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© 2026 AI Compliance Atlas. Informational only — not legal advice. Consult qualified counsel before making compliance decisions.Verified Jun 9, 2026
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AI Developer Obligations Under US Law

Developers create, train, or substantially modify AI systems before they reach deployers and end users. Under most US AI laws, developers carry distinct obligations around documentation, transparency, and bias mitigation that are independent from any deployer obligations.

Governance routing

Use the AI governance guide to assign decision rights, committees, lifecycle gates, and escalation paths before mapping role-specific duties into the AI compliance framework register.

Obligations under US laws

  • data handlingFlorida AI Legislation (Deepfake and AI Disclosure Laws)Fla. Stat. § 836.13 (HB 757 / Brooke's Law)

    Do not willfully create, possess with intent to promote, solicit, or produce an altered sexual depiction of an identifiable person without consent, including AI-generated deepfakes. Covered platforms must remove altered sexual depictions within 48 hours of a valid takedown request. Per-image third-degree felony exposure.

    Deadline: 48_hour_takedown

  • transparencyCalifornia Generative AI: Training Data TransparencyCal. Bus. & Prof. Code § 22757.20

    Publicly post on the developer's website a high-level summary of training datasets used for any generative AI system or service made available to Californians on or after January 1, 2022.

    Deadline: by_2026-01-01

  • documentationTransparency in Frontier Artificial Intelligence Act (TFAIA)Cal. Health & Safety Code § 22757.10

    Report critical safety incidents to the California Office of Emergency Services within statutory timeframes.

    Deadline: within_statutory_timeframe

  • transparencyTransparency in Frontier Artificial Intelligence Act (TFAIA)Cal. Health & Safety Code § 22757.10

    Publish a transparency report prior to deploying a new frontier AI model, summarizing pre-deployment assessments and mitigations.

    Deadline: before_deployment

  • governanceTransparency in Frontier Artificial Intelligence Act (TFAIA)Cal. Health & Safety Code § 22757.10

    Publish a written frontier AI safety framework describing how the developer assesses and mitigates catastrophic risks from frontier AI models, with periodic updates.

    Deadline: ongoing

  • transparencyCalifornia AI Transparency ActCal. Bus. & Prof. Code § 22757.x

    Apply latent disclosures (e.g., watermarking or provenance metadata) to AI-generated image, video, and audio content produced by the covered provider's system.

    Deadline: ongoing_from_effective_date

  • transparencyCalifornia AI Transparency ActCal. Bus. & Prof. Code § 22757.x

    Maintain a free, publicly available AI detection tool allowing users to assess whether content is generated or modified by the covered provider's AI system.

    Deadline: ongoing_from_effective_date

  • documentationColorado Artificial Intelligence ActC.R.S. § 6-1-1702

    Provide deployers with documentation including intended uses, harmful or inappropriate uses, data summaries, performance evaluations, mitigation measures, and information necessary for deployers to complete their impact assessments.

    Deadline: before_deployment

  • governanceTexas Responsible Artificial Intelligence Governance Act (TRAIGA)Tex. Bus. & Com. Code § 552.056

    Refrain from developing or deploying AI systems with the intent to engage in unlawful discrimination against protected classes under Texas or federal law.

    Deadline: ongoing

Framework controls

  • documentationISO/IEC 42001Clause 8 + Annex A.6

    Maintain documentation throughout the AI system lifecycle including data management, system development, verification and validation, and deployment per Annex A.6 controls.

  • risk assessmentISO/IEC 42001Clause 6 + Annex A.5

    Conduct AI system impact assessments and risk assessments addressing intended uses, deployment context, affected stakeholders, and mitigation of identified risks per Annex A.5 controls.

  • governanceISO/IEC 42001Clauses 4-5

    Establish, implement, maintain, and continually improve an AI management system (AIMS) covering policies, leadership commitment, roles, and integration with other management systems.

  • governanceNIST AI RMFMANAGE 1-4

    MANAGE function: prioritize and treat identified risks, allocate resources, and implement risk response strategies including mitigation, transfer, acceptance, or avoidance.

  • risk assessmentNIST AI RMFMEASURE 1-4

    MEASURE function: assess, analyze, and monitor AI risks using both quantitative and qualitative methods, including bias evaluation, robustness testing, and explainability assessments.

  • risk assessmentNIST AI RMFMAP 1-5

    MAP function: identify the context, intended uses, stakeholders, and risks of each AI system, including categorization of impacts on individuals, communities, and the organization.

  • governanceNIST AI RMFGOVERN 1-6

    GOVERN function: establish policies, processes, structures, and accountability for AI risk management across the organization, including senior leadership oversight and a risk-based culture.

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Legal disclaimer

This content is informational only and does not constitute legal advice. Laws change frequently and vary by jurisdiction. Consult qualified legal counsel before making compliance decisions. Information accuracy not guaranteed as of any specific date.

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