Healthcare AI Legislative Sessions

This act regulates the use of autonomous AI providers in clinical settings, requiring specific disclosures when patients are receiving care from an AI system without routine human clinical oversight. It mandates that operators post a surety bond and provides a framework for human review of AI-driven clinical decisions.

This act establishes requirements for the use of AI systems in utilization review by health insurers and related entities. It prohibits public and private payers from covering psychotherapy services conducted by AI and prohibits mental health providers from billing for such services.

This bill directs the Secretary of Health and Human Services to conduct a comprehensive study on the application of artificial intelligence technologies across the healthcare industry. The study aims to identify strategies to improve administrative and clerical processes while ensuring compliance with HIPAA and addressing cybersecurity threats.

This bill would have regulated the use of artificial intelligence and algorithms by health insurance issuers for utilization review and management. It aimed to ensure that AI-driven determinations were based on individual medical history and clinical circumstances rather than solely on group datasets, and prohibited AI from replacing human healthcare provider decision-making.

This resolution expresses congressional opposition to the use of AI by CMS for determining Medicare coverage. It serves as a formal warning against the automation of coverage decisions that could impact senior access to care.

This bill proposes that AI or machine learning technology may qualify as a prescribing practitioner for drugs, provided the technology is authorized by state law and approved under federal medical device regulations. It creates a legal framework for AI-driven prescription authority.

Amends the Social Security Act to ensure appropriate Medicare payment for algorithm-based healthcare services. It establishes a 'new technology ambulatory payment classification' for FDA-cleared devices using AI/ML, setting reimbursement based on actual cost data submitted by manufacturers for at least two years.

This bill would have established transparency requirements for health insurers and utilization review entities using AI in medical decision-making. It mandated that all medical necessity determinations be performed by a licensed physician or healthcare professional.

The bill establishes a grant program under the Department of Health and Human Services to facilitate research into the use of generative artificial intelligence in healthcare. It focuses on advancing the safe and effective integration of AI tools within clinical settings.

This act establishes that the use of artificial intelligence to provide patient advice or treatment without human practitioner interaction does not qualify as a regulated scope-of-practice innovation. It ensures that AI cannot replace the professional judgment of a licensed healthcare provider in clinical settings.

This bill restricts health insurers from using AI as the sole basis for denying, delaying, or modifying medical care decisions. It mandates that a licensed human physician must make final coverage determinations, ensuring human oversight in utilization review processes.

This bill would have prohibited health insurers and self-insured government plans from solely relying on artificial intelligence or automated decision tools to deny, modify, or reduce prior authorization requests. It required that any such denial be reviewed by a licensed health care professional.

This act establishes safety and transparency protocols for conversational AI services, including mandatory disclosures for minors and requirements for handling user prompts regarding suicidal ideation. It explicitly prohibits operators from programming AI to claim it provides professional mental or behavioral healthcare.

This act restricts the use of AI in psychotherapy, prohibiting AI from interacting with clients in therapeutic communication without real-time human professional oversight. It mandates informed consent and disclosure requirements for any AI-assisted recording or transcription of therapeutic sessions.

This bill mandates an independent evaluation of AI systems deployed by the Veterans Health Administration. It requires assessment of system outputs, data privacy, model integrity, and compliance with federal health information laws to mitigate bias and ensure patient safety.

This bill amends the Public Health Service Act to mandate education and training for medical students, residents, and faculty regarding the deployment of artificial intelligence in the medical profession. It aims to ensure the healthcare workforce is prepared for AI-integrated clinical environments.

This act imposes restrictions on the use of artificial intelligence systems by licensed providers of mental and behavioral health care. It requires that any use of AI by these providers must comply with federal and state laws governing patient privacy and the security of electronic health records.

This bill modifies the duties of the Office of Artificial Intelligence Policy and updates the Artificial Intelligence Learning Laboratory Program. It impacts how the state regulates AI, including potential applications in healthcare and other sectors under regulatory agreements.

This legislation requires covered providers to include specific disclosures in AI-generated content and mandates provenance data for distributed content. It establishes enforcement mechanisms through the Division of Consumer Protection for AI-related disclosures.

This bill would have established the AI Medical Services Act, creating an 11-member board to oversee the use of artificial intelligence in medical services. It aimed to regulate AI applications within clinical settings, though the bill failed to progress.

This law prohibits AI providers from making representations that an AI system is capable of providing professional mental or behavioral healthcare. It also restricts mental and behavioral healthcare professionals from using AI systems to perform specific functions related to the mental health of pupils.

This law establishes requirements for developers and deployers of automated decision-making technology (ADMT) used in consequential decisions, including health care services. It mandates risk management and transparency, with enforcement by the Attorney General starting in 2027.

This bill would have established the Kansas Community Harmed by AI Technology (CHAT) Act, requiring operators of companion AI chatbots to implement age verification, parental consent for minors, and monitoring for suicidal ideation. It mandated compliance guidance by 2027 and provided a safe harbor for entities that met specific consumer protection standards.

HB 286 mandates that AI developers and suppliers publish safety plans and provide transparency regarding the data and algorithms used in patient-facing chatbots. It includes specific provisions to prevent AI from engaging in inappropriate or harmful clinical-style interactions with minors, requiring proactive labeling and safety guardrails [When the AI chatbot becomes a suicide counselor](https://www.deseret.com/politics/2026/01/22/utah-legislature-supports-bill-to-force-ai-chatbots-to-care-about-kids-it-might-conflict-with-trump-executive-order-on-state-ai-regulations/).

This bill prohibits the training of AI systems to act as licensed mental health or healthcare professionals or to provide emotional support. It establishes civil liability for entities that develop AI models that simulate human relationships or provide unauthorized healthcare information.

This bill prohibits the Secretary of Health and Human Services from implementing the WISeR model or any substantially similar model that uses artificial intelligence for prior authorization in traditional Medicare. It amends the Social Security Act to explicitly bar the use of AI in future CMI models for prior authorization of items or services under Medicare Part A or B.

This bill regulates AI companies and includes provisions prohibiting insurers from using health data to train AI systems without obtaining affirmative, voluntary consent from the insured. It establishes oversight by the Bureau of Consumer Protection regarding AI-driven data practices.

This law prohibits the use of AI platforms from countries of concern (such as DeepSeek) on any state network or device. Critically for the healthcare sector, it bans medical and research facilities from using genetic sequencers or operational software for genetic analysis produced by foreign adversaries. This restricts the technology stack available for genomic research and AI-driven clinical analysis in Kansas laboratories and state-affiliated hospitals.

This law regulates conversational AI operators, requiring suicide prevention protocols and prohibiting the false representation of AI services as licensed health care, mental health, or dietary professionals. It includes specific protections for minors, including data privacy and measures to prevent emotional dependence.

This law establishes requirements for the use of AI systems in health care utilization review, mandating oversight and disclosures to state agencies. It also prohibits public and private payers from covering psychotherapy services conducted by AI and prevents mental health providers from billing for such AI-conducted services.

This bill regulates the use of artificial intelligence in the review of claims by group health plans and health insurance issuers. It amends the Public Health Service Act, ERISA, and the Internal Revenue Code to establish oversight for AI-driven claims processing.

This bill prohibits government entities from using artificial intelligence to calculate and assign social scores or to identify persons using biometric data. It provides specific exceptions and definitions, though it explicitly excludes certain healthcare-related entities such as community hospital districts from the definition of a governmental entity.

The Conversational AI Safety Act requires operators of public-facing conversational AI services to disclose when users are interacting with AI rather than a human. It also mandates that these services implement protocols to provide crisis resources, such as suicide hotlines, when a user prompts the system with suicidal ideation.

This law restricts mental health professionals from allowing AI to engage in therapeutic communication without synchronous human interaction or generating treatment recommendations without professional review. It requires written informed consent when AI is used to record or transcribe therapeutic sessions.

This bill amends the operations of the Office of Artificial Intelligence Policy, which oversees the regulatory sandbox for AI technologies. It facilitates the integration of clinical AI pilots and provides the framework for the Healthcare AI Advisory Network to review healthcare-related AI proposals.

This bill requires medical facilities and healthcare providers to include specific disclosures when using generative AI to create patient communications. It mandates that such communications provide clear instructions on how a patient can contact a human provider for assistance, unless the communication is reviewed by a provider before being sent.

This law regulates the use of automated decision-making technology (ADMT) in consequential domains, including health care services. It requires deployers to provide notice to consumers, allow for the correction of inaccurate data, and provide a process for requesting human review of adverse outcomes.

This bill proposes to make it unlawful to train AI models to perform specific functions, including acting as a healthcare professional or simulating clinical care. It targets the development of AI systems that could potentially replace or mimic human healthcare providers.

This bill mandates transparency requirements for entities utilizing artificial intelligence in professional and consumer-facing services. It requires clear disclosure to individuals when they are interacting with an AI system rather than a human, specifically impacting healthcare providers and administrative entities.

This bill seeks to restrict the use of artificial intelligence in the prior authorization process for health insurance, mirroring the intent of SB 128. It requires health insurers to ensure that coverage denial decisions are not solely determined by automated AI systems.

This law requires health insurers to disclose the use of artificial intelligence in their operations to the Utah Insurance Department. It aims to increase transparency in how AI-driven automated systems are utilized within the health insurance sector.

This legislation amends the governance of the Office of Artificial Intelligence Policy, which oversees regulatory sandboxes for AI deployment. It impacts healthcare entities participating in these sandboxes by establishing compliance frameworks for AI-driven clinical and administrative tools.

This bill would have required healthcare providers and medical facilities to include specific disclosures when using generative AI to produce patient communications. It aimed to ensure transparency regarding the use of automated systems in clinical correspondence.

This legislation establishes limitations on the use of artificial intelligence systems by state government agencies. It requires state entities to implement risk management policies when deploying automated systems, which impacts how government-run healthcare programs and health IT infrastructure must manage AI-driven decision-making.

Proposed a comprehensive regulatory framework for 'AI-augmented and autonomous service providers' (AAASPs), creating a state Board of Autonomous Medical Practice to license and audit AI systems used in medical diagnosis, treatment, and triage. The bill included requirements for a regulatory sandbox, liability waivers for certain AI clinical services, and mandates for 'clinical logic snapshots' to ensure auditability of AI decisions.

This bill enacts the Companion Chatbot Safety Act and establishes specific disclosure and data protection requirements for operators of AI chatbots. It explicitly includes provisions related to artificial intelligence applications in mental health care settings.

This legislation seeks to restrict health carriers from relying on AI-driven automated systems to issue denials for prior authorization requests. It requires that health plans maintain human-in-the-loop processes for coverage determinations to prevent algorithmic bias or errors in clinical care access.

This draft legislation requires governmental entities to ensure meaningful human review for any consequential decisions made using automated decision-making systems. It mandates that entities maintain records of the natural persons responsible for such reviews, with an effective date of July 1, 2027. The committee is currently considering expanding the scope to explicitly include healthcare decisions within the definition of consequential decisions.

This act requires health insurance carriers, pharmacy benefit managers, and utilization review organizations to ensure that any AI system used for utilization review complies with specific algorithmic transparency and equity requirements. It mandates that these entities implement oversight mechanisms to prevent discriminatory coverage denials.

This legislation mandates that Local Education Agencies (LEAs) adopt balanced technology and artificial intelligence use policies for classrooms. It requires the Utah State Board of Education to create model AI policies, including safeguards for student privacy and restrictions on using generative AI for high-stakes grading or determinations.

SB 128 restricts health insurers and health plans from utilizing or relying on artificial intelligence systems or automated decision tools to deny prior authorization requests or reduce covered health services. Payors and insurers must ensure qualified clinical personnel make adverse coverage determinations rather than automated algorithms. Compliance applies to health plans and insurers operating within Nevada.

This act prohibits the use of specific foreign-controlled AI platforms on state-owned devices and networks. It also restricts the use of foreign-produced genetic sequencers and associated software for genetic analysis, impacting state-funded healthcare and research entities.

This bill enacts the Companion Chatbot Safety Act and establishes specific regulatory frameworks for artificial intelligence applications in mental health. It mandates disclosure and data protection requirements for operators of AI systems interacting with patients in healthcare settings.

This bill addresses the integration of artificial intelligence within the healthcare sector to ensure patient safety and data integrity. It mandates oversight for AI-driven clinical tools and requires healthcare providers to disclose the use of automated systems in patient care.

This bill establishes requirements for state procurement processes to ensure that artificial intelligence systems used by state agencies are free from bias. It mandates that vendors providing AI solutions to the state must demonstrate compliance with non-discrimination and transparency standards.

This act requires the Idaho State Department of Education to develop a statewide generative AI framework for K-12 schools and mandates that local school districts adopt policies governing AI use. It requires vendors to disclose the use of machine learning or generative AI in procured tools and mandates compliance with federal data privacy laws like FERPA and COPPA by July 1, 2026.

Amends the Federal Food, Drug, and Cosmetic Act to clarify that artificial intelligence and machine learning technologies can qualify as a practitioner eligible to prescribe drugs. The bill requires that such AI systems be authorized by the State and approved, cleared, or authorized by the FDA.

This law requires health insurers to disclose to the Utah Insurance Department the use of artificial intelligence in making authorization or adverse preauthorization determinations. It establishes transparency requirements for insurers utilizing automated decision systems in utilization review processes.

The Healthcare Education in AI Literacy Act focuses on improving AI literacy within the healthcare workforce. It seeks to ensure that healthcare professionals are equipped to understand and utilize AI tools effectively in clinical settings.

This act creates criminal offenses related to the use of artificial intelligence to generate or possess child pornography. It also establishes liability limitations for AI developers, except in cases where the system was developed with the intent to facilitate illegal activities.

This bill establishes consumer protections for AI applications, specifically targeting mental health services and health spa interactions. It requires clear disclosures when a consumer is interacting with generative AI and sets safety standards for AI applications that provide behavioral health support to prevent self-harm and ensure professional oversight [HB 438 Artificial Intelligence Amendments - Utah Legislature](https://le.utah.gov/Session/2026/bills/static/HB0438.html).

This bill aims to regulate the use of AI-powered chatbots in healthcare and consumer services to protect senior citizens from misinformation and fraud. It mandates transparency and safety standards for chatbots interacting with vulnerable populations.

This bill requires the Secretary of Health and Human Services to conduct a comprehensive study on strategies for the application of artificial intelligence to improve efficiency in the healthcare system. It focuses on identifying best practices for AI deployment in clinical and administrative workflows.

This comprehensive act establishes a regulatory framework for AI use across the state, including minimum standards for AI in public services. Notably, it addresses Medicaid reimbursement for school-based health services that utilize artificial intelligence, ensuring that such tools meet state safety and efficacy standards.

This bill establishes a framework for research funding to leverage artificial intelligence technologies to address critical challenges in the healthcare sector. It defines key terms such as generative AI and aims to promote the integration of AI in medical research and development.

Establishes guardrails for prior authorization, requiring that adverse determinations must be made by a licensed physician in the same or similar specialty. While not using the term AI in the title, it effectively prohibits fully automated or autonomous AI-driven denials by mandating human-in-the-loop clinical peer review for chronic condition treatments.

Also known as the Chatbot Safety Act, this law requires operators of conversational AI to disclose to users when they are interacting with a non-human system. For healthcare providers, this applies to patient-facing triage bots and administrative portals, requiring clear labeling to prevent patient confusion.

This act expands the Montana Genetic Information Privacy Act to include 'neurotechnology data' generated by brain or nervous system activity and processed by devices. It requires entities to provide clear privacy notices, obtain express consent before collection or disclosure, and explicitly prohibits the sharing of such data with health or life insurers without the consumer's express permission.

Subjects 'mental health digital service' platforms, including mobile apps and websites that use automated systems to facilitate diagnosis and suggested therapies, to the Montana Uniform Health Care Information Act. This mandates that AI-driven mental health platforms comply with state-level healthcare privacy and confidentiality standards previously reserved for licensed practitioners.

Establishes a fundamental right to use computational resources but requires deployers of 'critical artificial intelligence systems' that control critical infrastructure to develop and maintain a risk management policy. These policies must align with recognized standards such as the NIST AI Risk Management Framework (RMF) or ISO/IEC 42001, impacting hospitals and major health facilities classified as critical infrastructure.

This bill establishes a task force to study the impacts and risks of AI and emerging technologies. Legislative testimony confirmed that the scope includes the healthcare sector to address specific clinical and operational AI risks.

Regulates AI chatbots used by minors, requiring safe design features and disclosure of AI status. It specifically directs HHS (CDC/NIH) to research the health and developmental effects of AI chatbots on youth and integrate AI usage questions into national health surveys.

Specifically regulates mental health chatbots by requiring suppliers to clearly and conspicuously disclose to users that they are interacting with AI rather than a human. The act prohibits the sale or sharing of a user's health information with third parties without explicit consent and restricts the placement of advertisements within chatbot-driven therapy sessions.

Amends the Colorado Privacy Act to include 'neural data' within the definition of sensitive data, requiring affirmative opt-in consent before collection or processing. This affects AI developers using brain-computer interfaces (BCIs), EEG sensors, or other neuro-technologies in healthcare or consumer settings. By 2026, it serves as the foundational data protection statute for Colorado-based neuro-tech AI applications.

Proposed regulations for health insurers that use artificial intelligence or automated decision tools for processing prior authorization requests. The measure would have prohibited insurers from using AI as the sole basis for denying care, requiring a licensed professional with appropriate expertise to conduct a human review of all adverse determinations.

Utah's primary AI statute, as amended by SB 226 in 2025, requires proactive disclosure for 'high-risk' AI interactions, including those involving healthcare data, biometric data, or medical advice. Regulated healthcare professionals must prominently disclose AI involvement at the start of any interaction, and the law establishes a regulatory sandbox (AI Learning Laboratory) for testing healthcare AI solutions under state supervision.

Mandates that HHS develop a formal national strategy to address public health risks and preparedness requirements related to artificial intelligence. This includes responding to AI-driven health security threats and infrastructure vulnerabilities.

Regulates the use of automated systems and AI in medical coding to prevent artificial 'upcoding' and fraudulent billing practices. It requires transparency in how algorithms determine code intensity for reimbursement.

Establishes the Conversational AI Safety Act, requiring operators of public-facing chatbots to disclose their artificial intelligence status. It specifically prohibits AI from representing itself as a licensed mental or behavioral health professional and requires the implementation of crisis-response protocols for user prompts involving suicidal ideation.

Modernizes the prior authorization process in Medicare Advantage by requiring electronic processes and increased transparency. Significant AI nexus through requirements for standardized automated approval workflows and oversight of automated denial algorithms.

Requires healthcare providers to disclose to patients if clinical AI tools are being used to assist in medical diagnosis or treatment recommendations. The law mandates that providers provide written or verbal notice and maintain clear signage at point-of-care locations where AI-integrated technologies are utilized.

Would have required health insurers that use artificial intelligence or automated decision tools for claims intake, review, and adjudication to provide standardized disclosures when such tools materially assist in a claim determination. The bill also clarified that the use of AI tools for documentation or coding does not relieve healthcare providers of legal responsibility for the accuracy of information submitted to insurers.

The law prohibits health insurers from using automated decision systems as the sole basis for denying prior authorization or clinical claims. It requires a review by a Montana-licensed physician for any AI-recommended denials and mandates annual reporting of AI-driven utilization review metrics.

Creates a state-level advisory committee to monitor the impact of generative AI and algorithmic tools on Nevada's healthcare workforce and patient outcomes. The committee is tasked with developing ethical guidelines and reporting requirements for health systems adopting large-scale clinical AI models.

This bill mandates that any health insurance carrier using automated decision systems (ADS) for utilization review or prior authorization must have a licensed physician review any adverse determination. It requires carriers to disclose the use of such systems to the Department of Insurance and policyholders, ensuring that AI is not the sole arbiter of medical necessity.

Expands the definition of health care information under Wyoming's privacy laws to include neural data generated by neurotechnologies and AI-integrated devices. It mandates that entities collecting neural data must implement strict security protocols and obtain explicit written consent before any sharing or commercialization of the data.

Requires Medicare Advantage plans to disclose detailed cost data, specifically targeting the impact of AI-driven utilization management on patient care costs and out-of-pocket expenses.

This law prohibits medical and research facilities in Kansas from using AI platforms or genetic analysis software produced by foreign adversaries (such as DeepSeek). It requires healthcare research institutions to perform security audits of AI tools used for genomic analysis to ensure data integrity and national security compliance.

Regulates health insurers' use of AI and automated decision systems for utilization review and prior authorization, requiring human oversight for all denials. It mandates that insurers perform and submit annual impact assessments to the Division of Insurance to ensure AI models do not exhibit bias or unfair discrimination against protected classes.

Focuses on program integrity and federal scrutiny of AI used by Medicare Advantage Organizations (MAOs). It mandates proactive compliance safeguards to limit financial and operational risks associated with automated claims and enrollment processes.

This act mandates that healthcare providers disclose the use of AI tools to patients when such tools are used for diagnosis or treatment recommendations. It requires that a human clinician maintains final decision-making authority over AI-generated outputs in clinical settings.

This bill prohibits health plans from using algorithms or AI tools to automatically deny or modify healthcare service requests. It requires that all prior authorization denials be based on individual clinical information and independently reviewed by a licensed healthcare professional rather than group data models.

Establishes a regulatory framework for the use of artificial intelligence in clinical settings, specifically targeting clinical decision support tools. It requires health care providers to provide notice to patients when AI is used in a significant capacity for diagnosis or treatment recommendations and requires developers to provide transparency regarding the training data sets used.

Directs the Department of Health and Human Services to issue formal guidance on the coverage, coding, and payment for AI-enabled medical devices and diagnostic software within the Medicare program. The goal is to ensure that federal reimbursement frameworks are updated concurrently with FDA marketing authorizations for algorithm-based health technologies.

Amends Nevada's privacy statutes to classify neural data—information generated by the central or peripheral nervous system—as protected health data. This impacts AI developers using brain-computer interfaces or neurological sensors, requiring specific affirmative consent for the collection and processing of such data outside of traditional clinical research contexts.

This bill requires health insurance issuers and group health plans to disclose the use of AI in prior authorization and medical necessity determinations. It mandates that any AI-driven denial must be reviewed by a human physician and requires regular bias auditing for algorithms used in clinical settings.

Prohibits healthcare providers and payers from utilizing algorithms that yield discriminatory results based on protected characteristics. It requires covered entities to submit annual 'algorithmic impact statements' to the HHS Office for Civil Rights for any AI tools used in treatment pathways or resource allocation.

Directs the Department of Health and Human Services (HHS) to establish a comprehensive regulatory framework for the deployment of AI in clinical decision support. It specifically tasks the FDA with updating pre-market notification requirements for AI-enabled medical devices to ensure safety and effectiveness in diverse populations.

Amends the Social Security Act and HIPAA to regulate the use of patient health information in training large-scale AI models. It restricts the sale or transfer of patient data to third-party AI developers without opt-in consent and requires transparency regarding how health data influences generative AI outputs.

Mandates that the Centers for Medicare & Medicaid Services (CMS) conduct quarterly audits of AI algorithms used by Medicare Advantage plans for utilization management. The bill prohibits the use of AI as the sole basis for terminating post-acute care or denying inpatient hospital stays.

Establishes a National Center for AI Safety in Healthcare within the ONC to monitor real-world performance and adverse events associated with medical AI. It mandates that healthcare developers report any significant AI failures or patient harms to a centralized federal database within 48 hours of discovery.

Enacts the Artificial Intelligence Policy Act which requires healthcare providers and other regulated professionals to provide clear and conspicuous disclosure when using generative AI to interact with patients. It creates the Office of Artificial Intelligence Policy and a 'Learning Laboratory' to monitor AI risks and provide regulatory mitigation for developers.

Mandates a formal legislative interim study to evaluate the implications of artificial intelligence across all sectors in Montana, specifically focusing on transparency, ethics, and regulatory needs. The study is tasked with examining how other states regulate AI in healthcare and insurance and will recommend specific legislative actions for the 2027 session. Compliance professionals should monitor this study as it will likely result in future sector-specific healthcare AI mandates.

Requires all insurance carriers, including those providing health and accident insurance, to establish a rigorous governance framework for the use of artificial intelligence. It specifically prohibits the use of algorithms that result in unfair discrimination against protected classes in underwriting, rate-setting, or claims processing. Companies are required to perform impact assessments and provide public-facing disclosures regarding their use of AI technologies.

This legislation regulates the use of artificial intelligence and automated decision systems in health insurance utilization reviews. It mandates that any adverse determination or denial of care must be reviewed and confirmed by a human clinical professional, preventing automated 'black-box' denials. Furthermore, insurers must disclose to both providers and policyholders when AI algorithms are employed in the clinical review process.

Clarifies legal liability for medical errors caused by AI-generated recommendations, establishing that healthcare providers retain ultimate responsibility for clinical outcomes. It requires AI developers to provide 'explainability documentation' for all clinical decision support tools to facilitate forensic audits after adverse events.

Requires state Medicaid agencies to conduct annual impact assessments and audits of automated decision systems (ADS) used for eligibility determinations and benefits allocation. The bill focuses on identifying and mitigating algorithmic discrimination that disproportionately impacts low-income and minority patients.

This bill coordinates federal efforts to utilize AI and advanced technology to improve pediatric cancer care, including optimizing clinical trial design and patient access through the Childhood Cancer Data Initiative. It mandates the integration of AI efforts with existing health data interoperability standards while ensuring privacy-compliant data sharing.

Establishes a process for the Office of Professional Licensure Review to conduct 'scope of practice reviews' for healthcare innovations, specifically including artificial intelligence. It defines innovations as technological upgrades that augment a practitioner's ability to provide care but excludes technology that solely provides advice or treatment without direct practitioner-patient interaction.

Amends the Artificial Intelligence Policy Act to refine the disclosure requirements for generative AI. It mandates that individuals in 'regulated occupations,' including all licensed healthcare providers, must prominently disclose the use of generative AI when providing services involving 'high-risk' interactions such as personalized medical advice.

Requires the Department of Health and Human Services (HHS), through the National Institute on Aging, to conduct a comprehensive study on the impact of AI-enabled systems, such as chatbots, on older adults. The study focuses on health-related information accuracy, caregiving support, and the mitigation of social isolation through AI companionship.

This law mandates that health insurance carriers provide detailed transparency reports when using AI for utilization review and prior authorization. It requires a human physician to review and sign off on any clinical denial generated by an automated decision system, ensuring accountability for AI-driven outcomes.

Building on previous privacy laws, this bill classifies neural data—information generated by the measurement of an individual's central or peripheral nervous system—as 'sensitive data' under the Colorado Privacy Act. It imposes specific security and consent requirements for AI developers whose systems process brain-computer interface data for healthcare or diagnostic purposes.

Establishes professional standards for the integration of generative AI 'chatbots' or virtual assistants in telehealth platforms. It requires providers to disclose to patients when they are interacting with an AI and mandates that AI-generated clinical advice be validated by a licensed practitioner.

Proposed to prohibit the state from entering into contracts with health IT vendors whose AI tools demonstrate disparate impacts based on protected characteristics. The bill failed to pass out of committee during the final days of the session.

This law mandates that health benefit plans using AI or automated decision systems for utilization review must provide public disclosure of their use. It requires that any denial of coverage generated by an algorithm be reviewed and signed by a licensed physician with the same specialty as the treating provider.

The bill sought to establish professional standards for healthcare providers using generative AI for clinical diagnosis or treatment planning. It would have required providers to obtain express written consent from patients before using AI-generated recommendations in their care path.

This bill prohibits the Secretary of Health and Human Services from implementing or testing payment models, such as the WISeR model, that utilize artificial intelligence for prior authorization in traditional Medicare. It further amends the Social Security Act to prevent any future Medicare Advantage or traditional Medicare models from using automated decision systems to delay or deny care without primary human clinical review.

This act regulates how hospitals and medical debt collectors use predictive AI models to determine a patient's propensity to pay or to automate billing disputes. It requires hospitals to perform an annual algorithmic impact assessment to ensure AI tools do not produce discriminatory outcomes based on protected health data.

A broad AI governance bill that was amended to include specific healthcare and insurance protections, including a prohibition on health insurers using patient data to train AI systems without explicit informed consent. It also proposed new reporting requirements for developers of high-risk AI systems used in automated decision-making contexts such as housing and insurance.

Mandates an interim study to evaluate the implications of AI technology and its regulatory needs, including transparency, liability, and civil rights impacts. The study includes assessing the use of AI in state agencies and its effects on resident data privacy, with findings intended to inform future legislation in the 2027 session.

This bill regulates the use of high-risk AI systems in hospital settings, specifically targeting automated triage and patient monitoring systems. It requires healthcare facilities to conduct annual impact assessments to detect and mitigate algorithmic bias in patient care delivery.

Requires companies using automated decision systems for high-stakes decisions, including health insurance and clinical care, to perform impact assessments for bias and safety. It establishes a duty of care for platforms designing algorithms that could result in patient harm or discriminatory outcomes.

Mandates the development of a national strategy to protect rural healthcare facilities from cyber threats, including a specific focus on mitigating risks from AI-driven cyberattacks and the secure deployment of AI within hospital IT infrastructure.

This amendment expands Montana's data privacy protections to include 'neural data'—information generated by the measurement of the activity of a person's central or peripheral nervous system. It directly impacts healthcare AI developers using brain-computer interfaces (BCIs) or neuro-technology by classifying such information as sensitive data requiring explicit opt-in consent. It establishes strict guidelines for AI systems that decode or process neural signals for medical or therapeutic purposes.

This bill creates a multidisciplinary task force to evaluate the implementation of AI across state agencies and the healthcare sector, specifically focusing on data security and ethical clinical use. The task force is required to provide recommendations for future regulation of AI-driven medical diagnostics and the use of AI in state-funded health programs. It impacts entities seeking government contracts or participating in Montana's public health initiatives.

The proposed bill would have required healthcare facilities and practitioners to provide written notice to patients when an artificial intelligence system was significantly involved in their diagnosis or treatment. It sought to mandate 'explainability' standards where clinicians would have to be able to explain the general logic of the AI's clinical recommendations upon request. The bill failed to pass out of committee before the session adjournment.

This law expands the definition of 'sensitive data' under the Colorado Privacy Act to include biological and neural data, which covers information generated by the central or peripheral nervous systems. Healthcare AI developers utilizing neurotechnology or biometric analysis must provide heightened security, clear disclosures, and obtain consumer consent before processing such sensitive data. It remains the foundational privacy law for neuro-AI applications and health-tech wearable devices in Colorado as of 2026.

Aims to improve access to AI-enabled medical devices by creating a temporary payment code for these technologies under Medicare's outpatient reimbursement system for five years. This pathway allows for data collection on the clinical efficacy and service costs of AI diagnostics to inform future permanent reimbursement rates.

Commonly known as the MIND Act, this bill defines 'neural data' as a sensitive category of personal information and directs the FTC to regulate its collection and use by neurotechnology devices. It addresses privacy risks associated with AI analysis of brain activity data and physiological signals in healthcare and consumer wearables.

Empowers federal agencies, including HHS, with expanded enforcement authority to ensure that AI systems used in healthcare comply with existing civil rights and consumer protection laws. It requires health systems and insurers to certify that automated decision-making tools for housing or clinical care do not exhibit racial or socioeconomic bias.

The legislation prohibits health insurance companies from using AI or automated decision systems as the sole basis for denying a claim or a prior authorization request. Any adverse determination generated by an algorithm must be reviewed by a licensed clinical professional with expertise in the relevant field before the denial is finalized.

This law requires healthcare practitioners to provide written disclosure to patients when artificial intelligence is utilized to make a final diagnosis or recommend a primary course of treatment. It further mandates that healthcare facilities maintain a registry of AI tools used in clinical settings and perform annual impact assessments to detect algorithmic bias. Failure to disclose or monitor for bias can result in disciplinary action by the respective licensing board.

As the primary AI governance framework in Colorado, this law requires developers and deployers of high-risk AI systems, including those used in healthcare, to implement comprehensive risk management programs and avoid algorithmic discrimination. Deployers must conduct annual impact assessments and provide specific disclosures to consumers when an AI system is used to make a consequential health decision.

Expands Nevada's Consumer Health Data Privacy Act to explicitly include 'neural data' generated by the measurement of the activity of a person's central or peripheral nervous system. This significantly impacts AI developers creating neuro-technology or brain-computer interfaces for health monitoring, requiring affirmative consent before such data can be processed by machine learning models. It grants consumers the right to delete neural data and opt-out of its use in AI training.

Explicitly blocks funding for the WISeR pilot program, which uses AI to automate prior authorization decisions for certain Medicare services. It mandates that any algorithm-based coverage determination in traditional Medicare must undergo human clinical review and prohibits sole reliance on AI for denying patient care.

Regulates the use of automated decision systems and AI by health insurers for utilization review and claims processing. Insurers must certify to the Commissioner of Insurance that their AI tools do not result in unfair discrimination based on protected classes, including race and health status. It requires insurers to provide an explanation to policyholders if a claim denial was generated or assisted by an algorithm.

Updates the Nevada Consumer Health Data Privacy Act to include 'neural data' within the definition of sensitive health information, specifically targeting AI technologies like brain-computer interfaces. It requires AI developers to obtain explicit consent before collecting or processing brain activity data and grants patients the right to delete such data from AI training sets.

Requires health insurers to disclose the use of automated decision systems in utilization review and clinical coverage determinations. It mandates that any denial of care generated by an algorithm must be reviewed by a licensed healthcare professional with relevant clinical expertise before a final adverse determination is made.

Regulates the use of generative AI in direct patient-facing communications and medical record documentation. Providers must obtain informed consent from patients before using AI-generated clinical advice and must clearly label any AI-generated summary in the electronic health record.

Proposed a regulatory framework for the Kansas Department of Health and Environment (KDHE) to use AI for epidemiological modeling and public health surveillance. The bill required annual impact assessments to ensure no bias against protected health classes in automated public health interventions.

Includes significant funding (Item 81) for the 'Utah Health AI Vault' to modernize the Utah Population Database at the University of Utah. This initiative supports the development of a technology system using health data and AI to drive clinical discovery, improve population-based medical outcomes, and inform state policy decisions.

The Heat Emergency Assessment and Tracking using AI Act directs HHS to establish a pilot program to develop AI tools that analyze unstructured medical records and localized weather data to improve the surveillance of heat-related illnesses and deaths. Participating hospitals and health departments must use these tools to create automated response protocols and clinician training modules.

Mandates that all biological research and clinical studies funded by the federal government must be formatted as AI-ready datasets. It establishes a centralized bio-dataset repository managed by NIH to facilitate the training of large-scale healthcare foundation models and requires investigators to adhere to new data standardization and security protocols.

This bill regulates the use of automated decision tools (ADTs) by health insurers for utilization review and claims processing. It requires insurers to disclose the use of AI to policyholders and mandates that any adverse medical necessity determination be reviewed by a licensed healthcare professional. The act aims to prevent 'denial by algorithm' without clinical oversight.

This comprehensive AI governance bill classifies AI systems used in healthcare delivery, clinical decision support, and health insurance as 'high-risk.' It requires developers to provide detailed documentation on training data and requires healthcare providers (deployers) to conduct annual algorithmic impact assessments. The law also mandates consumer notification when an AI system is making a consequential decision about their health.

Requires healthcare facilities and practitioners to provide written disclosure to patients when artificial intelligence is used to assist in clinical diagnoses or treatment recommendations. It mandates that any AI-generated clinical decision support must be reviewed and signed off by a licensed healthcare professional to prevent automated-only medical decisions.

Directs the Department of Health and Human Services (DHHS) to conduct an exhaustive inventory and impact assessment of all automated decision systems used in the administration of public health programs. The act requires reporting on the data sets used to train models that determine eligibility for Medicaid and other state-funded clinical services.

This legislation regulates how health insurers and pharmacy benefit managers use automated decision systems (ADS) for utilization review and claims processing. It requires insurers to disclose the specific clinical criteria and algorithmic logic used when a claim is denied by an automated system and mandates that all appeals of AI-generated denials be reviewed by a human medical professional.

This bill enacts the AI Transparency Act, requiring developers of certain artificial intelligence models to create, implement, and publish public safety and child protection plans. It also mandates the publication of risk assessment summaries and prohibits developers from making materially false or misleading statements about covered risks.

Directs the FTC and OSTP to establish a regulatory framework for 'neural data' collected by brain-computer interfaces and neurotechnology AI. It mandates strict privacy protections for biometric and neurological data used in clinical and consumer AI health applications, requiring impact assessments for AI models that analyze cognitive states.

Amends the Social Security Act to ensure appropriate Medicare payment for algorithm-based healthcare services. It requires the Secretary of HHS to establish new technology ambulatory payment classifications specifically for AI-driven diagnostic and therapeutic tools used in outpatient settings.

Empowers federal agencies including HHS to enforce existing health and civil rights laws against organizations using AI for life-altering decisions. It specifically targets AI-driven healthcare coverage and clinical decision-making, requiring agencies to issue sector-specific rules for algorithmic transparency and human-in-the-loop requirements.

Originally a billing bill, recent amendments require health plans to provide detailed disclosures regarding the use of AI-supported automation in prior authorization and claims processing. It mandates that states require Medicaid health plans to disclose testing, evaluation, and human oversight protocols for all AI used in utilization management.

Establishes a federal framework for large-scale AI developers, mandating third-party audits and a 24-hour reporting requirement for safety incidents causing 'serious physical injury.' While primarily focused on foundation models, it carves out a federal role in monitoring high-risk AI deployments in clinical environments and creates the Center for AI Standards and Innovation.

This legislation requires hospitals and large medical groups to perform annual impact assessments on AI algorithms used for clinical diagnosis or treatment recommendations. Covered entities must submit bias mitigation reports to the Colorado Department of Public Health and Environment to ensure equitable outcomes across protected classes.

Building upon 2024 biological data protections, this act classifies neural data used by AI diagnostic tools as sensitive information under the Colorado Privacy Act. It requires healthcare AI developers to implement strict data minimization and provides patients with the right to opt-out of neural data processing for non-clinical purposes.

This bill mandates transparency for health insurers utilizing AI and automated decision systems in utilization review and prior authorization processes. It requires a licensed physician to review and validate any adverse medical necessity determination generated by an algorithm before a denial is issued.

This law requires healthcare providers to provide clear notice to patients when artificial intelligence or machine learning is used to significantly inform clinical diagnosis or treatment recommendations. It mandates that clinical decision support tools remain subordinate to the practitioner's professional judgment and requires providers to maintain documentation of AI-assisted decisions for five years.

This omnibus AI governance law classifies healthcare and health insurance as 'consequential decision' sectors, subjecting AI tools in these fields to 'high-risk' requirements. Developers must provide impact assessments and technical documentation to deployers (hospitals/insurers), while deployers must implement risk management programs and conduct annual audits to prevent algorithmic discrimination.

Prohibits health insurance companies from using automated decision systems as the sole basis for denying a claim or a request for prior authorization. It requires a meaningful human review by a qualified medical professional for any adverse determination generated by an algorithm.

Attempted to establish liability frameworks for medical malpractice when AI software is used in patient diagnosis or treatment. The bill sought to define whether the clinician or the AI developer holds primary liability for algorithmic errors in a clinical setting.

This law requires all Kansas state agencies, including those overseeing health and human services (KDHE, KDADS), to provide clear notification when AI or automated systems are used in public-facing interactions. This impacts state-run healthcare portals, eligibility determinations for health programs, and automated patient communication tools managed by the state.

This bill targets the use of automated decision systems and complex algorithms in the insurance industry, including health insurance. It prohibits insurers from utilizing external consumer data or algorithms that result in unfair discrimination based on protected classes and requires rigorous risk management frameworks and disclosures to the Insurance Commissioner.

This bill requires the Division of Integrated Healthcare to maintain a dashboard of certain Medicaid data and publish specific data and reports on its website. It mandates that participants in the Medicaid program identify, report on, and repay improper payments, and develop corrective action plans to address such payments. The Department of Health and Human Services is required to publish reports of improper payments and corrective action plans on its website. The bill provides rulemaking authority, including sanctions for violations, and defines relevant terms. ([le.utah.gov](https://le.utah.gov/Session/2026/bills/enrolled/HB0566.pdf?utm_source=openai))

Expresses opposition to federal preemption of state laws regulating artificial intelligence, including those affecting healthcare.

Requires large entities using automated decision systems for 'critical decisions,' including healthcare, to conduct impact assessments and regular audits for bias and safety. The Federal Trade Commission (FTC) is tasked with establishing reporting guidelines and maintaining a public repository of basic information about covered systems.

Requires the Department of Veterans Affairs (VA) to submit a comprehensive plan to expand the use of automation and AI tools for processing benefit claims. The bill specifically targets the reduction of backlogs in pension and survivor benefits through improved digital document indexing and automated evidence gathering.

Mandates that developers of large-scale AI foundation models, including those used in medical diagnostics, disclose information regarding their training data, performance benchmarks, and red-teaming efforts. The FTC would oversee the transparency requirements to ensure users can assess the safety and reliability of models.

A massive reconciliation package that includes federal strategies to promote AI innovation through deregulation while simultaneously enacting significant Medicaid spending cuts and work requirements. The law directs agencies to identify and roll back federal regulations that may impede AI development in priority sectors like healthcare.

This legislation regulates the use of artificial intelligence in healthcare utilization reviews by insurance carriers. It mandates that any denial of a claim involving AI must be reviewed and validated by a licensed physician with relevant clinical expertise, prohibiting automated-only claim denials. Payors must disclose their use of AI algorithms to the Department of Insurance and to policyholders upon request.

This law establishes transparency requirements for the deployment of Clinical Decision Support (CDS) software in healthcare facilities. Healthcare providers are required to inform patients when an AI system significantly influences a diagnostic or treatment recommendation and must obtain specific consent for procedures heavily reliant on high-risk algorithmic outputs. It also requires facilities to maintain an inventory of all clinical AI tools currently in use.

This bill amends provisions related to parental access to children's medical records, ensuring that parents or legal guardians have the right to access their minor children's medical records, including those maintained by health care providers and health plans. It specifies the circumstances under which access may be denied and outlines the procedures for parents or guardians to request and receive copies of medical records.

This bill amends the Utah Artificial Intelligence Policy Act to specifically define and regulate 'high-risk' AI interactions, including those involving healthcare services, medical advice, and the processing of sensitive health data. It requires prominent disclosure to consumers when they are interacting with high-risk AI and expands the enforcement authority of the Office of Artificial Intelligence Policy.

Prohibits health insurers from using automated decision tools as the sole basis for denying a claim or determining medical necessity. It requires insurers to conduct annual algorithmic impact assessments to ensure AI tools do not produce biased outcomes against protected patient demographics.

Amends existing consumer privacy laws to include 'neural data' generated by the measurement of an individual's central or peripheral nervous system as sensitive health data. This impacts AI developers using neuro-technologies or biometric AI models in clinical or wellness settings, requiring strict opt-in consent.

This bill expands state privacy protections to include neural data and AI-generated biological profiles under the definition of sensitive personal information. It requires AI developers and healthcare entities to obtain explicit opt-in consent before collecting or processing brain-computer interface data or predictive neural health analytics.

This legislation regulates the use of artificial intelligence and automated decision systems by health insurers for utilization review and prior authorization. It mandates that any adverse determination generated by an AI must be reviewed by a licensed physician and requires insurers to disclose the use of AI algorithms in their decision-making processes to both providers and patients.

Proposed rigorous clinical validation standards for AI-based clinical decision support tools used in Wyoming hospitals. The bill failed to receive the necessary two-thirds vote for introduction during the budget session.

This bill regulates the use of artificial intelligence in health insurance utilization management. It mandates that any denial of coverage generated by an algorithm must be reviewed and certified by a licensed physician to ensure clinical accuracy and compliance with state-mandated medical necessity standards.

Requires healthcare providers to provide clear notice to patients when artificial intelligence is used to generate medical advice or diagnostic summaries. It establishes that clinical decision support systems remain advisory and that practitioners maintain ultimate liability for AI-influenced clinical decisions.

Proposed the creation of the Kansas Healthcare Data Privacy Act, specifically targeting the use of neural and biometric data in AI models. It would have required opt-in consent for the use of health data for profiling or automated decisions that result in legal or significant clinical effects.

Requires healthcare entities and health insurance issuers to provide clear disclosure when AI or automated decision systems are used in clinical care or coverage determinations. It mandates the creation of a public registry for high-risk AI health tools and requires annual bias audits for algorithms used in patient care.

Prohibits Medicare Advantage plans from using AI or algorithmic tools to deny coverage for medically necessary services without a meaningful human review. Requires plans to report accuracy rates and clinical outcomes for all AI-driven utilization review processes to CMS.

Directs the Department of Health and Human Services (HHS) to establish a cross-agency task force to monitor the development and deployment of AI in medical practice. The bill focuses on creating standardized validation metrics for clinical decision support tools to ensure safety and efficacy across diverse populations.

Establishes a framework for post-market surveillance of AI-based medical devices and software used in clinical settings. Requires healthcare providers to report 'AI adverse events' where algorithmic errors lead to patient harm and mandates that developers provide technical documentation to hospitals regarding training data diversity.

Expands the definition of protected health information (PHI) under HIPAA to include neural data and biometric signals used by AI-driven neurotechnology. It requires developers of consumer and clinical brain-computer interfaces to implement strict data minimization and consent protocols for AI training purposes.

This act prohibits health insurers from using automated decision systems to deny prior authorization requests without a subsequent review by a licensed healthcare professional in a similar specialty. It mandates that any AI-generated denial include a specific explanation of the clinical data used and provides the patient the right to appeal to a human reviewer.

The law requires healthcare providers to disclose to patients when generative AI or high-risk clinical decision support (CDS) algorithms are used to formulate diagnosis or treatment plans. It establishes standards for algorithm validation and requires facilities to maintain a registry of all AI tools used in patient-facing clinical workflows.

This bill defines 'artificial intelligence' within the context of emergency management and mandates that emergency management plans, both state and local, ensure that final decisions regarding emergency response and resource allocation are not made solely by AI. Additionally, it prohibits public utilities from making final decisions to reduce or shut down services during emergencies based solely on AI. Compliance is required from all state and local emergency management agencies and public utilities, effective October 1, 2025.

Amends the Artificial Intelligence Policy Act to clarify disclosure requirements, specifically mandating 'prominent' proactive disclosures for 'high-risk' interactions. These high-risk scenarios explicitly include interactions where AI is used to provide medical or mental health advice or when the system collects sensitive health or biometric data.

Establishes a regulatory framework for mental health chatbots, requiring suppliers to prominently disclose that the user is interacting with AI rather than a human. It prohibits the sale or sharing of individually identifiable health data and restricts the use of user inputs for targeted advertising within therapeutic chatbot platforms.

Directs HHS to establish a risk-based framework for clinical AI tools. Requires manufacturers to provide transparency regarding data provenance and validation metrics for AI models used in diagnostics.

Establishes post-market surveillance requirements for AI-enabled medical devices. Requires developers to notify the FDA of significant drift in model performance that could impact patient safety.

Mandates that Medicare Advantage plans disclose the use of automated decision systems in prior authorization. Requires annual independent audits to ensure AI models do not result in disparate denials for protected groups.

Regulates the use of consumer health data and neural data for training generative AI models. Prohibits the use of sensitive health information in AI training without express, opt-in consent from the patient.

Prohibits the use of automated systems for claims processing that lack human-in-the-loop review for clinical denials. Establishes a private right of action for patients harmed by biased algorithm-driven medical necessity determinations.

Requires health care providers and medical facilities to provide written or electronic notice to patients when generative AI or clinical decision support algorithms are used to significantly inform a diagnosis or treatment plan. It establishes a patient's right to request a manual review of any AI-driven clinical recommendation by a qualified human practitioner.

Governs the use of high-risk automated decision systems by state agencies, including the Department of Health and Human Services (DHHS). It requires impact assessments for AI systems used to determine eligibility for public assistance, healthcare benefits, or clinical placements, and mandates a mechanism for administrative appeal of AI-driven denials.

Requires healthcare providers using generative AI to interact with patients during telehealth visits to provide a clear and conspicuous disclosure at the start of the interaction. It applies to both synchronous and asynchronous AI-driven chatbots used for triage or patient intake.