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CalPrivacy’s Data Broker Enforcement Strike Force: updates and enforcement actions

On November 26, 2025, CalPrivacy (previously the CPPA) issued a decision requiring ROR Partners LLC to pay $56,600 for failure to register as a data broker under California’s Delete Act. According to the decision, the company used “billions of data points” from over 262 million Americans to create consumer profiles and audience lists, which ROR’s clients could then use for targeted advertising. This action was brought as part of CalPrivacy’s Data Broker Enforcement Strike Force, designed to investigate privacy violations by the data broker industry. As part of this effort, CalPrivacy recently issued an Enforcement Advisory highlighting data broker registration requirements related to trade names, websites and parent/subsidiary entities of data brokers. What is a data broker? By law, a data broker is defined as “a business that knowingly collects and sells to third parties the personal information of a consumer with whom the business does not have a direct relationship,” with limited exceptions for certain entities covered under other sector-specific laws. In short, they are companies that collect and sell a consumer’s personal information without directly interacting with that consumer. Data brokers commonly collect information such as email, phone number, browsing history, or location data from places like public records, commercial data, and other sources. Data brokers often then analyze, bundle and sell these profiles about consumers to other businesses. According to CalPrivacy’s DROP website, “[t]his information can be used to influence you – to buy certain products, to feel certain emotions, or even take certain actions. It can put you at greater risk of identity theft, fraud, or AI impersonations. It can also increase the chances your data is leaked or hacked.” What is the Data Broker Enforcement Strike Force? On November 19, one week prior to the ROR decision, CalPrivacy announced its creation of the Data Broker Enforcement Strike Force within its Enforcement Division. According to the announcement, “[t]he Enforcement Division will be reviewing the [data broker] industry for compliance with the data broker registration requirement in the Delete Act, as well as for compliance with the state’s comprehensive privacy law, the California Consumer Privacy Act (CCPA).” This is not the first time the California regulator has targeted data brokers. In 2024, the Enforcement Division conducted a public investigative sweep of data broker registration with a similar goal of verifying compliance with the Delete Act and the CCPA. What is the Delete Act? The Delete Act is a law that applies to data brokers and requires them to register with CalPrivacy and pay an annual fee. Additionally, data brokers must also disclose:
  • The number of consumer deletion requests they have received, as well as their average response time;
  • Whether the data broker collects certain types of sensitive information or the personal information of minors; and,
  • A link on their website informing customers of their rights under the CCPA.
Entities covered under the Act must register by January 31 if they operated as a data broker in the previous year, and they face a $200 penalty per day for failure to register. As of 2024, the data broker registry is maintained by CalPrivacy. The annual fee funds the registry, along with the new mechanism for allowing deletion of personal information from data brokers, called “DROP.” What is DROP? The first-of-its-kind deletion mechanism, the Data Broker Requests and Opt-Out Platform (DROP) will allow consumers to file a single request, which directs all registered data brokers to delete the consumers’ personal information immediately, and continuously every 45 days. According to the DROP website, the data that is subject to DROP may include:
  • Basic identifiers, including name, phone number, or email.
  • Behavioral data, including social media or browsing history, likes and dislikes.
  • Financial-related data, including payment history or spending habits.
  • Health-related data, including your usage of health-related apps, wearables, trackers or websites.
  • Location data, including where you go and how often you visit certain places.
  • Relationships, including your family and friends and how often you interact with them.
  • Inferences, including those about your lifestyle, hobbies, incomes, or even religious or philosophical beliefs, which can include history of the videos you watch, articles you read, or topics you search for.
However, the law has certain exemptions for information that is not required to be deleted. This includes information that the government makes public (property records, court filings, etc.) or information controlled by other state or federal laws, such as certain financial or health information. The intent behind the mechanism is to give consumers more control over their personal information and helps protect their privacy. DROP is expected to be available to consumers on January 1, 2026. What’s next? With the release of DROP and the establishment of the Data Broker Enforcement Strike Force, California is positioned to take data broker enforcement seriously. The decision against ROR Partners LLC was finalized one week after the Strike Force was announced, and all signs say this is the first of many enforcement efforts under this regulatory push. If your company or organization may be acting as a data broker, it is important that you understand your obligations under laws like the California Delete Act, but also other state laws. These laws may have requirements like registering as a data broker, publishing a clear privacy notice, providing specific opt-outs, and reporting certain disclosures.
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California: New AI laws in California – roundup of the 2025 legislative session

This article was originally published by OneTrust DataGuidance on November 24, 2025 and can be found on the DataGuidance website here.

California introduces comprehensive AI laws focusing on transparency, children’s safety, healthcare, antitrust, and law enforcement.

California has taken an aggressive stance towards artificial intelligence (AI) legislation and will likely set the standard for other US states. Back in 2024, Governor Newsom vetoed comprehensive AI safety legislation under bill SB 1047 and advised caution on regulations for this nascent and important technology. This year, Governor Newsom pressed ahead with a full slate of new AI laws. The reasons for this change in approach are many, including but not limited to the lack of federal AI legislation, the growing concern over children’s interactions with AI, especially sexualized content, and harmonization with more stringent requirements in the EU and elsewhere.

This year’s legislative session set records for the number and scope of new AI laws. For the roundup this year, Lily Li, of Metaverse Law Corporation, breaks down the new AI laws by scope and sector, noting where this may add on to existing California legislation and rulemaking from 2024-2025.

General AI safety, transparency, and risk assessments

  • SB 53: Transparency in Frontier Artificial Intelligence Act (Wiener) – Starting in January 2026, California will require large frontier AI developers to publish a framework detailing how they incorporate safety, security, and testing standards into their AI models. SB 53 also creates a mechanism for AI developers and the public to report critical safety incidents, and protects internal whistleblowers who report risks posed by frontier AI models. The law establishes significant penalties for companies that fail to comply, with fines of up to $1 million per violation.
  • AB 316: Artificial Intelligence defenses (Krell) – This amends California’s Civil Code. If a party to a lawsuit develops, modifies, or uses AI, this law prohibits them from asserting as a defense that the AI autonomously caused the harm.
  • AB 853: California AI Transparency Act (Wicks) – This bill expands the existing AI Transparency Act and modifies the effective date from January 1, 2026, to August 2, 2026. The California AI Transparency Act requires covered generative AI developers to provide an AI-detection tool to assess whether image, video, or audio content is created or altered by generative AI. This bill adds to the existing law by requiring large online platforms to embed provenance data into generated content. Starting January 1, 2028, users will also have the option to include latent disclosures on ‘capture devices’ such as cameras, video recorders, and other recorders.

This new California approach to AI transparency and safety legislation needs to be read in conjunction with the following existing laws.

  • California Privacy Protection Agency’s (CPPA’s) recently approved Cyber, Risk, ADMT, and Insurance Regulations – The CPPA’s most recently updated 127-page regulation package contains requirements governing cybersecurity audits, risk assessments, and automated decision-making technology. AI developers and systems that process personal information and meet certain California privacy thresholds will now face new cybersecurity audit and risk assessment requirements. In addition, automated and significant decisions concerning the provision or denial of financial or lending services, housing, education enrollment or opportunities, employment or independent contracting opportunities or compensation, or healthcare services will trigger significant notice, opt-out, and risk assessment requirements.
  • AB 2013: AI Training Data Transparency Act (Irwin-2024) – Passed last year, this law will require covered generative AI developers to publish online a high-level summary of the datasets used in the development of the generative AI system or service, including but not limited to whether personal information or copyrighted information is included in the training data. The law is scheduled to go into effect on January 1, 2026.

Children’s safety, age verifications, and companion chatbots

  • SB243: Companion Chatbots (Padilla) – This law applies to chatbots that provide human-like interactions and are capable of sustaining relationships across multiple interactions. Beginning July 1, 2027, developers of these ‘companion chatbots’ will need to develop and report protocols addressing suicidal ideation and self-harm to regulators and the public. The law requires AI disclosures, referrals to suicide hotlines or crisis text lines, and break reminders. SB 243 further requires developers to institute reasonable measures to prevent the chatbot from producing visual material of sexually explicit conduct or directly stating that the minor should engage in sexually explicit conduct. The legislation includes a private right of action to individuals who suffer ‘an injury in fact’ with statutory damages of $1,000 per violation, or actual damages if greater.
  • AB 1043 – Digital Age Assurance Act (Wicks) – Starting January 1, 2027, operating systems and covered application stores will be required to obtain age data from users and pass on age bracket data to developers when users download and launch an application.
  • AB 56: Social Media Warning Law (Bauer-Kahan) – Starting January 1, 2027, covered social media platforms will need to display a warning label to minors the first time a user accesses the platform each day, after three hours of active use, as well as once per hour of cumulative active use after that. The warning label must say ‘The Surgeon General has warned that while social media may have benefits for some young users, social media is associated with significant mental health harms and has not been proven safe for young users.’
  • AB 621: Deepfake pornography (Bauer-Kahan) – This amends California’s Civil Code and expands protections against deepfake pornography. The law explicitly provides a cause of action against individuals who create or disclose deepfake pornography if they know, or reasonably should know, that the depicted individual was a minor and also provides a cause of action against individuals who knowingly facilitate or recklessly aid or abet the creation or disclosure of such nonconsensual deepfake pornography. The bill confirms that a minor cannot consent to the creation or distribution of deepfake pornography.

California’s approach to AI and children has a long and complicated history, and these new laws should be read in conjunction with the following laws on the books.

  • California Age Appropriate Design Code (Wicks) – This law was signed on September 15, 2022, and was scheduled to go into effect on July 1, 2024. Modeled after the UK Age Appropriate Design Code, this law requires businesses to conduct impact assessments, provide Privacy by Default, estimate the age of all users, and restrict dark patterns. The law was enjoined in March 2025, but is being appealed by the California Attorney General.
  • Protecting Our Kids from Social Media Addiction Act (Skinner-2024) – This law is scheduled to go into effect on January 1, 2027, and prohibits covered social media platforms from providing addictive feeds to minors without verifiable parental consent. The law has so far escaped a constitutional challenge, but may face other court challenges prior to the effective date.

Healthcare AI and chatbots

  • AB 489: Health care professions: deceptive terms or letters: artificial intelligence (Bonta) – This law prohibits AI systems from falsely indicating or implying possession of a medical license or certificate through advertising, marketing, or other functionality. AB 489 also makes AI developers directly subject to the healthcare professional licensing board or enforcement agency if they develop such a system. Each use of a prohibited term, letter, or phrase shall constitute a separate violation.

California’s approach to AI in healthcare also needs to be read in conjunction with the following laws and guidance.

  • Legal Advisory on the Application of Existing California Law to Artificial Intelligence in Healthcare – In January 2025, California Attorney General Rob Bonta issued this advisory, setting forth California’s existing consumer protection, civil rights, competition, and data privacy laws governing healthcare AI.
  • SB 1120: Physicians Make Decisions Act (Becker-2024) – This law prohibits covered healthcare service plans from denying, delaying, or changing healthcare services based, in whole or in part, on medical necessity using AI, algorithms, or other software tools. Such determinations shall require a physician or licensed healthcare professional and review of individual circumstances. This law also requires written policies and procedures governing such determinations.
  • AB 3030: Artificial Intelligence in Health Care Services (Calderon – 2024) – This law applies to health facilities, clinics, physicians’ offices, or other health group practices that use generative AI for communications about patient clinical information. Under this bill, generative AI, which pertains to clinical information, must include:
    • a disclaimer that indicates the communication was generated by AI at the beginning of the interaction; and
    • clear instructions on how the patient can contact the appropriate person.

Antitrust and pricing discrimination

  • AB 325: Cartwright Act violations (Aguiar-Curry)  This amends California’s existing antitrust law, the Cartwright Act, to explicitly cover ‘common pricing algorithms.’ The law prohibits:
    • the use or distribution of a ‘common pricing algorithm’ as part of a contract, combination in the form of a trust, or conspiracy to restrain trade or commerce; or
    • coercion to set or adopt a recommended price or term, recommended by the common pricing algorithm for the same or similar products or services.

Complaints shall not be required to allege facts tending to exclude the possibility of independent action.

Law enforcement use of AI

  • SB 524 Law Enforcement Agencies (Arreguín) – SB 524 requires law enforcement to disclose if an official report was written either fully or in part using AI, as well as retain the first draft created by AI and an associated audit trail that, at minimum, identifies both the officer who used AI to create a report and the video and audio footage used to create a report, if any. SB 524 also prohibits AI vendors from sharing, selling, or otherwise using information, except as provided in the bill (e.g., troubleshooting, bias mitigation, quality control, legal purposes, etc.).

Employment and bias

While Governor Newsom vetoed SB 7, the No Robo Bosses Act, the Governor’s veto letter pointed to the CPPA’s ADMT regulations as addressing some of the bill’s requirements. Per Governor Newsom, SB 7 is ‘partially covered’ by these regulations, as they ‘allow employees and independent contractors to better understand how their personal data is used by automated decision technology.’ In addition, the California Civil Rights Council’s recently promulgated regulations state that California’s antidiscrimination laws apply to AI workplace tools. These regulations address another concern raised in SB 7, which sought to prohibit ADS systems from inferring a worker’s protected status.

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Image of a cellular phone with the ChatGPT app open.

Overview: The EU General-Purpose AI Code of Practice

Why Do We Need a Code of Practice?

On August 2, 2025, the general-purpose AI (GPAI) provisions of the EU AI Act went into effect. GPAI models (including models that support most generative AI, like ChatGPT), now face certain obligations in the EU, including requirements around transparency, copyright and systemic risk. However, the EU AI Act is a framework: it defines obligations but leaves technical details to harmonized standards and codes of practice. While this approach sets certain expectations and allows the EU AI Act to remain technology-neutral, it also leaves questions about how businesses substantially comply with the EU AI Act. To bridge this gap, a multi-stakeholder group drafted the General-Purpose AI Code of Practice (GPAI Code). On August 1, 2025, the European Commission issued a formal opinion confirming the GPAI Code is an “adequate tool” to help demonstrate compliance with the EU AI Act. Why is the Code significant? This opinion signals that organizations who adopt the GPAI Code may be able to demonstrate good-faith efforts to comply with the relevant provisions of the EU AI Act –  according to the Commission’s website: “The Code of Practice helps industry comply with the AI Act legal obligations…of general-purpose AI models.” In its opinion, the Commission notes that the Code provides actionable commitments and reporting mechanisms, especially for high-risk models. Additionally, the Commission emphasized that the Code provides a practical framework to demonstrate regulatory compliance. Following this endorsement, providers of GPAI models can voluntarily sign the Code, which “will reduce their administrative burden and give them more legal certainty than if they proved compliance through other methods.” Still, signatories should be aware that the Code explicitly states that adherence to the Code does not necessarily constitute evidence of compliance with the EU AI Act.

What is a General-Purpose AI Model?

A GPAI model is a component of an AI system with a wide range of possible uses, whether intentional or unintentional. It is important to note that these models are not systems in themselves but are part of AI systems. Additional elements, like user interfaces, are necessary to make these models fully operational systems. Under Article 3(63) of the EU AI Act, a GPAI model includes those trained on a “large amount of data using self-supervision at scale.”  They can be applied across sectors or tasks, usually without substantial modification, meaning GPAI models “can be integrated into a variety of downstream systems or applications.” Recital 98 of the EU AI Act states that the generality of the model can also be determined by the number of parameters, and “models with at least a billion parameters…should be considered to display significant generality and to competently perform a wide range of distinctive tasks.” GPAI models are sometimes called “foundation” or “frontier” models, and while they may include large language models (LLMs), they can also process audio, physical, textual or visual data, powering systems like DALL-E, GPT-4, Gemini, LaMDA, SEER, ALIGN, and more.

How are general-purpose AI models regulated?

Under the EU AI Act, the chapter on GPAI both addresses generative AI and outlines some of the most stringent requirements under the Act. However, all requirements for GPAI under the EU AI Act are directed to providers as opposed to deployers. Providers of GPAI models have a range of obligations under the EU AI act, both directly to supervising authorities and onward to AI providers who integrate the GPAI models into their systems. Obligations of Providers of GPAI Models If a provider places a GPAI model on the EU market, or integrates such a model into its own AI system on the EU market, it must:
  • Prepare and maintain technical documentation for regulators. This should include at least a general description of the GPAI model, including the tasks it’s designed to perform and the types of systems in which it can be integrated; acceptable use policies; and information on training process.
  • Prepare and maintain documentation for downstream providers. This should include information that allows the downstream AI system providers to comply with their own obligations under Article 53(1)(b). Similar to the technical documentation, this includes but is not limited to a general description of the model, and a description of its elements and development process.
  • Prepare an EU copyright policy. This policy should establish a means to comply with EU regulations on copyright and related rights.
  • Prepare and publish a summary of training content. Using the template provided by the AI Office, providers of GPAI must share a comprehensive summary of AI training information. This should allow stakeholders to exercise their rights by informing them of the information used to train the GPAI model.
  • Cooperate with relevant authorities and appoint an authorized representative. Providers must also cooperate with relevant authorities, and if they are established outside the EU, appoint an authorized representative located in the EU.
It is notable that under Recital 85, the EU AI Act states that GPAI systems “may be used as high-risk systems by themselves or be components of other high-risk systems.” Therefore, the providers of GPAI systems must work closely with providers of high-risk AI systems to ensure compliance with any requirements of high-risk systems under the Act. Obligations of Providers of GPAI Models with Systemic Risk What does “systemic risk” mean? GPAI models with systemic risk include models that reasonably pose foreseeable negative effects relating to major accidents, disruption of critical sectors, serious consequences to public health and safety, public and economic security, democratic processes, and the dissemination of false or discriminatory content, or other similar effect. Under Article 51(1) of the EU AI Act, a GPAI model will be classified as having systemic risk if:
  • It has high impact capabilities, or
  • It is designated by the Commission to have high impact capabilities based on the criteria in Annex XIII (i.e., the number of parameters in the model, the size of the data set, the amount of computation used to train the model, etc.).
What are the additional obligations for these models? In addition to the requirements for all GPAI models, those with systemic risk have additional obligations related to:
  • Model evaluation, assessment, and mitigation of systemic risks;
  • Incident management and reporting; and
  • Cybersecurity protections and technical documentation.
Because there are differences in the obligations between GPAI systems generally and GPAI systems with systemic risk, this classification procedure should be noted by providers of GPAI systems; it is essential to understand where each GPAI model falls, and what requirements the model has under the EU AI Act. According to Article 52(6), a list of GPAI models with systemic risk will be published and updated by the European Commission, but it has not been published at the time of writing.

What is the General-Purpose AI Code of Practice?

While not legally binding, providers of GPAI models can use the Code of Practice to demonstrate compliance with their obligations under the EU AI Act. The Code consists of three chapters on 1) transparency, 2) copyright, and 3) safety and security. The first two chapters apply to all providers of general-purpose AI models, providing a way to demonstrate compliance with obligations under Article 53 of the AI Act. The final chapter applies only to general-purpose AI models with systemic risk under Article 55 of the AI Act. Chapter 1: Transparency Among other things, this chapter requires signatories to create and maintain documentation for all GPAI models distributed within the EU for up to ten years. There are exceptions for models that are free, open-source, and do not pose systemic risk. When completing this documentation, signatories must use a standard Model Documentation Form, which includes information on licensing, technical specifications, training data, and other parameters of the GPAI model. The Code encourages publication of this information to promote transparency. Chapter 2: Copyright This chapter requires signatories to create and maintain a copyright policy that complies with the EU’s legal standards. This includes, but is not limited to, ensuring that data collected by web crawling is lawfully accessible, and certain websites flagged for copyright infringement are avoided. Importantly, signatories must designate a contact for copyright holders to submit complaints, along with a process for handling those complaints. Chapter 3: Safety & Security (GPAI with systemic risk only) One of the main elements of this chapter is the requirement for signatories to develop a state-of-the-art Safety and Security Framework before releasing any GPAI model categorized as posing a systemic risk. Additionally, systemic risks should be identified and inventoried, and before progressing with development or deployment, the signatories should weigh the relative risks and determine if they are acceptable, among other requirements.

What’s next?

The Code will be monitored and reviewed at regular intervals by the AI Office, and may be updated in response to emerging risks, technological developments, or incidents involving general-purpose AI models.
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CCPA Draft Regulations Sent for Final Approval

On July 24, 2025 the California Privacy Protection Agency (CCPA) board voted 5-0 to finalize Draft Regulations to the California Consumer Privacy Act (CCPA). The CPPA sent the rulemaking package to the Office of Administrative Law, which has 30 days to approve the regulations. The rulemaking process for these Draft Regulations began in 2022, and while the regulations have been narrowed since the prior proposal, the Draft Regulations will significantly impact how companies manage automated decisionmaking technology (ADMT), conduct risk assessments, and implement cybersecurity audits. Additionally, California’s regulatory process requires the CCPA to respond to public comments with their rationale for accepting or rejecting the suggestion. This requirement provides additional context and guidance for interpreting the intent of the Draft Regulations as they go into effect. What’s New? A Summary of Key Changes The Draft Regulations contain significant changes from the prior proposal – along with a 9-page explanation of changes. Most notably, the Draft Regulations roll back several of the most highly debated elements, while streamlining and clarifying other requirements:
  • References to “Artificial Intelligence” have been removed, significantly tightening the scope of ADMT systems.
  • First-party advertising removed from ADMT definition, narrowing the requirements needed for this type of processing.
  • Risk assessments are streamlined, and the scope of the types of data processing activities that trigger risk assessments has been narrowed.
  • Cybersecurity audits are clarified, and the CPPA included a “cybersecurity audit report” which should be produced during the audit process.

ADMT: Narrower Definition, Clearer Application

The Draft Regulations significantly narrow the scope of ADMT systems. Previously, ADMT systems included any technology that “substantially facilitated” human decisionmaking. Now, the Draft Regulations limits ADMT to systems which “substantially replace” human decisions. In practical terms, this may mean that only technologies which operate without human review or override fall under the ADMT rules. Importantly, the CPPA also removed first-party behavioral advertising from the definition of ADMT. Previously, businesses raised strong concerns that including this category within the ADMT definition would impose unnecessary burdens on common advertising practices. Businesses also voiced that including first-party behavioral advertising in the definition of ADMT went beyond Proposition 24, which provides the basis for amending the CCPA.

Risk Assessments: Who, What, and When?

While risk assessments remain a key part of the Draft Regulations, the CPPA has refined when they apply and what they must include. Who Needs to Conduct a Risk Assessment? Under the Draft Regulations, covered businesses that fall under the California Consumer Privacy Act (CCPA) “whose processing…presents significant risk to consumers’ privacy” must conduct a risk assessment. However, the newest version of the Regulations narrows what processing activities present “significant risk.” These activities include but are not limited to:
  • Selling or sharing personal information, which may require specific contractual obligations per the CCPA and current CCPA Regulations.
  • Processing sensitive personal information, as defined in the CCPA, including financial information, precise geolocation, health information and children’s personal information.
  • Using automated decisionmaking technology for a “significant decision” concerning a consumer, including those that impact availability of financial or lending services, housing, education enrollment or opportunities, employment or independent contracting opportunities or compensation, or healthcare services.
  • Using automated processing to profile a consumer through systematic observation when the individual is acting as an educational program application, job applicant, student, employee, or independent contractor for the covered business.
  • Using automated processing to profile a consumer based on their presence in a sensitive location, including healthcare facilities, domestic violence shelters, food pantries, housing/emergency shelters, educational institutions, political party offices, legal services offices, union offices, and places of worship.
  • Using personal information to train AI that could be used to make significant decisions concerning consumers, train facial- or emotional-recognition or other technology to verify a consumer’s identify or conducts physical or biological identification or profiling of a consumer.
While these risk assessments no longer apply to the previous expanded version of ADMT, they will apply to processing if the technology substantially replaces human decisionmaking for “significant decisions.” For example, if a covered business videotapes job interviews and uses AI to determine who to hire without human involvement, the covered business must conduct a risk assessment because of its use of ADMT for a significant decision concerning the consumer. What is Required for a Risk Assessment? As part of an effort to streamline and clarify the risk assessments required under the Draft Regulations, the CPPA defined a “risk assessment report” as the document that every covered business is required to create upon conducting the assessment. The CPPA provides a newly articulated goal for risk assessments: “[R]estricting or prohibiting the processing of personal information if the risks to privacy of the consumer outweigh the benefits resulting from processing to the consumer, the business, other stakeholders, and the public.” Additionally, the addition of the risk assessment report and changes in requirements may ease compliance efforts. To complete a risk assessment, a covered business should document, among other things:
  • The purpose of processing, the types of data involved, and any sensitive categories of personal information.
  • How the business plans to use the data, or otherwise collect, disclose or process the information, along with the retention period for the information.
  • How the business interacts with consumers, and whose data they process, along with the number of consumers whose information will be processed.
  • The disclosures made to consumers, and any other disclosures that the covered business plans to make, along with the names of service provides, contractors, or third parties to whom the information will be disclosed and the purpose for that disclosure.
  • The benefits, negative impacts, and safeguards of the planned processing.
  • Whether or not the business will initiate the processing subject to the risk assessment.
  • The individuals who provided information, as well as who the document was reviewed and approved by.
  If a covered business is using ADMT, the business must also identify:
  • The logic of the ADMT, including any assumptions or limitations of the logic; and
  • The output of the ADMT and how the covered business will use that output to make a significant decision.
The CPPA also clarifies that the risk assessment process may include involvement by external parties. Finally, a covered business must submit the following risk assessment information, among other things, to the Agency:
  • The business’s contact information, the information of the person submitting the assessment, and the date of certification.
  • The time period covered by the submission, and the number of risk assessments conducted or updated during that time.
  • Whether the risk assessments involved the processing of each of the categories of personal information identified in the CCPA.
  • A specific attestation, which certifies the business conducted a risk assessment for the processing activities involving significant decisions, subject to the penalty or perjury.
The individual submitting the information to the Agency must be a member of the covered business’s executive management team who is: 1) directly responsible for the business’s risk assessment compliance; 2) has sufficient knowledge to provide accurate information regarding the assessment; and 3) has the authority to submit the assessment information to the Agency. In addition, the Agency or Attorney General may require a covered business to submit its risk assessment reports at any time, within 30 days of the request. When Should Risk Assessments Be Conducted? According to the Proposed Rules, a covered business must conduct and document a risk assessment before beginning any processing activities that present a significant risk to consumers’ privacy. At least once every three years, the covered business must review and update their assessment. The covered business must also update a risk assessment whenever there is a material change relating to the processing activity, no later than 45 days from the material change. The covered business must retain its risk assessments – including original and updated versions – for as long as the processing continues or for five years after the completion of the risk assessment, whichever is later. What if I Have Already Conducted A Risk Assessment? There have been significant changes to the Draft Regulations regarding how covered businesses can use comparable assessments to satisfy the risk assessment criteria. New additions provide that a covered business may use a risk assessment that it has prepared for another purpose, provided that the assessment contains or is paired with all the required information to meet the Proposed Regulation’s requirements.

Cybersecurity Audits: Who, What, and When?

Among the added definitions is the “cybersecurity audit report” – the document that covered businesses must create as part of the cybersecurity audit. Similar to changes regarding risk assessments, this inclusion was part of the streamlining and clarification efforts of the CPPA. The scope and requirements of the cybersecurity audit – and the resulting audit report – have also been modified. Who Needs to Complete a Cybersecurity Audit? According to the Draft Regulations, every covered business whose processing of information presents a “significant risk” to consumers’ security must complete a security audit. While this language is similar to the requirements of the risk assessment, “significant risk” is defined slightly differently in the context of a cybersecurity audit. According to the Draft Regulations, a “significant risk” that warrants a cybersecurity audit includes but is not limited to covered businesses which:
  1. Derive 50% of more of its annual revenue from selling or sharing consumer’s personal information; or
  2. Had a gross annual revenue of $25M in the preceding calendar year (adjusted for inflation), and
    1. Processed the information of 250,000 or more consumers or households in the last year; or
    2. Processed the sensitive information of 50,000 or more consumers in the last year.
Covered businesses that are required to complete a cybersecurity audit must do so using a “qualified, objective, independent processional (‘auditor’) using procedures and standards accepted in the profession of auditing.” This audit may be internal or external to the covered business, but a qualified auditor must have knowledge of cybersecurity and know how to audit a business’s cybersecurity program, according to the changes in the Draft Regulations. What Should the Cybersecurity Audit Assess? Initially, the cybersecurity audit must assess how the covered business’s cybersecurity program protects personal information against unauthorized access, destruction, use, modification and disclosure, as well as how the program protects against unauthorized activity resulting in the loss of availability to that information. The cybersecurity audit must also assess the strength of a covered business’s cybersecurity program across such as, but not limited to:
  • Authentication and encryption;
  • Access control and account management;
  • Software and hardware inventories;
  • Patch and configuration management;
  • Network security, antivirus, and antimalware;
  • Incident response and business continuity;
  • Vendor oversight;
  • Data retention and disposal; and
  • Employee and contractor training.
The covered business’s auditor must also create a detailed cybersecurity audit report, documenting:
  • What was assessed and why. The report should describe the processes, activities, and components of the business’s cybersecurity program, the criteria used for the audit, along with the specific evidence examined to make decisions and assessments.
  • Evidence reviewed. The report must also include why these elements were appropriate for the audit, and how the evidence examined supports the findings.
  • Gaps or weaknesses found. The report should describe, in detail, the status of any gaps or weaknesses and any additional components that the auditor deemed to increase the risk of unauthorized activity. The report should also document the business’s plan to address these gaps and/or weaknesses.
  • Auditor information and certification. The report should also include the auditor’s information, as well as a statement by the highest-ranking auditor that certifies that they completed an independent review of the business’s cybersecurity program and information system, exercised objective and impartial judgement on all issues within the scope of the audit and did not rely primarily on assertations or attestations by business management to create the audit.
When Should Cybersecurity Audits Be Conducted? The final determination of when a covered business must conduct their first cybersecurity audit is based on the business’s annual gross revenue. If a business meets the audit thresholds, it may be time to start thinking about a compliance plan. First audit reports will be due:
  • April 1, 2028, for covered businesses with over $100 million in gross annual revenue;
  • April 1, 2029, for covered businesses with $50 million to $100 million in gross annual revenue; and
  • April 1, 2030, for covered businesses with under $50 million in revenue.
Each audit must cover the previous calendar year from January to January, with reports completed within the following three months. What if I Have Already Conducted A Cybersecurity Audit? As with the risk assessment, a covered business may use a cybersecurity audit, assessment, or evaluation that it has prepared for another purpose – provided that the audit meets all the requirements of the Draft Regulations, on its own or through supplemental information. The Draft Regulations provide, as an example, that a covered business may use the NIST Cybersecurity Framework 2.0 “and meets all the requirements of this Article.”

What Comes Next?

On July 24, 2025, the CPPA sent the rulemaking package to the Office of Administrative Law, which has 30 days to approve the regulations. The CPPA’s Draft Regulations signal a more measured approach to emerging technologies, such as AI. Still, these Draft Regulations carry out the CPPA’s mandate to issue regulations, reinforcing the agency’s commitment to privacy and security. For executives, the potential adoption of the Draft Regulations could be a strategic inflection point: Whether they are responsible for legal, compliance, data governance or information security, these Draft Regulations should prompt a reassessment of data practices, internal documentation and audit readiness. The publication of these Draft Regulations is also an opportunity to engage more deeply with operational teams. These rules will require clear cross-functional coordination, and organizations that begin building these bridges sooner will be better positioned to meet regulatory expectations and reinforce consumer trust in coming years. Compliance Deadlines: Compliance with these Draft Regulations will be required once they are approved by the Office of Administrative Law. The deadlines include:
  • ADMT Regulations: January 1, 2027
  • Privacy Risk Assessments: December 31, 2027
  • Cybersecurity Audits:
    • For businesses with $100+ million in annual gross revenue: April 1, 2028.
    • For businesses between $50 million and $100 million in annual gross revenue: April 1, 2029.
    • For businesses with less than $50 million in annual gross revenue: April 1, 2030.
 
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Image of a computer circuit board with "AI" written on one of the chips.

AI Updates: An Overview of the Legal Landscape

As AI continues to advance, so do regulatory efforts. During the 2024 legislative session, 45 states along with Puerto Rico, the Virgin Islands, and Washington D.C. all introduced AI bills. With the legislative session for 2025 wrapping up, we are seeing similar tends this year. As new legal requirements emerge, organizations across the U.S. and EU may face overlapping – yet not identical – regulations that touch on issues of bias, safety, privacy, and transparency. Additionally, these laws may categorize the same AI system differently in different jurisdictions, requiring a nuanced approach to navigating these laws. Keeping this in mind, this article provides a brief overview of a handful of these laws. The practical takeaway? Businesses operating in the U.S. or EU should be aware of their legal requirements. Additionally, these organizations may want to consider a programmatic, auditable, and documented approach to AI governance, which may allow the business to map their AI controls to multiple legal frameworks.

Converging Themes

While details of AI laws differ across jurisdictions, trends seem to be converging on risk-based classification, transparency requirements, and enforcement efforts. Regulators are moving toward risk-based classification. This means AI uses are categorized according to their use case (and the risk associated with that use case). As seen in the EU AI Act, the Colorado AI Act, and TRAIGA, systems may be prohibited or classified by risk. High-risk systems tend to have stricter governance, testing and documentation requirements. Another shared theme is transparency. Laws including the EU AI Act, Colorado AI Act, Utah AI Policy Act, may require covered entities to tell people when AI is in use, while other laws may require the developer or deployer to explain the logic behind certain outputs, and provide consumers with a methods of contesting certain decisions, or opt out of certain types of decisionmaking entirely. The California AI Transparency Act and the EU AI Act may also require labeling of certain AI-generated content. Finally, enforcement is sharpening. The EU AI Act comes with regulatory teeth, with fines of the higher of €35,000,000 or 7% global annual turnover for violation of prohibited practices. In the U.S., state attorneys general and regulators have been active in monitoring AI missteps, including consumer protection and privacy violations. For example, attorneys general in Massachusetts and Oregon have issued advisories on how consumer protection laws apply to AI, while Texas Attorney General Ken Paxton reached the first-of-its-kind settlement in a healthcare generative AI investigation.

The European Union Artificial Intelligence Act (EU AI Act)  

Overview: The EU AI Act is the world’s first comprehensive AI regulation and sets a high-water mark for governance expectations. The Act is technology neutral and uses risk-based classification to sort AI systems into risk-tiers, each with escalating obligations. Key Provisions:
  • Prohibited systems include cognitive behavioral manipulation, most real-time biometric identification, and systems used for social scoring. These systems are considered to pose an unacceptable risk to safety or fundamental rights.
  • High-risk systems include hiring tools, biometric identification, and critical safety technology. They must undergo conformity assessments, maintain technical documentation, and ensure human oversight.
  • Limited-risk systemsinclude chatbots, deepfake generators, and public facing generative AI. These systems have transparency obligations to ensure users understand they are interacting with AI.
  • Minimal-risk systems include AI-enabled spam filers, grammar checkers, and basic AI in video games. These systems have no specific obligations under the Act, but best practices are encouraged.
Key Dates & Enforcement:
  • February 2, 2025: Prohibitions on certain AI systems and requirements on AI literacy start to apply.
  • August 2, 2025: Rules on general practice AI models, governance, confidentiality, and penalties start to apply.
  • August 2, 2026: The remainder of the AI Act (except for Article 6(1)) applies.
The Act will be enforced by European AI Office and national market surveillance authorities. Non-compliance with the prohibition of AI practices is subject to an administrative fine of up to €35,000,000 or up to 7% worldwide annual turnover, whichever is higher. Non-compliance with other provisions shall be subject to administrative fines of up to €15,000,000 of up to 3% of its total worldwide annual turnover, whichever is higher.

Colorado: Consumer Protections for Artificial Intelligence Act (CO AI Act)

Overview: Enacted in May 2024, the CO AI Act was the first far-reaching AI law in the United States. This Act primarily focuses on high-risk AI systems, including but not limited to those which influence “consequential decisions” – those impacting areas such as employment, education, housing, healthcare, finance, insurance, legal services, and essential government services. Key Provisions: Developer and deployers must both exercise “reasonable care” to protect consumers from known or reasonably foreseeable risks of algorithmic discrimination. For both, this may include providing notice to the Colorado Attorney General within 90 days of becoming aware of new discrimination risks.
  • Developers. There is a rebuttable presumption that the developer used reasonable care if they disclose, among other things:
    • reasonably foreseeable uses and known inappropriate or harmful uses of the AI system (including of algorithmic discrimination) and the measures taken to mitigate them;
    • the intended purpose, benefits, uses and outputs of the AI system; and
    • high-level summaries of the data types used to train the AI system, including data governance measures.
  • Deployers must also exercise reasonable care to protect consumers from any known or reasonably foreseeable risks of algorithmic discrimination. Similarly, there is a rebuttable presumption that the deployer used reasonable care if they complete the following, among other things:
    • a risk-management program that considers the NIST AI Risk Management Framework (AI RMF) or another similarly recognized risk management framework with substantially similar requirements (for more information about conducting an AI Risk Assessment, you can check out our post here);
    • an impact assessment, that includes the purpose, use cases, deployment context, and an analysis of whether it poses any foreseeable risks of discrimination, along with steps taken to mitigate those risks;
    • notice to consumers when certain systems are being used that include the system purpose, contact information, and options to opt-out of AI processing for that purpose, correct personal information used in the decisionmaking process, and appeal the decisionmaking process.
  • Disclosure should be clear. Regardless of risk level, any AI system that is directly interacting with Colorado consumers must disclose that it is an AI system, unless that would be obvious to a reasonable person.
Key Dates & Enforcement: While this law was originally set to take effect in 2026, Colorado Governor Polis called a special legislative session to address budget issues, taking place on August 21. The impact of SB24-05 (Consumer Protections for AI) is on the agenda, which may result in a delayed enforcement deadline and substantive changes to the law’s provisions. Violations are treated as deceptive trade practices under Colorado’s Consumer Protection Act, subject to enforcement by the Colorado Attorney General and penalties of up to $20,000 per violation.

Texas Responsible AI Governance Act (TRAIGA)

Overview: While TRAIGA originally provided a comprehensive AI framework, the final version has been significantly pared down. With narrow substantive provisions, TRAIGA focuses on harms caused by AI, and the Act regulates – or completely bans – certain uses of these systems. TRAIGA applies broadly to private sector companies if they provide AI-generated content or services to Texas residents, even if they are located outside the state of Texas. Additionally, government agencies interacting with the public fall squarely within the scope of the Act. You can read more about TRAIGA at our blog post covering the Act here. Key Provisions:
  • Prohibited AI For Public and Private Sectors include but are not limited to intentionally inciting self-harm, violence or crime; infringing on an individual’s rights; or unlawfully discriminating (with purposeful intent). The Act also prohibits deploying AI systems that intentionally generate illegal content, as well as child sexual abuse material or sexually explicit chat systems that impersonate children.
  • Prohibited AI uses for the Public Sector include but are not limited to social scoring and uniquely identifying individuals with biometric data (with limited exceptions).
  • Transparency Requirements for Public Sector may require governmental agencies to, among other things, provide conspicuous notice to consumers that they are acting with an AI system.
Key Dates & Enforcement:   TRAIGA was signed into law in June 2025 and takes effect on January 1, 2026. With no private right of action, the Act can only be enforced by the Texas Attorney General. The Act requires the Attorney General to create an “online mechanism” on their website where consumers can submit complaints of potential violations. If the Attorney General determines a violation has occurred, there is a 60-day cure period. If the violation continues after this period, the Attorney General may bring a claim for, among other things:
  • an injunction;
  • a civil penalty for curable breaches between $10,000 and $12,000;
  • a civil penalty for uncurable breaches between $80,000 and $200,000; and
  • a civil penalty for each day of continued violation between $2,000 and $40,000.
 

California CCPA Draft Regulations

Overview: On July 24, 2025, the California Privacy Protection Agency (CCPA) board voted 5-0 to finalize Draft Regulations to the California Consumer Privacy Act (CCPA). The CPPA sent the rulemaking package to the Office of Administrative Law, which has 30 days to approve the regulations. For a deeper dive on the CCPA Draft Regulations, please see our post here. Key Provisions:
  • Automated-decisionmaking (ADMT): Businesses must inform consumers with a pre-use notice and provide opt-out rights when AI or automated tools influence “significant decisions,” including those about employment, education, housing, healthcare, financial or lending services, and similar areas.
  • Risk Assessments: Organizations engaging in high-risk data processing (such as the decisions covered in ADMT, above) must conduct risk assessments before beginning processing, and must update them regularly, including within 45 days of any material change of the system. For more information about conducting an AI Risk Assessment, you can check out our post here.
  • Cybersecurity Audits: Businesses meeting certain thresholds must undergo annual, evidence-based audits carried out by a “qualified, objective, independent professional.” The audits must rely on specific evidence (as opposed to assertions by the business management), and all information related to the audit should be kept for a minimum of five years after completion.
Key Dates & Enforcement: Compliance with these Draft Regulations will be required once they are approved by the Office of Administrative Law. The deadlines include:
  • ADMT Regulations: January 1, 2027
  • Privacy Risk Assessments: December 31, 2027
  • Cybersecurity Audits:
    • For businesses with $100+ million in annual gross revenue: April 1, 2028.
    • For businesses between $50 million and $100 million in annual gross revenue: April 1, 2029.
    • For businesses with less than $50 million in annual gross revenue: April 1, 2030.

Other Laws to Consider

Along with the more far-reaching laws provided above, there are additional laws that businesses may want to consider when building, implementing, or otherwise engaging with AI tools or systems.
  • Utah’s Artificial Intelligence Policy Act
    • Effective as of May 2024, this Act mandates certain disclosures when businesses use generative AI to interact with consumers. This applies specifically to “regulated professions,” where the provider shall make the disclosure prominently, regardless of whether it is obvious the person is interacting with an AI system or not.
  • New York City’s Local Law 144 (and other AI employment regulations)
    • Signed in 2021, this law applies to employers and employment agencies in New York City that use “automated employment decision tools” to screen candidates or employees. It requires that an independent bias audit be conducted within one year of using the AI tools. For more information on AI in employment, see our article on AI In the Workplace: Legal Considerations for Leadership Teams.
  • California’s AI Transparency Law (SB 942)
    • Effective January 1, 2026, this law applies to “covered providers” – those offering generative AI systems with over 1 million monthly users in California. These providers must provide: 1) a free, public AI detection tool; and 2) certain disclosures as a label or embedded within their content.
  • California’s Data Transparency Law (AB 2013)
    • Effective January 1, 2026, developers of generative AI systems must post a disclosure on their website including documentation used to train the AI system. This documentation includes high-level summary of datasets used in the development of the AI system – the sources or owners of the datasets, how they further the purpose of the AI system, the number of datapoints in the datasets, and more.

Key Takeaway

As lawmakers race to keep up with the breakneck speed of AI implementation, guidance is quickly becoming enforcement. While specific requirements between these laws vary, the common thread is clear: covered entities are expected to understand, document, and justify their AI systems’ design, data, and impact. Additionally, organizations utilizing AI should consider building responsible AI governance into their operations. By incorporating these governance processes into everyday systems and – similar to those for privacy and cybersecurity – organizations may proactively protect against legal, ethical and operational risk when implementing AI.
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