AI Bubble Transparency Act
- Sponsor
- Sen. Warren, Elizabeth [D-MA]
- Committees
- Banking, Housing, and Urban Affairs Committee (primary)
- Last action
- Jun 10, 2026
Bottom line
The bill aims to proactively assess and mitigate potential systemic financial risks posed by the rapidly growing artificial intelligence sector through mandated data collection and regulatory recommendations.
What it actually does
This bill mandates the Office of Financial Research (OFR) to collect extensive data from financial companies regarding their exposure to the artificial intelligence (AI) sector, including investments in debt and equity instruments of AI-related companies. It requires the Financial Stability Oversight Council (FSOC) to issue a public report evaluating the financial system's exposure to AI and to make policy recommendations to mitigate potential financial stability risks. The collected data, in unredacted form, must also be submitted to relevant congressional committees.
Proponents argue
Supporters argue that the rapid growth and significant investment in the AI sector, particularly in hardware and infrastructure, could create an asset bubble that poses systemic risks to the financial system. They contend that proactive data collection and oversight by financial regulators are essential to identify vulnerabilities, understand interconnectedness, and develop timely policy responses to prevent a potential financial crisis similar to past bubbles.
Opponents contend
Critics might argue that this bill imposes an undue regulatory burden on financial companies, requiring extensive and potentially proprietary data collection on a nascent and rapidly evolving sector. They may contend that such broad data mandates could stifle innovation in the AI industry by increasing compliance costs and regulatory scrutiny, or that existing regulatory frameworks are sufficient to monitor emerging risks without creating new, sector-specific reporting requirements.
The bill is very short and straightforward, making it highly accessible for a quick and informed review by any interested party.
Section 2, adding Section 157(b) to the Financial Stability Act of 2010
Mandatory Data Collection on AI Sector Exposure
This provision requires the Director of the Office of Financial Research (OFR) to order all financial companies to submit data on their exposure to debt and equity instruments connected to companies involved in artificial intelligence development. This includes chip makers, data centers, cloud providers, AI model developers, and data infrastructure. The data must detail the type, size, interest rates, terms, collateral, and characteristics of both the financial instruments and the AI companies involved.
Supporters argue
Supporters argue this data collection is crucial for understanding the financial system's interconnectedness with the rapidly growing AI sector, allowing regulators to identify and monitor potential systemic risks before they materialize. They believe it provides necessary transparency into a potentially volatile market.
Critics contend
Opponents might argue that the scope of data required is overly broad and could impose substantial compliance costs on financial institutions, potentially diverting resources from productive investments. They may also raise concerns about the privacy and security of such extensive proprietary financial data.
Tradeoffs
This provision balances the need for regulatory transparency and financial stability against the potential for increased compliance costs and administrative burden on financial institutions and the OFR.
Section 2, adding Section 157(d) to the Financial Stability Act of 2010
FSOC Report and Recommendations on AI Financial Risks
This provision requires the Chair of the Financial Stability Oversight Council (FSOC) to publish a report within one year, based on the collected data. The report must evaluate the size, scope, complexity, and interconnectedness of the financial system's exposure to AI, analyze how a decline in AI asset values could threaten financial stability, and assess indirect exposures through other financial companies. Following this, the FSOC must issue policy recommendations to financial regulatory agencies and Congress to mitigate identified risks.
Section 2, adding Section 157(e) to the Financial Stability Act of 2010
Submission of Unredacted Data to Congress
This provision requires the Director of the Office of Financial Research (OFR) to submit all collected data, in an unredacted form, to the Chairs and Ranking Members of the Senate Committee on Banking, Housing, and Urban Affairs and the House Committee on Financial Services within one year of the bill's enactment.
Defines 'artificial intelligence' by referencing section 5002 of the National Artificial Intelligence Initiative Act of 2020 (15 U.S.C. 9401).
Section 2, adding Section 157(a) to the Financial Stability Act of 2010
Why it matters:This is standard legislative practice to avoid reprinting lengthy definitions and ensure consistency across statutes. It is not necessarily evasive.
Case for: Referencing an existing definition ensures consistency in how 'artificial intelligence' is understood and applied across different federal laws and initiatives, preventing conflicting interpretations.
Case against: For a reader unfamiliar with the referenced statute, this requires additional research to fully grasp the scope of the bill's applicability, potentially making the bill less immediately accessible.
Estimated impact: The specific definition of AI will determine the universe of companies and financial instruments subject to reporting, significantly impacting the breadth of data collection.
Exempts small financial companies (banks with less than $10 billion in assets) and financial companies with less than $500 million of financial exposure to AI instruments from the reporting requirements.
Section 2, adding Section 157(b)(2) to the Financial Stability Act of 2010
Why it matters:This is a common legislative technique to narrow the scope of a mandate without making it a primary focus. It balances the need for data with concerns about burdening smaller entities.
Case for: This exemption reduces the compliance burden on smaller financial institutions and those with minimal exposure to the AI sector, focusing regulatory resources on entities that pose a greater potential systemic risk. It prevents disproportionate impact on smaller players.
Case against: Some might argue that even small exposures, when aggregated across many entities, could contribute to systemic risk, or that the exemption threshold might be too high, potentially missing some relevant data points.
Estimated impact: Significantly reduces the number of entities required to report, focusing the data collection on larger financial institutions and those with substantial AI investments.