post-meeting tasks, etc.), will CRM systems eventually just do it themselves? Especially recognizing that many of the industry-specific AI Notetakers are charging $60–$80/month or more 'just' to put client meeting information into CRM systems that themselves often cost about the same for the entire CRM. And as has already occurred in the category of Specialized Financial Planning software, it's not uncommon for a tool that initially launches as a standalone solution – designed to go beyond 'traditional software' – to eventually get adopted by the incumbents and simply become a feature of the traditional platform (e.g., what Financial Planning software did to standalone Social Security planning and Retirement Income Planning tools over the past several years).
The one thing that seems certain, though, is that the implementation of AI within advisor technology is moving fast – as while it is not a 'disruptor' (at least to the extent of displacing financial advisors), there is an immense amount of focus, capital, and developer time now going into how AI solutions can be leveraged to make financial advisors more efficient.
And to that end, we're excited this week to kick off the data-gathering phase of the latest Kitces AdvisorTech Research survey, so that we can understand firsthand how the landscape of AI in advisor technology continues to evolve, with respect to AI Meeting Notes tools (where our 'latest' data from last fall already seems remarkably dated in this fast-moving space). And we'll report back the results to all of you, the advicer community, as we always do at the end of each Kitces Research study!
So if you have a few minutes, please participate in our AdvisorTech Research survey, and stay tuned for the results in a few months!
