AI is an almost insignificant portion of wealth management firms’ tech budgets these days. But wait until next year.
That was among the findings in Financial Planning’s inaugural “Cost of AI” report, which found that while most firms are spending less than 10% of their tech budgets on AI, around 76% plan to up that outlay next year. Conducted from January to March this year, 239 of the study’s 694 respondents were in the wealth management industry. Of those 239, these figures were compiled from 89 of wealth management respondents who are aware of their organization’s AI technology budget.
That finding was supported by an October 2024 study by technology services and consulting company Wipro Limited, which surveyed 100 U.S. wealth management executives and found that IT budget allocations for AI expected to more than double — from 16% to 37% — within the next three to five years.
READ MORE: Firms increasing their tech spending, especially on AI
For example, while Bruce Lee, founder and CEO of Keebeck Wealth Management in Chicago, said his firm spends in the low-to-mid-six figures annually, AI only makes up perhaps 5% to 10% of that amount, “but it’s growing.”
“I expect that number to double in the next 24 months, but not just in dollars — in value,” he said. “This isn’t about spending more. It’s about spending smarter.”
Experts said the relatively smaller current spend on AI in tech budgets may tick up steadily over time as firms move beyond exploration into implementation.
AI still makes up only a small percentage of tech budgets
Percentage-wise, even the most gung-ho firms are still only allocating single digits to AI-specific tools.
According to the “Cost of AI” report, around half, 51%, of wealth management firms reported spending between 1% and 10% of their tech budgets on AI.
And over half of wealth management firms, 55%, reported that they spent only between 1% and 10% of their AI budgets specifically on generative AI in the past 12 months.
READ MORE: How much time is AI saving advisors? And how do they spend it?
Alvin Carlos, financial planner and managing partner at District Capital Management in Washington, D.C., said he plans to create another custom GPT to help train advisors on how to run better sales calls. It only costs him $25 per month per user to subscribe to ChatGPT’s business plan.
“I am planning to look into how AI can help us create financial plans,” he said. “For this, I would likely have to spend $5,000 or more to hire a developer.”
Currently, Nathan Sebesta, owner of Access Wealth Strategies in Artesia, New Mexico, said his firm’s technology budget is modest and some of the tools they use have little to no cost, with only a small portion allocated to AI experimentation.
“We expect that to grow as tools become more advisor-friendly,” he said. “We’re committed to learning and exploring without compromising our personal touch with clients.”
Similarly, Marcos A. Segrera, wealth manager and principal in Evensky & Katz / Foldes Wealth Management in Coral Gables, Florida, said his firm’s annual technology spend is only about 3% of revenue, with only a small part AI-related.
“We do expect both of these figures to increase in the coming years as AI technology matures and we identify more high-value use cases,” he said.
Larger AI budget allocations in the future
The relatively low percentage allocated to AI in advisor tech stacks compared to other budget items may change over time.
Colleagues at other firms are still in their “learning phase,” said Fergal Glynn, chief marketing officer at AI security firm Mindgard.
“I have noticed that although they are interested in using AI, they feel hesitant,” he said. “It’s like having a wait-and-see attitude, as all they want is proof of return on investment before committing to it.”
Rather than push for a “big bang” approach with a broad rollout, Raj Bhaskar, co-founder and CEO of embedded business accounting firm Tight, said his business is taking a controlled approach to deployment focused on “precision, performance and regulations.” About 15% to 20% of the firm’s tech budget goes into AI initiatives and “that will gradually change as there is fevered interest in these initiatives, not due to hype,” said Bhaskar.
“We’re tackling AI from a very focused, granular perspective, starting with automation of income type classification, anomaly detection and foreseeing tax comments,” he said. “That level of control helps us go faster while being able to build trust.”
In AI’s integration within financial services, scalability will only occur after businesses address factors such as explainability, compliance and auditability, said Bhaskar.
Today, the most tangible opportunity lies with tactical AI, relegated to high-frequency tasks in back offices. The single biggest constraint is not ethics or even budget, it is how complex data integration is.
“Without clean standardized data as inputs, strong models do not provide reliable outcomes,” he said. “Most firms neglect the amount of foundational data work required before AI can scale.”
