{"id":905846,"date":"2026-07-01T14:51:02","date_gmt":"2026-07-01T20:51:02","guid":{"rendered":"https:\/\/www.myconstructionexpert.com\/blog\/?p=905846"},"modified":"2026-07-01T14:51:09","modified_gmt":"2026-07-01T20:51:09","slug":"artificial-intelligence-congress-and-state-lawmakers-racing-to-keep-up","status":"publish","type":"post","link":"https:\/\/www.myconstructionexpert.com\/blog\/artificial-intelligence-congress-and-state-lawmakers-racing-to-keep-up\/","title":{"rendered":"Congress and State Lawmakers Are Racing to Keep Up With AI"},"content":{"rendered":"\n

Gabe Maldoff, Omer Tene and Bethany P. Withers | Goodwin<\/a><\/p>\n\n\n\n

States are taking the lead in regulating artificial intelligence<\/a> (AI), even as Congress begins to debate a bipartisan frontier AI law and the Trump administration pursues a deregulatory agenda seeking to curb state AI lawmaking through an executive order (EO).<\/p>\n\n\n\n

This year is set to break previous records, with more than 1,500 AI bills under consideration in statehouses, many of which are nearing or have crossed the finish line. These laws add to a chorus of state lawmaking, which includes 150 AI-related bills that passed into law in 2025, according to a Stanford University report.<\/p>\n\n\n\n

Congress\u2019 latest foray into AI regulation would, if passed, build on the framework emerging at the state level. Released on June 4, 2026, by Reps. Jay Obernolte (R-CA) and Lori Trahan (D-MA), the Great American AI Act of 2026 would nationalize the frontier-model governance approach emerging in several states. While the bill would preempt certain state laws that regulate AI development for a three-year period, the current discussion draft of the bill would leave much of the current state patchwork intact.<\/p>\n\n\n\n

Meanwhile, President Trump\u2019s EO, which\u00a0aims to block state AI lawmaking<\/a>\u00a0in order to promote AI innovation and US competitiveness, hasn\u2019t yet displaced the framework emerging at the state level. In fact, a more recent EO, \u201cPromoting Advanced Artificial Intelligence Innovation and Security<\/a>,\u201d adopts a voluntary standard for frontier AI safety that\u2019s similar to the state model and congressional bill.<\/p>\n\n\n\n

The structure of AI regulation emerging across these state and federal initiatives doesn\u2019t replicate the European Union\u2019s more \u201ccomprehensive\u201d AI Act, which prohibits certain uses of AI deemed unacceptable and includes frameworks of varying complexity for \u201chigh-risk\u201d and \u201cgeneral-purpose\u201d AI systems and models.<\/p>\n\n\n\n

Instead, US regulation has focused on several key issues, such as AI companions, mental health applications, the use of AI to make \u201cconsequential decisions,\u201d generative AI development, and frontier models, as well as AI deployment in critical sectors such as life sciences, healthcare, and financial services.<\/p>\n\n\n\n

Here are the key themes underlying the emerging consensus on US AI regulation, as it stands in 2026:<\/p>\n\n\n\n

AI Disclosures for Chatbots<\/h4>\n\n\n\n

The earliest AI-specific laws \u2014 predating the rise of generative AI \u2014 required companies to disclose to consumers that they were interacting with AI in limited contexts, such as online sales and political advocacy. As generative AI use cases have proliferated, so have AI transparency measures. Utah\u2019s AI Policy Act, for example, requires those in \u201cregulated occupations\u201d (including healthcare professionals) to disclose to consumers at the beginning of an interaction that they are interacting with generative AI. Outside of regulated occupations, other businesses need to \u201cclearly and conspicuously\u201d tell consumers that they are interacting with generative AI systems when asked.<\/p>\n\n\n\n

At their core, these laws are designed to ensure that consumers know when they are interacting with AI models rather than humans. Expect that requirements to disclose AI use will continue to proliferate.<\/p>\n\n\n\n

Self-Harm and Children\u2019s Safety Guardrails for Companion AI<\/h4>\n\n\n\n

Some states, including California, Connecticut, New York, Oregon, and Washington, have begun regulating \u201ccompanion AI\u201d services that simulate ongoing human-like relationships. These laws reach beyond chatbots that are explicitly marketed as AI companions and could include a wide range of chatbots that retain and draw from conversation logs across user sessions.<\/p>\n\n\n\n

Companion AI laws are designed to address emotional manipulation, mental health risks, and use of services by vulnerable populations, such as minors.<\/p>\n\n\n\n

Companion AI laws generally require companies to inform (and, in some instances, remind) users that they are engaging with AI and implement policies and protections against self-harm and suicidal ideation. California\u2019s companion AI law, for instance, mandates that companion chatbot operators publish a safety protocol on their website and refer users to crisis service providers, such as a suicide hotline or crisis text line, if the user expresses signs of suicidal ideation, suicide, or self-harm.<\/p>\n\n\n\n

Chatbots offered to minors are subject to more stringent protections. For example, Oregon Senate Bill (SB) 1546 requires that covered chatbot operators employ reasonable measures to prevent the AI companion from producing sexually explicit content and remind minor users to take a break at least every three hours.<\/p>\n\n\n\n

Restrictions on Mental Health and Therapeutic Uses<\/h4>\n\n\n\n

States are beginning to draw clearer lines around the use of AI in therapy, with laws including Illinois\u2019 House Bill (HB) 1806 setting an early benchmark.<\/p>\n\n\n\n

Most significantly, HB 1806 prohibits AI from replacing licensed therapists in delivering care \u2014 complicating the use of more autonomous, agentic AI systems capable of making therapeutic decisions and raising critical questions for use of AI in health and wellness applications, which are among the most popular consumer uses of AI.<\/p>\n\n\n\n

Illinois\u2019 law also requires licensed providers to obtain patient consent for certain \u201csupplementary support\u201d uses, including recording or transcribing sessions and maintaining patient file notes, and allows AI to support administrative tasks, such as scheduling therapy sessions, without patient consent.<\/p>\n\n\n\n

Transparency, Explainability, and Rights to Contest Use of AI for Consequential Decisions in Employment, Financial Services, Healthcare, Education, and Housing<\/h4>\n\n\n\n

Although regulation of automated decision-making technology (ADMT) existed long before the advent of generative AI \u2014 including in EU data protection laws dating back to 1995 \u2014 the growing sophistication and scale of modern AI systems has brought renewed regulatory focus to these tools used in \u201cconsequential\u201d or \u201csignificant\u201d decisions affecting employment, financial services, healthcare, education, and housing.<\/p>\n\n\n\n

States such as Colorado, Texas, and California have advanced laws and regulations that impose obligations on companies using ADMT. Illinois and New York City have passed similar measures focused specifically on employment. Importantly, these laws not only apply to \u201csolely\u201d automated decisions but also AI-assisted decisions in which ADMT plays a role in the outcomes, though the threshold for triggering regulation varies from a \u201csubstantial factor\u201d standard to the lower \u201cnon-de minimis factor\u201d test adopted by Colorado\u2019s amended law.<\/p>\n\n\n\n

Common requirements in these laws include notifying consumers when AI is being used in consequential decision-making, giving individuals opportunities to opt out of or contest the decision, allowing individuals to seek human review, and requiring companies to adopt risk management policies to minimize error, bias, and discrimination.<\/p>\n\n\n\n

Colorado\u2019s recent legislative pivot illustrates how ADMT regulation is evolving. In 2026, the state replaced its landmark Colorado AI Act with the Colorado ADMT Act, broadening the law\u2019s focus from \u201cartificial intelligence\u201d to \u201cautomated decision-making technology.\u201d The new law expands coverage to a wider range of digital technologies, and while the amendment replaces many of the original law\u2019s governance requirements with a framework centered on transparency, consumer rights, and accountability, a new liability regime is designed to encourage companies to implement internal procedures and safeguards \u2014 similar to those mandated in the original law \u2014 to mitigate legal risks.<\/p>\n\n\n\n

Training Data Transparency and Watermarking for Generative AI Developers<\/h4>\n\n\n\n

Some laws specifically regulate generative AI systems that generate new content based on patterns learned from large training datasets.<\/p>\n\n\n\n

California\u2019s\u00a0Assembly Bill (AB) 2013, for example, requires developers of generative AI systems, as well as entities that \u201csubstantially modify\u201d such systems, to\u00a0publicly post documentation<\/a>\u00a0about the data used to train their models, including the sources and ownership of the datasets, the purpose and methodology of data collection, the inclusion of personal information, and the licensing status of such datasets.<\/p>\n\n\n\n

Under another California law, SB 942, developers of generative AI systems with more than 1 million monthly users need to watermark AI-generated content to facilitate detection and provide tools that allow users to verify whether content was generated by the developer\u2019s system.<\/p>\n\n\n\n

Frontier AI Safety and Safeguards Against Catastrophic Risks<\/h4>\n\n\n\n

Some states are beginning to address the risks associated with the most advanced AI systems, often referred to as \u201cfrontier models\u201d \u2014 defined as foundation models that are trained on broad datasets, adapted to a wide range of tasks, and developed using a quantity of computing power greater than 10^26 computational operations. Both California and New York have adopted laws that require developers of frontier models to implement frameworks designed to protect against \u201ccatastrophic risks.\u201d<\/p>\n\n\n\n

Frontier AI safety frameworks must include alignment with national, international, or industry standards; internal governance programs; third-party risk assessments; and transparency reporting of such frameworks and assessments. Frontier developers also need to disclose certain safety incidents to regulators within set timelines. A bill in Illinois (SB 315), which has passed the legislature and is now awaiting the governor\u2019s signature, would build on the California and New York laws by also requiring independent third-party auditing of compliance with internal safety frameworks.<\/p>\n\n\n\n

The White House is also stepping in to formally oversee advanced AI developers. A recent Trump administration EO asks AI companies to share models with the government for cybersecurity testing before public release. The Great American AI Act of 2026, currently under debate in Congress, would impose transparency reports, a published frontier AI framework, critical safety incident reporting, and whistleblower protections on large-scale frontier developers \u2014 measures that largely align with the California and New York laws. The proposed federal law would also incorporate independent auditing requirements similar to Illinois SB 315.<\/p>\n\n\n\n

Sector-Specific Legislation: Employment, Healthcare, and Finance<\/h4>\n\n\n\n

Rather than enacting a single omnibus statute, many states are increasingly regulating AI sector by sector.<\/p>\n\n\n\n