Bridging Innovation and Accountability: The Evolution of AI Governance in Massachusetts

Introduction

Massachusetts is home to leading biotech and life sciences companies, research universities, and a vibrant start-up ecosystem. Although the state is not mentioned as frequently as other jurisdictions when discussing the AI industry or AI regulation, Massachusetts has made substantial investments into AI in recent years and has been a key voice in the development of AI safeguards. These efforts include the establishment of the state’s AI Strategic Task Force in 2024 and subsequent USD100 million investment in the Massachusetts AI Hub, a collaborative initiative between government, industry, start-ups, and academia to address critical challenges and expand economic opportunities across the state.

Likewise, although the state has not yet passed a comprehensive AI statute, Massachusetts has found meaningful ways to govern AI technologies through its existing consumer protection, anti-discrimination, and data privacy laws, as endorsed by Attorney General Campbell’s 16 April 2024 advisory reiterating the applicability of existing Massachusetts law to developers, suppliers, and users of artificial intelligence and algorithmic decision-making systems.

Legal developments

April 2024 AI advisory and notable activity from the Attorney General’s Office

On 16 April 2024, the Massachusetts Attorney General Andrea Campbell issued an Advisory on the Application of the Commonwealth’s Consumer Protection, Civil Rights, and Data Privacy Laws to Artificial Intelligence (“AI Advisory”) describing the application of the Commonwealth’s consumer protection, anti-discrimination, and data privacy laws to developers, suppliers, and users of artificial intelligence and algorithmic decision-making systems. In the absence of substantial omnibus legislation, the AI Advisory remains an important reference for the Massachusetts AI legal regime and regulators’ enforcement priorities. In particular, it highlights that Massachusetts does not need additional AI legislation to pursue enforcement actions within the state, but can rely on well-established existing authorities, including Mass. Gen. Laws ch. 93A Section 2 (prohibiting unfair or deceptive acts or practices) and 940 Mass. Code Regs. 3.02 (prohibiting false advertising).

Among the AI-related activities that the AI Advisory lists as possibly constituting unfair or deceptive practices subject to Massachusetts and federal consumer protection laws are as follows.

• False advertisement of “the quality, value, or usability of AI systems[,]” such as when “a supplier claims that an AI system has functionality that it does not possess.” (AI Advisory at 3.)
• “Supply[ing] an AI system that is defective, unusable, or impractical for the purpose advertised[,]” since “[s]uppliers have an obligation to ensure that an AI system performs as intended.” (Id. (citing American Shooting Sports Council, Inc. v Attorney General, 429 Mass. 871, 877 (1999)).)
• “Misrepresent[ing] the reliability, manner of performance, safety, or condition of an AI system. ... Examples of misrepresentation include claims or representations that an AI system is fully automated when [in reality] its functions are performed in whole or in part by humans.” (Id.)
• “Offer[ing] for sale or use an AI system in breach of warranty in that the system is not fit for the ordinary purposes for which such systems are used, or [...] is unfit for the specific purpose for which it is sold where the supplier knows of such purpose.” (Id.)
• “Misrepresent[ing] audio or video content of a person for the purpose of deceiving another to engage in a business transaction or supply personal information as if to a trusted business partner” like using “deepfakes, voice cloning, or chatbots ... to engage in fraud.” (Id.)
• “Fail[ing] to comply with Massachusetts ‘statutes, rules, regulations or laws, meant for the protection of the public’s health, safety, or welfare.’” (Id. at 4 (quoting 940 Mass. Code Regs. 3.16(3).)
• Failing to “provide accurate and specific reasons to consumers indicating why their loan applications were denied, including in circumstances where the creditor uses AI models.” (Id.)

These examples emphasise that suppliers have an obligation under Massachusetts law to ensure accuracy in their product descriptions and ensure that an AI system performs reasonably as expected. These examples also emphasise that existing laws – and well-recognised crimes – will continue to be enforced and prosecuted when committed with the aid of AI.

The AI Advisory also makes clear that Massachusetts’ anti-discrimination laws apply equally to AI systems and prohibit the deployment of AI systems that discriminate against Massachusetts residents on the basis of a legally protected characteristic. This includes algorithmic decision-making technologies that rely on or use discriminatory inputs and produce discriminatory results that disfavour or disadvantage a person or group of people based on a legally protected characteristic. Likewise, the AI Advisory emphasises that AI systems “must comply with the [state’s] Standards for the Protection of Personal Information of Residents of the Commonwealth” and that “AI developers, suppliers, and users must take the necessary and appropriate steps to safeguard personal information used by those systems, and are expected to comply with the breach notification requirements set forth [under the breach notification law].” (Id. (citation omitted).)

While the AI Advisory is not binding law, the consumer protection focus in the Advisory signals that the Massachusetts Attorney General is especially focused on entities that engage in consumer harms using AI, such as overstating the capabilities of AI technologies. This concern mirrors recent commentary and activity by other regulators at both the federal and state level, including the Federal Trade Commission, which has taken actions against companies alleged to have engaged in deceptive or unfair practices by exaggerating the capabilities of their AI products, as demonstrated in the Commission’s 2024 Operation AI Comply.

Consumer protection in action

The Massachusetts Attorney General’s Office has also participated in several bipartisan, multi-state efforts aimed at addressing key AI-related concerns. For example, Massachusetts co-led a coalition of attorneys general in August 2025 calling on search engines and payment platforms to take stronger action against the increasing spread of AI-generated deepfake non-consensual intimate imagery. Massachusetts also signed on to an August 2025 bipartisan letter to multiple AI companies urging them to protect children from harmful chatbot interactions, citing recent reports of inappropriate and sexualised content involving minors.

Although Massachusetts has not enacted AI-specific laws that expressly require companies to implement formal governance programmes of the kind required by some other state laws, consumer protection enforcement activity and injunctive relief precedent through the Massachusetts Attorney General’s Office highlights a focus on risk management processes. The Attorney General’s Office favours comprehensive governance programmes with internal controls, ongoing risk assessments and testing, as well as identified individuals or functions for oversight. This can be particularly important where AI or algorithmic or automated decision-making may implicate consumer protection or anti-discrimination concerns. Notably, elements such as internal oversight teams, documented testing practices, and protected channels for reporting algorithmic bias that may be viewed favourably by Massachusetts policymakers mirror features of AI legislation in other jurisdictions, such as those in California’s Transparency in Frontier AI Act.

As another illustration, on 3 January 2025, the Massachusetts Executive Office of Technology Services and Security issued a formal Enterprise Use and Development of Generative AI Policy that established baseline requirements for how state agencies and offices may develop and use AI systems. The policy is expressly designed to create minimum governance standards, emphasising that agencies must deploy AI in a manner that is ethical, transparent, accountable, and aligned with public trust. It incorporates core principles drawn from frameworks like NIST, including risk management, accountability, transparency, fairness, and privacy by design, and requires agencies to actively evaluate and mitigate risks, such as bias, discrimination, data integrity issues, and misinformation. Although the policy formally applies only to state agencies and their personnel (including contractors and vendors working with the state), the policy reflects a broader signal of expectations and best practices in Massachusetts, particularly around documentation, testing, transparency, and bias mitigation.

Lie detector statute and developments from the Plaintiffs’ Bar

Aside from AI legislation or enforcement activity, the Massachusetts’ lie detector statute (Mass. Gen. Laws ch. 149, Section 19B) has emerged as an interestingly prominent component of the state’s AI regulation landscape. Passed in 1986, the law was originally enacted to prohibit employers from requiring polygraph tests. The statute is drafted broadly, barring the use of any “device, mechanism, instrument or written examination” designed to detect deception or assess honesty, and requires employers to include a notice on job applications informing applicants of this prohibition. (Id.) This expansive language, coupled with a private right of action and statutory damages, has made the law an attractive vehicle for plaintiffs alleging that certain AI-enabled hiring tools, especially video interview platforms, function as prohibited lie detectors.

For example, in Baker v CVS Health Corp., 717 F. Supp. 3d 188 (D. Mass. 16 February 2024), a job candidate alleged that the defendant had violated the lie detector statute by requiring the candidate to undergo an AI video interview process which analysed an applicant’s facial expressions and vocal cues to evaluate personality traits, including honesty and integrity. Although the case eventually settled, the district court had initially denied the defendant’s motion to dismiss recognising that there had been an information injury based on the employer’s failure to provide the appropriate notice under the statute, stating that while “the notice would not have specifically informed [the defendant] that the [interview] was a lie detector test, it would have primed him to view the interview more critically.” (Id. at 192.) At the same time, more recent decisions have introduced meaningful constraints to the application of the lie detector statute to such technologies. In particular, case law has emphasised that it may not be enough that an AI video interview tool could be theoretically used to infer honesty, but that it must be actually used for that purpose – particularly where any device, mechanism, instrument, or written examination could qualify as a lie detector should a theoretical feasibility standard be used.

Although case law continues to evolve, it is clear that, even in the absence of substantial generally applicable AI legislation, there continues to be legal developments shaping the use of AI technologies in Massachusetts, with certain scenarios presenting higher risk than others.

Public investment in AI

Beyond legal developments, Governor Healey has stated that AI is a key component of the state’s economic strategy. On 20 November 2024, she signed the Mass Leads Act, a nearly USD4 billion economic development package that includes up to USD100 million to support the creation of an AI Hub in Massachusetts. The legislation is intended to strengthen the state’s leadership in climate tech, life sciences, and emerging technologies, including applied AI, which the Governor has identified as critical to long-term state economic growth.

The AI Hub, launched on 6 May 2025, is intended to act as a central point of co-ordination for AI innovation across industry, academia, and the public sector, though its full structure and implementation continue to develop. As part of these efforts, the state has committed USD31 million in funding to expand high-performance computing and data capacity, including support for the Massachusetts Green High Performance Computing Center, a consortium that includes Boston University, Harvard, MIT, Northeastern, University of Massachusetts, and Yale. Over the next five years, the joint partnership is expected to receive approximately USD120 million in funding from the state and universities.

In February 2025, the Massachusetts Technology Collaborative (MassTech) launched the Massachusetts AI Models Innovation Challenge, which is intended to provide more than USD3 million in funding for AI model development projects across advanced manufacturing, climate tech, education, financial services, healthcare, life sciences, and robotics. In March 2025, MassTech also announced a grant of more than USD1.9 million through its Sector Spark programme, intended to support entrepreneur support organisations across the state, to Cambridge-based LabCentral, and partner C10 Labs, which plan to use the funds to launch the first “Applied AI” programme targeting AI breakthroughs in biotech.

As Massachusetts continues to grow in tech innovation and investment, the authors expect to see continued policymaker attention on the development of safeguards, and consumer protection regulator activity. This may well lead to comprehensive AI legislation in the future.

Looking ahead

Currently, there are a number of bills that are being considered by the Massachusetts legislature related to AI. For example, as of April 2026, Massachusetts lawmakers are debating more targeted, sector-specific proposals like S2632 which focuses on healthcare AI and seeks to regulate the use of AI technologies in clinical and insurance-related decision-making processes.

Among the most notable proposals is H94, “An Act to Ensure Accountability and Transparency in Artificial Intelligence Systems.” This bill would establish a comprehensive AI framework focused on consumer protection and algorithmic fairness. The bill contains a risk-based approach, centred on “high-risk” AI systems that materially influence consequential decisions in areas such as employment, housing, lending, healthcare, and insurance. The bill would also impose obligations on both developers and deployers of AI systems under which developers would be required to exercise reasonable care to identify and mitigate algorithmic discrimination, maintain detailed documentation on system functionality and training data, and disclose certain known risks to deployers and the Attorney General. Deployers, in turn, would need to implement risk management programmes aligned with recognised standards (such as the NIST AI Risk Management Framework), conduct annual impact assessments, and provide consumer-facing disclosures when AI materially influences decisions. However, what ultimately becomes of this legislative proposal remains to be seen, particularly in light of the federal national AI policy emphasising a minimally burdensome legal landscape.

Massachusetts has not yet enacted the kind of omnibus AI statutes that appear to be a key focus of the December 2025 Executive Order “Ensuring a National Policy Framework for Artificial Intelligence.” Instead, the state’s current approach leverages existing consumer protection and anti-discrimination statutes rather than creating new AI-specific frameworks. This approach may ultimately prove more resilient to federal pre-emption challenges precisely because it does not create new state laws that can be characterised as specific barriers to AI innovation.

Taken together, Massachusetts’ approach to AI governance reflects a pragmatic and evolving model that relies on the strength of existing legal frameworks, active enforcement, and strategic public investment rather than sweeping new legislation. Through the Attorney General’s emphasis on consumer protection and anti-discrimination, the state has demonstrated a willingness to apply long-standing legal principles to emerging technologies while signalling clear expectations around transparency, accuracy, and risk mitigation. At the same time, ongoing legislative proposals and significant public funding initiatives suggest that Massachusetts is actively positioning itself to shape the next phase of AI governance. As a result, the Commonwealth is likely to remain an influential, if sometimes understated, player in the development of AI policy, bridging innovation and accountability in a manner that may serve as a model for other jurisdictions.