CORPORATE GOVERNANCE | 2026-09-06

SEC Investor Advisory Committee to Examine Artificial Intelligence (AI) Disclosure for Public Companies

The SEC's Investor Advisory Committee will discuss artificial intelligence and public-company disclosure on September 10, 2026. Here is what California boards and general counsel should take from it.

On September 10, 2026, the U.S. Securities and Exchange Commission's Investor Advisory Committee will convene a public meeting whose agenda includes a panel on disclosure and artificial intelligence. For California, home to the densest concentration of publicly traded technology and applied-AI companies in the country, that agenda item is not academic. The committee does not write rules, but it advises the Commission on priorities that shape rulemaking, examinations, and enforcement.

The SEC Investor Advisory Committee and Its September 10, 2026 Meeting

The Securities and Exchange Commission's Investor Advisory Committee will hold a public meeting on September 10, 2026, beginning at 10:00 a.m. Eastern Time, at the Commission's headquarters, 100 F Street NE, Washington, DC 20549, in the Multipurpose Room, and by live webcast on www.sec.gov. The published agenda includes a welcome and opening remarks, approval of previous meeting minutes, a panel discussion regarding disclosure and artificial intelligence, a panel discussion regarding Regulation National Market System (Regulation NMS), subcommittee reports, and a non-public administrative session. Members of the public may submit written statements to be received on or before September 9, 2026. For California companies whose disclosure practices are shaped in board meetings, disclosure committees, and outside-counsel drafting sessions, a Commission advisory body devoting a formal panel to artificial intelligence and disclosure is a development worth tracking closely.

What the Investor Advisory Committee Is

The Investor Advisory Committee advises the Commission on regulatory priorities and initiatives designed to protect investors and promote the integrity of the securities markets. It brings together voices meant to represent the interests of individual and institutional investors, and it examines emerging issues before those issues mature into formal Commission action. The committee functions as an early-warning and priority-setting body: the topics it studies frequently foreshadow where the Commission's attention, and eventually its rules and examinations, will turn. Because the committee reports directly to the Commission, its discussions carry weight beyond their advisory label. A panel dedicated to disclosure and artificial intelligence tells public companies that investor-protection concerns about AI have reached the level of institutional attention, not merely commentary.

What This Meeting Is, and What It Is Not

Precision matters here. The Investor Advisory Committee makes recommendations to the Commission; it does not itself adopt rules. The September 10, 2026 meeting is a discussion and advisory event, not a rulemaking proceeding. Nothing that occurs at the meeting will, by itself, change a single disclosure obligation or create a new one. California general counsel should resist two opposite errors: dismissing the meeting as irrelevant because no rule will emerge from it, and overreacting as though new mandates take effect the next morning. The correct posture is attentive preparation. Advisory discussions are how the Commission tests ideas, hears from investor representatives, and builds the record that can later support guidance, comment-letter emphasis, examination priorities, or proposed rules.

Why California Companies Should Pay Attention

California is where much of the public market's artificial intelligence story is written. The state's issuers include semiconductor designers, cloud infrastructure providers, enterprise software companies embedding AI into their products, consumer platforms deploying machine learning at scale, and a growing cohort of companies whose valuations rest substantially on AI narratives. When investor-protection attention turns to how issuers describe artificial intelligence, California companies are disproportionately in the frame. The disclosure choices these companies make, in their risk factors, their management discussion, their earnings commentary, and their promotional materials, are precisely the choices the Commission's investor-protection apparatus is examining. Paying attention now, before guidance or examination emphasis hardens, gives California boards the runway to align their practices deliberately rather than reactively.

Why Artificial Intelligence Disclosure Is on the SEC's Radar

Artificial intelligence has become one of the most powerful drivers of market narratives, capital allocation, and investor expectations. Where a theme moves valuations, the securities laws follow, because the laws exist to ensure that what moves valuations is accurate. The Commission's interest in AI disclosure flows from the same investor-protection logic that has governed every prior wave of transformative technology: investors are entitled to truthful, non-misleading information about the factors that materially affect the companies they own.

The Rise of AI Washing as a Disclosure Concern

The Commission under Chairman Paul S. Atkins has emphasized combating what is commonly called AI washing, the making of materially false or misleading claims by issuers or advisers about their use of artificial intelligence, as an enforcement and disclosure concern in 2026. The concept parallels the greenwashing problem the Commission previously scrutinized: a company overstates, embellishes, or fabricates the extent, sophistication, or results of its AI capabilities to attract investors or customers. AI washing can take many forms, from claiming proprietary models that are in fact off-the-shelf tools, to describing capabilities still in early experimentation as though they were deployed and revenue-generating, to attributing financial performance to AI in ways the underlying facts do not support. The core problem is the same one the antifraud provisions have always addressed: statements that create a false impression of a company's business.

Investor-Protection Concerns Specific to AI

AI presents disclosure challenges that make investor-protection concerns acute. The technology is complex and often opaque, which widens the information gap between insiders who understand a company's actual capabilities and investors who must rely on the company's descriptions. AI claims are frequently forward-looking and aspirational, describing what a model may achieve rather than what it has achieved. The competitive incentive to appear at the frontier of AI is intense, creating pressure toward optimistic framing. And the pace of the field means that descriptions can become stale quickly, so that a statement accurate when made may mislead if not updated. Each of these features increases the risk that investors receive an inaccurate picture, which is exactly the risk the disclosure regime is built to counter.

Why an Advisory Panel Signals Institutional Attention

The decision to devote an Investor Advisory Committee panel to disclosure and artificial intelligence reflects that these concerns have matured from individual observations into a systemic priority. Advisory panels are convened around issues the Commission believes merit sustained, structured examination from the investor perspective. For California issuers, the practical takeaway is that AI disclosure is no longer a niche drafting question handled quietly in the risk-factor section. It is a topic the Commission's investor-protection machinery is studying in the open, and companies should expect that study to inform comment letters, examination focus, and enforcement judgment in the periods ahead.

How Artificial Intelligence Appears in Existing Disclosure Obligations

A crucial point for California boards is that no new AI-specific rule is required for AI to be a disclosure obligation today. The existing disclosure regime, built on the Securities Act of 1933 and the Securities Exchange Act of 1934 and implemented through Regulation S-K, already reaches AI wherever it materially affects a company's business, financial condition, or prospects. Companies that wait for a bespoke AI rule before disciplining their AI disclosures misunderstand how the framework operates.

Risk Factors Under Regulation S-K Item 105

Item 105 of Regulation S-K requires issuers to disclose the material factors that make an investment in the company speculative or risky. Artificial intelligence generates risk factors on both sides of the ledger. On the risk-of-use side, a company deploying AI may face model errors, bias and discrimination exposure, data-privacy and security vulnerabilities, intellectual-property disputes over training data, regulatory uncertainty, and reputational harm from AI failures. On the competitive-disruption side, a company may face the risk that competitors' AI capabilities erode its market position, or that its own AI investments fail to produce returns. Item 105 demands that risk factors be specific to the company rather than generic boilerplate. A California software company cannot satisfy Item 105 by reciting that AI is generally risky; it must describe the particular AI-related risks that are material to its own operations, in terms an investor can use.

Management's Discussion and Analysis Under Item 303

Item 303 of Regulation S-K requires management's discussion and analysis of financial condition and results of operations, including known trends, events, and uncertainties reasonably likely to have a material effect. Where artificial intelligence is driving revenue, compressing margins through infrastructure spending, requiring significant capital expenditure on compute, or reshaping a company's cost structure, MD&A is where investors expect a candid account of those dynamics. If a California company attributes growth to AI-enabled products, MD&A should give investors enough to understand the durability and drivers of that growth. If AI investment is a known uncertainty, whether it will pay off, how much capital it will consume, or what regulatory developments could affect it, Item 303 calls for its disclosure. The management discussion is often where AI claims made in more promotional settings must be reconciled with financial reality.

The Interaction of Voluntary Statements and Mandatory Filings

AI descriptions do not live only in SEC filings. They appear in press releases, product launches, investor-day presentations, earnings-call remarks, and marketing. The securities laws do not confine antifraud liability to formal filings; materially misleading statements made in connection with the purchase or sale of securities can create exposure wherever they occur. This means the AI narrative a California company tells its customers and the public must be consistent with, and no more optimistic than, what it can substantiate and what it discloses in its filings. A disconnect between an aggressive public AI story and a cautious filing, or between either and the underlying facts, is precisely the kind of gap that draws scrutiny.

Materiality and Antifraud Exposure for Artificial Intelligence Claims

The disclosure obligations above are enforced through a materiality standard and a set of antifraud provisions that give AI claims real legal consequences. California companies should understand how these doctrines apply to statements about artificial intelligence, because that is where advisory attention translates into litigation and enforcement risk.

The Materiality Standard

Under the standard articulated in TSC Industries v. Northway and reaffirmed in Basic Inc. v. Levinson, information is material if there is a substantial likelihood that a reasonable investor would consider it important in making an investment decision, or that its disclosure would significantly alter the total mix of information available. Applied to AI, materiality turns on the specific role artificial intelligence plays in a company's business. For a company whose valuation and strategy center on AI, statements about the nature, performance, and prospects of that AI are likely to be material. Basic also supplies the framework for contingent or speculative matters, weighing the probability that an event will occur against its anticipated magnitude, which is directly relevant to forward-looking AI claims about capabilities not yet realized. Materiality is the gatekeeper: it determines which AI statements carry legal weight.

Antifraud Liability Under Section 10(b) and Rule 10b-5

Section 10(b) of the Exchange Act and Rule 10b-5 prohibit material misstatements and omissions made with scienter in connection with the purchase or sale of securities. This is the central antifraud exposure for AI claims. A California company that materially overstates its AI capabilities, that describes experimental technology as deployed, that claims proprietary models it does not have, or that attributes performance to AI in ways the facts do not support, risks a 10b-5 action if those statements are material and made with the requisite state of mind. Omissions matter too: a statement that is literally true but creates a misleading impression because it omits qualifying facts can be actionable. The antifraud provisions do not require an AI-specific rule; they apply to any material misrepresentation, and AI claims are no exception.

Securities Act Liability Under Sections 11 and 12(a)(2)

For companies conducting registered offerings, Securities Act Sections 11 and 12(a)(2) impose liability for material misstatements or omissions in registration statements and prospectuses. These provisions are more demanding for issuers than 10b-5 in an important respect: Section 11 liability for the issuer does not require proof of scienter, so an issuer can be liable for a material misstatement in a registration statement even without intent to deceive. For a California company going public or raising capital in a registered offering while telling an AI-heavy story, this raises the stakes considerably. The AI claims in an offering document must be accurate and substantiated, because the near strict-liability character of Section 11 leaves little room for the excuse that the statement was merely optimistic.

The PSLRA Safe Harbor for Forward-Looking Statements

Because so many AI claims are forward-looking, the Private Securities Litigation Reform Act safe harbor is central to managing exposure. The PSLRA protects forward-looking statements that are identified as such and accompanied by meaningful cautionary language identifying important factors that could cause actual results to differ materially. The protection is not automatic. Cautionary language must be substantive and tailored, not generic boilerplate, and the safe harbor generally does not shield statements known to be false when made. For AI, this means a California company can describe aspirational capabilities and future plans with meaningful legal protection, but only if it clearly labels those statements as forward-looking, pairs them with specific and current cautionary factors, and does not use forward-looking framing to disguise present falsehoods. Disciplined use of the safe harbor is one of the most effective tools available for AI disclosure.

The line between a protected forward-looking statement and an unprotected statement of present fact deserves particular care in the AI context. A claim about what a model will do, how a product roadmap will unfold, or what returns an AI investment is expected to generate is forward-looking. A claim about what a model does today, what capabilities the company currently possesses, or what results have already been achieved is a statement of present or historical fact and falls outside the safe harbor. AI descriptions frequently blur these categories, mixing what exists with what is planned in a single sentence. California companies should draft with that boundary in mind, separating verifiable present-tense claims, which must be accurate on their own, from forward-looking projections, which must be labeled and cautioned. Where a statement contains both, the present-fact component receives no safe-harbor protection regardless of how the forward-looking portion is framed.

Board and Committee Oversight of Artificial Intelligence

Disclosure discipline is not only a drafting exercise; it is a governance responsibility. The Investor Advisory Committee's attention to AI disclosure implicates the oversight duties of California public-company boards and the controls that management must maintain. Boards that treat AI as purely a management or engineering matter, disconnected from oversight and disclosure, expose themselves and their companies to risk.

Caremark Oversight Duties Under Delaware Law

Many California public companies are incorporated in Delaware, and Delaware law imposes on directors a duty of oversight under the Caremark line of authority. Directors must make a good-faith effort to implement and monitor a reasonable system of controls and reporting for the risks central to the company's business, and they must not consciously ignore red flags that such systems surface. Where artificial intelligence is mission-critical, whether as the company's product, a core input, or a significant risk, AI oversight falls within the board's Caremark responsibilities. This means the board should ensure that management has systems to identify material AI risks, that information about those risks reaches the board, and that the board attends to warning signs. A board that never engages with the accuracy of its company's AI claims, in a company where AI is central, invites the argument that it failed its oversight duty.

Allocating AI Oversight Among Board Committees

Effective oversight requires deciding where AI responsibility sits. Some boards assign AI risk to the audit committee, given its existing role over risk and disclosure; others task a technology or risk committee, or address AI at the full board. There is no single correct structure, but there should be a deliberate one. The board should be clear about which body owns AI oversight, what reporting it receives, how often it engages, and how AI risk connects to disclosure. Documenting this allocation and the board's engagement is important both for effective governance and for demonstrating, if later questioned, that the board discharged its oversight duty in good faith.

Connecting Governance to Disclosure Accuracy

Board oversight of AI and public disclosure of AI are two ends of the same rope. The board's oversight system should feed the disclosure process, so that the material AI risks the board monitors are the risks investors read about, and so that the AI capabilities the company touts are ones the board understands to be real. When governance and disclosure are connected, the company's public AI narrative rests on an informed, monitored foundation. When they are disconnected, the company may be making public claims its own board cannot substantiate, which is a governance failure and a disclosure risk at once.

Disclosure Controls and Procedures for Artificial Intelligence Claims

Between board oversight and public statements lies the machinery of disclosure controls. Exchange Act Rules 13a-15 and 15d-15 require issuers to maintain disclosure controls and procedures designed to ensure that information required to be disclosed is recorded, processed, summarized, and reported accurately and on time, and that it is communicated to management to allow timely decisions about disclosure. For AI claims, these controls are the practical mechanism that keeps public statements accurate.

Building AI Into the Disclosure Controls Framework

A company's disclosure controls should specifically address artificial intelligence claims. That means having a process to verify AI-related statements before they are made, whether in filings, press releases, or earnings materials. Who confirms that a described capability actually exists and performs as claimed? Who checks that a proprietary-model assertion is accurate? Who ensures that AI descriptions are current rather than stale? Building these verification steps into the disclosure committee's process transforms AI accuracy from an ad hoc hope into a controlled outcome. For California companies whose most consequential claims often concern technology, integrating technical review into disclosure controls is essential.

Substantiation and Documentation

A disciplined disclosure controls process substantiates AI claims and documents the basis for them. When a company states that its AI improves a metric, drives revenue, or outperforms alternatives, there should be a factual record supporting the claim at the time it is made. Contemporaneous documentation serves two purposes: it improves accuracy by forcing the company to confirm what it can prove, and it provides a defense if a statement is later challenged, by demonstrating that the company had a reasonable basis. In an environment where AI washing is an enforcement priority, the ability to show a reasonable, documented basis for AI claims is a meaningful protection.

Keeping AI Disclosures Current

Because AI capabilities and risks evolve quickly, disclosure controls must include a process for updating AI-related statements. A description accurate last quarter may mislead this quarter if the underlying facts have changed. The disclosure process should revisit AI claims each reporting cycle, retire statements that are no longer true, and refresh cautionary language so that it identifies current rather than outdated risk factors. This maintenance is part of what makes the PSLRA safe harbor effective and what keeps risk factors compliant with Item 105's specificity demands.

What the Investor Advisory Committee Discussion Could Foreshadow

The September 10, 2026 panel will not change any rule, but it may indicate the direction of the Commission's attention. California companies can use the discussion as a forward indicator, while keeping in mind that advisory discussion is not law.

Possible Directions for Commission Attention

An advisory panel on AI disclosure may surface themes that later inform how the Commission approaches the topic: emphasis on specific rather than boilerplate AI risk factors, scrutiny of the gap between promotional AI claims and substantiated capabilities, attention to how AI is reflected in MD&A, and interest in whether existing disclosure adequately serves investors trying to evaluate AI-driven companies. None of these is a rule, but each is a plausible area where comment-letter focus or examination emphasis could develop. California companies that align their disclosures with these themes now position themselves ahead of any such shift.

The Parallel Regulation NMS Panel

The same September 10 meeting includes a separate panel on Regulation National Market System, the framework governing equity market structure. While that discussion addresses trading and market-structure questions rather than issuer disclosure, its presence on the agenda is a reminder that the Investor Advisory Committee's remit spans the full range of investor-protection issues. For public-company disclosure purposes, the AI panel is the relevant item, but California companies with an interest in equity market structure may find the Regulation NMS discussion worth monitoring as well.

Reading the Signal Without Overreading It

The right way to use an advisory meeting is as intelligence, not instruction. California boards and general counsel should follow the AI panel, note the concerns raised from the investor perspective, and factor them into disclosure planning. They should not, however, treat the discussion as though it imposed new obligations. The obligations that govern AI disclosure today are the ones already in the securities laws and Regulation S-K. The advisory discussion helps predict where emphasis is heading; the existing framework is what companies must comply with now.

Practical Steps for California Public Companies

The most valuable response to the Investor Advisory Committee's attention to AI disclosure is concrete preparation within the existing framework. The following steps help California public companies align their AI narratives with the disclosure regime and reduce their exposure.

Conduct AI Disclosure Diligence

Companies should inventory every place their AI story appears, in filings, press releases, investor presentations, earnings scripts, websites, and product marketing, and test each claim against what the company can substantiate. This diligence surfaces inconsistencies between the promotional narrative and the filed disclosure, identifies claims that outrun the facts, and flags descriptions that have grown stale. For a California technology company whose AI claims are numerous and prominent, this inventory is the foundation for disciplined disclosure. It should be repeated periodically, not treated as a one-time exercise, because the AI story changes with each product cycle.

Strengthen Risk Factors and MD&A

Companies should revisit their Item 105 risk factors to ensure they describe company-specific AI risks in concrete terms rather than generic language, covering both the risks of using AI and the competitive risks AI creates. They should review MD&A under Item 303 to ensure that where AI materially affects revenue, costs, capital expenditure, or known uncertainties, investors receive a candid account. The goal is disclosure that gives an investor an accurate, usable understanding of how artificial intelligence shapes the company's business and prospects, drafted with the specificity the rules require.

Discipline Forward-Looking AI Statements

Companies should ensure that forward-looking AI claims are clearly identified as such and accompanied by meaningful, tailored cautionary language that identifies the specific factors that could cause actual results to differ, refreshed each cycle to remain current. They should confirm that no forward-looking framing is being used to obscure a present falsehood, since the safe harbor does not protect statements known to be false when made. Used well, the PSLRA safe harbor lets a company describe its AI ambitions with legal protection; used carelessly, it offers no shield.

Build Governance and Controls

Companies should confirm that the board has a deliberate, documented structure for AI oversight consistent with Caremark duties, that material AI risks reach the board, and that disclosure controls under Rules 13a-15 and 15d-15 specifically verify, substantiate, document, and update AI claims. These governance and controls measures connect the board's oversight to the accuracy of public statements, so that what the company tells investors about artificial intelligence rests on an informed and monitored foundation. Together, diligence, disclosure drafting, forward-looking discipline, and governance form a coherent program that positions California public companies to meet AI disclosure expectations as the Commission's attention to the topic intensifies.

Trembach Law Firm helps California public companies, boards, and general counsel translate the SEC Investor Advisory Committee's focus on artificial intelligence into practical disclosure and governance action, from AI risk-factor and MD&A drafting to forward-looking statement discipline, disclosure controls, and board oversight structures. If your company wants to review how it discloses and governs its use of artificial intelligence, contact Trembach Law Firm at (818) 514-7680 to speak with counsel experienced in public-company securities disclosure and corporate governance.

Contact Trembach Law Firm at (818) 514-7680 for a confidential consultation.

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