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To research a public company’s AI exposure, start with its latest Form 10-K, then compare what it says there with its product pages, investor materials, earnings releases, and call materials. Separate what the company sells from how it uses AI internally, and distinguish reported results from plans, forecasts, and promotional claims. A mention of AI is a lead to investigate—not proof of material revenue, customer traction, or investment value.
Start with the latest Form 10-K
Find the company’s most recent annual report and confirm the registrant, filing date, and fiscal period before taking notes. Use the filing’s contents page to locate the sections that explain both the business and its uncertainties. For a live analysis, use the issuer’s current filing rather than relying on an older example.
- Business: Map products, services, customer markets, and strategy. Identify what the company actually sells and where AI appears in that offering.
- Risk Factors: Look for disclosed adoption uncertainty, competition, development costs, delays, capacity constraints, customer concentration, regulation, intellectual-property issues, and cybersecurity risks.
- Cybersecurity: Review the company’s stated governance and risk controls; do not treat the mere presence of a policy description as proof that risks are eliminated.
- MD&A: Compare management’s discussion of results and trends with its AI-related statements. Look for evidence of effects on revenue, expenses, margins, or operations, not just forward-looking ambitions.
- Financial statements and market-risk disclosures: Ground the narrative in reported financial context and any disclosed exposure to relevant operating or market risks.
A useful filing map and disclosure checklist are available in the SEC’s C3.ai FY2025 Form 10-K; use it as an illustration of where disclosures can appear, not as a substitute for the company you are studying.
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Read product pages, investor presentations, earnings releases, and earnings-call materials alongside the filing. Company websites can describe products and strategy more recently than an annual report, but a website page is not automatically part of the filed report. For example, C3.ai’s FY2025 annual report says that its website and social content are not incorporated by reference into its Form 10-K. Treat each source according to its channel and date, and compare website claims with filed disclosures rather than assuming they carry the same status.
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Record the exact URL and publication date for each item. For calls and presentations, note the reporting period they concern and distinguish prepared remarks, management answers, and formal filings where possible.
Classify the company’s role in AI
Do not classify a company as an “AI company” just because its materials use the term. Identify the mechanism connecting AI to the business.
Provider or seller
Does the company sell AI hardware, software, applications, or services? Record the named product or feature, the customer problem it is intended to address, and whether the company reports results tied to it.
Rank #2
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Internal adopter
Does the company describe deploying AI in its own operations? Note the stated use case and whether the company reports an observed operational result, or only describes an initiative.
Both, or unclear
A company may sell AI-related offerings and use AI internally. Keep those roles separate in your notes. If disclosures do not establish a role, describe what is disclosed and leave the classification uncertain rather than inferring it from branding.
Look for specific mechanisms and evidence
Search for concrete details, not only occurrences of “AI” or “generative AI.” Useful evidence includes:
- Named products, features, and the capabilities being offered.
- Research and development spending or capital commitments described by the company.
- Customer demand, adoption, or usage claims, with the period and basis stated.
- Reported revenue or operating results attributed to an AI-related offering or deployment.
- Dependencies on data centers, energy, suppliers, distribution, or customers’ ability to finance infrastructure.
Label each statement by what it is: a current product description, an observed result, a target, a forecast, a risk, or general positioning. A pipeline estimate, strategic goal, or statement of opportunity is not realized revenue. When a company does not quantify an outcome, do not supply a number or imply that the commercial effect is established.
Balance opportunity with execution risk
Assess the potential business mechanism alongside what could prevent it from working. Consider adoption uncertainty, product-development and operating costs, competition, launch delays, capacity limits, concentration among customers or suppliers, regulation, intellectual-property questions, privacy, cybersecurity, and human oversight where relevant. Connect AI-specific statements to the company’s broader risk and governance disclosures.
Management discussion establishes that the company has disclosed or discussed a topic; it does not by itself prove a material exposure, successful deployment, competitive advantage, or financial return. As one company-specific example, AMD’s FY2026 Form 10-K, filed February 4, 2026, discusses AI accelerator demand alongside customer use, data-center capacity and energy constraints, and uncertainty about generative AI adoption. AMD states: “The demand for such products will in part depend on the extent to which our customers utilize generative AI solutions in a wide variety of applications, and both the near-term and long-term trajectory of such generative AI solutions is unknown.” This is AMD’s disclosure about its own business and dependencies, not an independent forecast for other companies.
Rank #4
Build a dated evidence table
A compact evidence log makes it easier to compare claims and revisit them when disclosures change. Use one row per material statement, and keep company assertions separate from independently reported facts.
| Field | What to record |
|---|---|
| Source | Document or page title and channel, such as Form 10-K, product page, investor presentation, earnings release, or call material. |
| URL and date | Exact source URL and publication or filing date. |
| Period | Fiscal period or operating period the statement addresses. |
| Evidence | Relevant page, item, or passage, captured as an exact quotation or faithful paraphrase. |
| Claim type | Current offering, observed result, target, forecast, risk, or general positioning. |
| Provenance | Company statement or independently reported fact; do not blend the two. |
Before publishing or relying on the analysis, check newer quarterly filings, material 8-K filings, and updated investor materials. Disclosures change, and an older product description or forecast may no longer reflect the company’s current position.
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When comparing issuers, use the same time period where possible and make clear when periods differ. These are comparison dimensions, not a universal scorecard:
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- Role: AI hardware, software, or service provider; internal adopter; or both.
- Evidence strength: Named offerings and reported outcomes versus plans, targets, forecasts, or broad positioning.
- Commercial traction: Disclosed customers, demand, or revenue contribution versus unquantified opportunity.
- Dependencies: Product development, computing capacity, data centers, energy, suppliers, distribution, and customer financing.
- Economics: Investment and operating costs, expected returns, potential revenue or margin effects, and customer concentration where disclosed.
- Risk and governance: Competition, privacy, cybersecurity, intellectual property, regulation, human oversight, and management or board oversight.
- Time and geography: When a claim was made, the filing period it concerns, and relevant jurisdictions.
Public disclosures vary in detail. A company’s failure to discuss an issue in the materials you reviewed is not proof that it has no exposure.
Write a conclusion that states both what is known and what is not
Summarize the evidence for AI exposure, the business mechanism involved, and the principal dependencies or risks. Identify which conclusions rely on current offerings or reported outcomes and which rely on management targets or forecasts. State what the available evidence cannot establish—for example, materiality to revenue, customer traction, competitive advantage, or valuation—unless dated sources support those claims. This is a disclosure-based research method, not an audit of management’s statements, a legal interpretation, or an investment recommendation.
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If you want to capture a company’s product or investor page for your evidence log, ScreenshotNeo offers a one-request screenshot API. It can help preserve a dated visual record of a web page, but a screenshot does not replace filings, source dates, or judgment about what a claim establishes. See the ScreenshotNeo documentation for request options.
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