Wealth management firms that disclose artificial intelligence use in regulatory filings are hiring faster and posting stronger advisor productivity numbers than firms that do not, according to new research from Astraeus and Pirker Partners. The findings challenge widespread assumptions that AI adoption leads to job cuts in the sector.
The 2026 RIA Market Monitor, released today, analyzed Form ADV filings from 6,384 independent registered investment advisors (RIAs). Researchers combined Part 1a and Part 2a disclosures into a single data set using Astraeus's proprietary AI platform. The result is one of the first data-driven looks at how AI adoption correlates with firm performance across the U.S. wealth management industry.
Firms with AI disclosures are adding headcount, not cutting it
Firms that disclosed meaningful AI use increased total headcount by 15% between April 2025 and April 2026. Comparable firms without AI disclosures grew headcount by 8%. Among enterprise and large RIAs, non-advisory staffing rose 14.2% - more than double the growth rate of advisor headcount. Researchers found no evidence that AI adoption is reducing employment.
"Much of the public conversation around AI assumes that the technology will reduce headcount, but that's not what we're seeing in the wealth management industry," said Jon Stevenson, Co-Founder and President of Astraeus. "The firms moving fastest with AI are hiring people, investing in operational infrastructure, and building the capabilities necessary to support more sophisticated businesses. At this stage, AI appears to be creating capacity rather than replacing it."
Adoption remains concentrated among larger firms
Only 6% of independent RIAs disclosed AI use in their March 2026 filings, though those firms collectively manage roughly 11% of industry assets. Adoption rates climb with firm size: 16% of RIAs managing between $5 billion and $25 billion in assets disclosed AI use, compared with 7% of mid-sized firms and 5% of smaller firms. Hybrid RIAs were more likely than fee-only firms to report adoption.
"The industry narrative often suggests AI is everywhere, but the disclosure record paints a more nuanced picture," said Alois Pirker, Founder and CEO of Pirker Partners. "Meaningful adoption is occurring primarily among firms with the scale, resources, and operational complexity to invest in enterprise initiatives."
Firms adopting AI were nearly twice as likely to offer private equity investments and more than three times as likely to offer private credit solutions. They were also more likely to provide tax-optimized portfolios and direct indexing - suggesting AI adoption correlates with greater business and investment complexity. For management teams evaluating AI for Executives & Strategy, the data indicates adoption patterns track closely with operational sophistication.
Most AI use cases are operational, not investment-driven
Nearly half of firms identified AI applications tied to administrative efficiency: meeting summaries, document generation, workflow management, and CRM updates. Only 4% reported using AI as a direct input into investment decisions, while nearly 40% explicitly stated that AI does not make investment decisions. The findings suggest AI is currently a back-office force multiplier rather than a portfolio management tool.
Advisor productivity metrics reinforce this picture. Among enterprise and large RIAs, assets under management per advisor increased 22% for firms with AI disclosures, versus 12% for peers without them. Researchers cautioned against crediting AI as the sole driver - firms adopting AI were already growing faster before widespread deployment began.
Disclosures likely understate real adoption levels
The report found that 42% of AI-related disclosures focused primarily on risks, 55% balanced risks and benefits, and only 4% emphasized benefits. Many firms appear to discuss AI through a compliance lens rather than as a business capability. Andrew Lasky, Head of GTM and Strategy at Astraeus, said disclosures should be viewed "as a floor rather than a scorecard for AI adoption," since actual usage almost certainly extends beyond what appears in public filings.
For professionals working in AI for Finance, the gap between disclosed and actual AI use is a critical nuance - regulatory filings capture what firms are willing to document, not the full scope of tools already in production.
Why this matters for management
The data challenges a core assumption many business leaders carry into AI planning: that automation means workforce reduction. In wealth management, at least, the early evidence points the other direction. Firms adopting AI are scaling headcount and operational infrastructure simultaneously. For managers building business cases around AI investment, the productivity gains are real - but they appear to come from giving advisors and staff better tools, not from eliminating roles.
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