The US Securities and Exchange Commission (SEC) held a roundtable in Washington on November 9, 2026, examining whether financial disclosures are structured well enough for increasingly capable AI systems to interpret reliably, according to a series of SEC releases. 

Participants included representatives from BlackRock, JPMorgan Chase, S&P, Meta, Google, PwC, Workiva, and Calcbench. The event brought together regulators, financial institutions, technology companies, academics, and investor advocates to discuss the benefits, costs, and risks of machine-understandable data in the age of AI, or super intelligence (SI).

The discussion addressed how structured financial information supports automated analysis, why poor data quality can undermine AI-generated insights, and what role the SEC could play in improving the accessibility and usability of disclosed information. 

SEC Chief Economist Joshua White emphasized that machine-readable data is not necessarily machine-understandable: extracting a figure from a filing does not mean an AI system understands what it represents or how to interpret it.

Why Machine-Readable Data Needs Context

White raised questions about whether structured data improves investment decisions and reduces analysis costs, what risks arise when automated systems use inaccurate or incomplete information, and how the SEC could improve the way disclosed data is structured and accessed.

For chief data officers (CDOs), this reinforces the need to look beyond data availability. 

Organizations must ensure that information retains its meaning as it moves between systems and is consumed by AI applications. Data quality, metadata management, lineage, and validation are essential to preventing automated systems from producing confident conclusions based on flawed inputs.

Implications for AI Governance

CDOs will need to work with technology, finance, compliance, and risk teams to establish consistent data definitions and validation processes. They must also ensure that AI-generated analysis can be traced back to its original sources and that important qualifications are not lost during automated processing.

In recorded remarks, SEC Commissioner Mark Uyeda noted that structured data could help investors compare company disclosures and potentially expand research coverage of smaller companies.

The SEC did not announce any new rules or regulatory requirements following the roundtable. 

However, the discussion underscores a growing AI governance challenge: as AI systems take on more financial analysis, organizations need data that is not merely accessible to machines but accurate, interpretable, and trustworthy.