The Securities and Exchange Commission wants to talk about how machines read. Specifically, how the most advanced AI systems consume the data that public companies and funds file with the agency.
The SEC’s Office of Data Standards and Innovation will host a public roundtable on November 9, 2026, titled “Machine-Understandable Data in the Age of Super Intelligence (SI).” Wall Street and Big Tech are both sending people, which tells you how seriously the topic is being taken.
What’s on the agenda
The SEC announced the event on October 19, 2026. It runs from 9 a.m. to 3:30 p.m. ET at agency headquarters, 100 F Street, N.E., in Washington, D.C.
In-person seating will be limited. A livestream will be available for everyone who didn’t snag a seat.
The stated goal is to examine how market participants use machine-understandable data in applications involving super intelligence. The program will also cover the risks, costs and governance challenges that come along for the ride.
The speaker list reads like a cross-section of modern finance. Panelists include executives from BlackRock, JPMorgan, Meta, Google, S&P and Two Sigma.
SEC Chairman Paul Atkins is scheduled to deliver closing remarks.
The agency has framed the event around the importance of high-quality information in enabling these technologies. It aims to gather feedback that could inform future practices.
Why the SEC cares about how machines read
The SEC has spent years promoting structured formats like XBRL and Inline XBRL for corporate disclosures. These formats tag the numbers inside filings so software can identify them without guesswork. They have been central to making disclosures readable by machines and to supporting AI-driven analysis.
Demand for this kind of data is climbing fast. Machine access to SEC datasets has increased recently, with Form N-PORT data volume rising over 14x year-over-year through July 2026.
Form N-PORT is the filing where registered funds report their portfolio holdings.
The road to this roundtable
This event didn’t come out of nowhere. It builds on a September 2026 panel that explored AI and public markets.
At that session, Julie Marlowe gave a presentation emphasizing how machine-readable data can improve AI capabilities. The November roundtable picks up that thread and pushes it further into super intelligence territory.
The roundtable is seen as a response to an Executive Order defining super intelligence and its potential to reduce AI-related errors in financial data analysis.
What this means for markets
For investors, the practical stakes come down to data quality. More and more analysis of public companies is done, at least in part, by software rather than people reading filings line by line.
That’s why the governance piece of the agenda may end up being the most consequential. Questions about who is accountable when an AI misreads a disclosure don’t have tidy answers yet.
The cost discussion deserves attention too. Producing richer, more structured filings takes effort, and that burden typically lands on the companies and funds doing the filing. Smaller issuers may feel that more acutely than the giants on the panel.
None of this amounts to a rule proposal. A roundtable is a listening exercise, and the SEC has only said the feedback could inform future practices.
The things to watch on November 9 are fairly specific. Listen for how panelists define “machine-understandable,” whether anyone pushes for new tagging standards, and what tone Atkins strikes in his closing remarks.
Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our Editorial Policy.