What 16,000 SEC Filings Say About AI Adoption on Wall Street
Analysis of ADV filings on the state of AI adoption in financial services.
Matt’s note: This post was updated on Friday April 17 with more granular data from the ADV analysis.
As I’ve said before, AI excels at organizing tedious, repetitive material that no one would review by hand. Form ADV brochures fit that description. They’re long, dense, and there are thousands of them.
So I ran them through a local model.
I downloaded roughly 16,000 Form ADV filings filed in March, the annual disclosures registered investment advisers file with the SEC describing how they run their businesses. Of those, roughly 15,000 were standalone Part 2A brochures, covering about 12,600 advisory firms across hedge funds, private equity, venture, real estate, and traditional RIAs.
What the Filings Show
I scanned every filing for AI-related keywords. About 5,800, just under 40%, mentioned AI at all. In most cases, that meant boilerplate risk disclosures warning about potential impacts on portfolio companies or financial markets.
More than 1,200 firms described using AI in their operations. Fewer than 320 named a specific product. Of those, more than 450 firms disclosed a formal internal AI policy, and 88 said AI-related costs were being charged directly to clients or fund investors.
• Point72 Asset Management — Uses generative AI and large language models “in the operation of its business, including in connection with investment and non-investment processes.”
• Rexford Capital — “Rexford Capital subscribes exclusively to enterprise-grade, paid versions of major AI platforms, including offerings from OpenAI, Anthropic, and Microsoft. This matters for clients: unlike free consumer-facing versions of these tools, our enterprise subscriptions include enhanced data privacy protections, end-to-end encryption, and contractual assurances.”
• Jupiter Asset Management — Names Aladdin, FactSet, Northfield, ICE, Bloomberg, and Style Analytics. “Artificial Intelligence is not used to generate investment decisions but may be used as a tool in the broader analytical approach deployed.”
The detailed disclosures are concentrated at the top. The largest managers — those with more than $100 billion under management — were meaningfully more likely to describe specific AI use cases and governance frameworks than smaller firms. Building an AI governance framework requires lawyers, compliance staff, and engineers working in concert. Most smaller firms don’t have that infrastructure. Explicit references to AI driving investment decisions are less common, and usually more carefully qualified.
Where firms do describe AI in concrete terms, it’s mostly operational. Concentric Capital Strategies, with $3.1 billion in regulatory assets under management, discloses the use of LLMs, such as ChatGPT, within its investment research and business processes.
Caveat: Form ADV filings capture what firms consider material enough to disclose. Routine or limited AI use may not appear at all.
Data & Methodology
Each ADV was converted from PDF to plain text and scanned for AI-related keywords (artificial intelligence, machine learning, large language model, generative AI, and close variants). Filings with at least one hit were passed to Gemma 4 for structured extraction. Gemma read the most AI-relevant passage from each filing — typically drawn from the section with the highest density of AI-related language. It returned a set of flags covering own-use vs. portfolio theme, investment vs. operational use, tool names, governance policy, human oversight language, and cost disclosures.
A Closer Look at the Largest Managers
I selected 100 of the world’s largest and most recognizable money managers — firms spanning traditional asset management, hedge funds, private equity, and venture capital — and scanned their 2026 ADV filings with Gemma.
Seventy-five of the 100 disclosed some form of AI use. Twenty-four named a formal governance policy. Thirteen disclosed that AI-related costs may be passed to investors.
AI Street Data
I’m still working out what to do with the underlying dataset — governance flags, named tools, and cost-charging disclosures across firms. If that would be useful to you, reply and let me know how you’d use it.
The following is for paid subscribers and examines the firms that named governance policies and what those policies actually say, the private equity pattern of charging AI infrastructure costs to fund investors, and three large managers that went from no AI disclosure in 2025 to named frameworks in 2026.
