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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsResearch an AI company the way you would any business: establish what it sells, verify that customers use it, read its filings, examine its finances and risks, and check that the investment and seller are legitimate. AI branding, a product demonstration, or a forecast is not proof of commercial success or a reason on its own to buy a stock.
1. Find out what the company actually does
Start with the company’s business description in its filings and investor disclosures. Identify its products or services, who pays for them, how the company earns revenue, and how much AI matters to that business. A company that sells AI software or computing infrastructure is different from one that uses AI as a feature or to support an existing operation.
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Separate what is available to customers now from research projects, pilots, partnerships, and future plans. A useful way to test the distinction is to ask:
- What specific product or capability is the company describing?
- Can customers buy or use it now, or is it still being developed or tested?
- What evidence does the company provide of customer demand, deployment, or repeat purchasing?
- Does the company explain how AI contributes to its operations or revenue, or is the connection mainly promotional?
FINRA’s general stock-research guidance recommends examining a company’s operations, demand, management, growth and profitability prospects, debt, industry conditions, and risks. Apply those questions to the business rather than treating “AI company” as a complete description.
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2. Read the filings, not just summaries
For a U.S. public company, use the SEC’s EDGAR system to find the issuer’s filings. Start with its latest annual Form 10-K and quarterly Form 10-Q, then compare them with earlier reports. FINRA describes 10-Ks as annual audited reports and 10-Qs as quarterly unaudited reports. These filings provide the company’s own account of its business, risks, and financial results.
Read the business description, Management’s Discussion and Analysis (MD&A), risk factors, financial statements, debt and liquidity information, and any material legal proceedings. Compare the same disclosures across periods. For example, a change in how management describes an AI product, customer concentration, costs, or financing needs can help you assess whether AI is becoming economically significant or remains an aspiration. A change alone does not establish whether the business is improving or worsening; look at the context and reported results.
3. Verify AI claims against evidence
The SEC, NASAA, and FINRA warn investors to scrutinize both company disclosures and promotional campaigns. The SEC’s investor alert says false claims about AI-related products and services may be used in pump-and-dump schemes. It also cautions against relying solely on AI-generated investment information, which can be inaccurate, incomplete, outdated, misleading, or fabricated. Check the underlying sources yourself and consult more than one reliable source.
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Look for a reasonable basis for specific claims. Compare promotional language with filed descriptions and reported results, and distinguish a deployed product from a forecast, demonstration, or announcement. A partnership announcement may show that two organizations have a relationship; it does not by itself establish customer adoption, meaningful revenue, or a durable competitive advantage.
SEC Chair Gary Gensler said public companies “should make sure they have a reasonable basis for the claims they make” about AI and the particular risks they face. He also warned that “AI washing” may violate securities laws. Both statements were last reviewed by the SEC on March 18, 2024. They are a reason to examine the company’s specific evidence, not a regulator-issued scorecard for deciding whether to invest.
4. Examine financial performance and valuation
Review revenue, expenses, earnings, cash generation, debt, and financing needs across several reporting periods. For a business developing or operating AI, look for how costs or commitments related to computing capacity, data centers, research, and infrastructure appear in its own financial statements and disclosures. Companies may report these items differently; do not assume a single AI-specific accounting checklist applies to every issuer.
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FINRA describes several measures investors can use when evaluating public stocks. Treat each as one input, not a verdict. Ratios depend on the underlying figures, the measurement date, and the businesses chosen for comparison.
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| Measure | What it compares | What to keep in mind |
|---|---|---|
| Earnings per share (EPS) | Earnings divided by shares. | One indication of current financial strength; interpret it alongside the company’s earnings and share information. |
| Price-to-earnings (P/E) | Share price relative to EPS. | Shows what investors are paying per dollar of earnings. It is less useful as a standalone comparison when companies have very different earnings profiles. |
| Price-to-sales (P/S) | Market capitalization relative to revenue. | Can be useful when a company is not profitable, but does not account for whether sales produce a profit. |
| Debt-to-equity (D/E) | FINRA describes this as total liabilities divided by shareholder equity. | Used to assess leverage and debt financing; examine the issuer’s actual obligations and context as well. |
FINRA advises comparing ratios with the overall market and the company’s industry because typical ratios vary significantly between industries. Choose peers with relevant business models, and note the figures and date used. Comparing an AI infrastructure provider with a software company or an established business that merely uses AI can produce a misleading conclusion if their economics differ.
5. Assess company-specific risks and oversight
Read the risk disclosures in the context of how the company operates. Depending on its products, suppliers, and customers, relevant exposures may include privacy, bias, cybersecurity, legal compliance, dependence on third-party providers, and operational reliance on AI systems. The important question is how a risk could affect this particular business and what the company discloses about managing it.
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For public companies covered by the SEC’s cybersecurity disclosure rule, the SEC describes requirements for current disclosure of material cybersecurity incidents and periodic reporting about processes for assessing, identifying, and managing material cybersecurity risks, management’s role, and board oversight. The SEC rule page states that the rule became effective September 5, 2023. These disclosures do not guarantee that a company is secure, and not every AI-related incident is necessarily material.
Some risks depend on the industry. The U.S. Treasury’s discussion of AI in financial services identifies privacy, bias, and third-party-provider risks in that sector, and recommends that financial firms review AI use cases for compliance before deployment and reevaluate them periodically. That sector-specific guidance should not be treated as a rule for every AI company.
6. Compare companies using the same evidence
When weighing multiple companies, use common dimensions while allowing for different business models. This comparison framework applies general investor due-diligence guidance; it is not a standardized SEC or FINRA scorecard.
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| Comparison dimension | Evidence to examine |
|---|---|
| Business model and AI’s role | What the company sells, how it earns revenue, and whether AI is central to the product, a feature, or an operational tool. |
| Demand and deployment | Whether products are commercially available and what the issuer reports about customer use, demand, or repeat purchasing. |
| Financial condition | Revenue growth, profitability, cash generation, financing needs, and debt across reporting periods. |
| Valuation | Relevant financial ratios and a peer set of companies with meaningfully comparable businesses. |
| Concentration and dependencies | Reliance on particular customers, suppliers, platforms, or third-party providers, as described by the company. |
| Risks and oversight | Disclosed operational, cybersecurity, privacy, regulatory, and legal risks, and the issuer’s account of governance and management. |
| Specificity and consistency | Whether management describes AI capabilities concretely and consistently across disclosures and reporting periods. |
7. Verify the security, seller, and promotion
Before sending money or placing an order, independently check what security is being offered, where it trades, and whether the intermediary or professional is registered for the relevant activity and jurisdiction. The SEC/NASAA/FINRA investor alert points U.S. investors to Investor.gov registration checks and SEC resources for registered exchanges and alternative trading systems. Confirm communications through independent channels, especially when a message claims to come from an executive or celebrity: the alert warns about impersonation scams using deepfake audio and video.
Treat guaranteed returns, pressure to act quickly, unregistered sellers, celebrity endorsements, and promotion-heavy campaigns as warning signs. No single warning sign proves fraud, but it is a reason to pause and verify rather than rely on the promotion.
For private or pre-IPO offers
Private-company offers need separate diligence; public-company filing research does not transfer completely to private offerings, where public information may be limited. The SEC warns that pre-IPO shares may be difficult or impossible to resell, the company may never go public, and an investor may lose the entire investment. Broad public solicitation may be unlawful depending on whether the offering is registered or qualifies for an exemption. AI is one of the emerging-technology themes used to pitch offers, but that fact alone does not establish that a particular offer is fraudulent.
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What this process can—and cannot—tell you
Filings and other checkable evidence can help you distinguish a commercial product from an AI narrative, understand a company’s reported financial condition, and identify risks that matter to its business. They cannot establish that a stock is suitable for you or guarantee future performance. The cited guidance is primarily U.S.-focused; securities rules, disclosure duties, and access to private offerings differ by jurisdiction and issuer type.
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