When an advisory firm needs a piece of technology for a certain function, the most common path is to buy a piece of software "off the shelf" from an outside software provider and plug it into the firm's existing tech stack. This usually makes sense because RIAs aren't software developers, and don't have the expertise or resources in-house to create their own bespoke technology, and off-the-shelf solutions are good enough to meet most (if not quite 100%) of most advisory firms' needs. Which makes it a better idea most of the time to license the software from a third party than investing in building it internally, since the incremental gains from building wouldn't be enough to justify the massive extra cost of doing so.
When a firm reaches a certain level of size and scale, though, it sometimes does start to make sense to build technology internally. Even if off-the-shelf software does 95% of what the advisory firm needs it to do, that extra 5% – multiplied by hundreds or thousands of employees across the firm – can start to add up to significant dollars and flip the cost-benefit comparison in favor of building. Thus why historically, the largest advisor enterprises – e.g., major wirehouses with 10,000+ advisors each – were often the builders of the best (proprietary) technology.
But that doesn't mean that just because an advisory firm has the resources to build in-house that it necessarily should do so: it's really about whether or not the in-house product would drive meaningfully better margins to justify the cost of building it, compared to going with the off-the-shelf solution that does "almost" everything for a fraction of the cost to build. Especially in a world where now, thanks to the rise of the internet and APIs, independent software platforms often have tens or even hundreds of thousands of advisor users, which means the technology firms often have more resources (and users to amortize their costs across) to build specialized solutions than even the largest advisory firms have resources to build for themselves.
But business owners – advisory firm owners included – can sometimes be a little dazzled by the possibilities for efficiency gains and cost savings that new technology brings, which can make it hard to see the economics clearly for what they are. One example is Carson Group's rollout last year of its AI assistant "Steve", which it claimed would save its employees 5 minutes per search or a cumulative 5,000 hours per year across its network. But with 287 investment adviser representatives per Carson's most recent ADV filing, those 5,000 hours equate to around 20 minutes per week per advisor, or about 0.8% of their working time (or alternatively, about 2.5 team members assuming 2,000 working hours per year). It isn't clear how much "Steve" cost to build, but it's fair to wonder if Carson could have achieved the same less-than-1% productivity gains that allows it to replace 2.5 team members with a third-party tool… that didn't require the more-than-2.5 staffers (between product and development) just to build an in-house solution from scratch in the first place?
Or more recently, there's Savant Wealth Management's announced plans to spend $15–20 million per year ($50M in total over the next 3 years) to build an AI operating infrastructure in order to replace a chunk of its human knowledge workers with "bionic agents" that it hopes will help it scale faster as it grows, while claiming that doing so could help Savant quadruple its revenue while "only" doubling its staff headcount. In other words, Savant expects its new AI agents to double each of its employees' productivity, even though there's no evidence so far of AI generating anywhere near that kind of a productivity boost. Even the recent McKinsey report highlighting a 100,000 advisor shortage noted that the industry has a talent shortage in part because of the limits in how much productivity can realistically be generated from AI, with their estimate that even in 10 years gen-AI-enabled tools will only deliver time savings of 6% to 12%. (Although Savant CEO Brent Brodeski's remarks that Savant's agents "don't take vacation" and "never speak back unless you ask them to" suggest that there are other motives behind the investment in AI agents beyond just process automation, perhaps to the chagrin of its existing human employees.)
The decision to invest so heavily into internal AI tools seems even stranger when comparing those investments to the cost of an off-the-shelf solution. Advisors can license AI tools like Vega Minds, CogniCor, or Zeplyn for somewhere between $500-$1200 per seat per year. Compare that to Savant's plans of spending $50 million, which with a reported 727 employees equates to $68,775 per employee – and doesn't include the very real costs the firm will face to maintain and keep iterating on the software after the initial build. Will the in-house version really be so much better that it's worth spending around 60 times the annual cost of the equivalent off-the-shelf product to build it themselves (plus more to keep it maintained and updated every year in a rapidly evolving AI environment)?
Or viewed another way, are even "mega-RIAs" like Savant still too small with too few advisors or team members to fully justify the cost of self-building their own technology (as compared to a wirehouse with 10,000+ advisors to amortize those costs across)? After all, even Commonwealth with its 2,000 advisors decided in 2019 to spin off Advisor360 because it found the ongoing costs to maintain and iterate on their own proprietary CRM and portfolio management system were just too high without having more advisors (as an independent software company) to spread the development costs across.
It's worth noting that there's also a third option for investing in technology besides buying an off-the-shelf solution or building an in-house version, which is to buy software from third party providers – but then also invest into the technology providers themselves (most of whom are startups still in active fundraising mode). This happened recently when RFG Advisory made a strategic investment into Zocks as part of Zocks' recent Series B fundraising round earlier this year. A strategic investment can serve as a sort of middle path between licensing off-the-shelf software and building the technology internally: It provides more visibility and perhaps input on the product strategy and roadmap (and sometimes even a board seat) to give more assurance that the technology company is building their product in the direction that the advisory firm wants it to, while at the same time requiring far fewer internal resources for planning and building the software than an internal build. And then if the software provider does well and grows in value, the advisory firm gets to participate in that upside, offsetting or even eliminating the cost of the investment to achieve the tech they wanted to see built in the first place.
Ultimately there can be good reasons to buy, invest in, or even build software internally. But the greater the investment, the more the advisory firm would need to realize in return – in terms of higher margins driven by efficiency or providing higher value services, or literally realizing a return on investing into a technology provider itself – in order to justify the cost compared to an admittedly-not-perfect but also far-less-expensive off-the-shelf option. In an age of so much talk about the future possibilities of AI, there's always a strong temptation for business leaders to be seen as being ahead of the curve – but it's hard to see where the math adds up for embarking on a massive internal AI build when the true long-term gains that proponents have been claiming to be just around the corner for several years now are still very much a question mark.
This article first appeared on the Nerd’s Eye View at Kitces.com at https://kitc.es/advisortech-may2026, and has been reprinted here with permission.
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 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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