How do governments regulate AI compared with other industries?

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1. 1

   Regulation of artificial intelligence (Wikipedia)

   WikipediaPublished Oct 12, 2026Checked Oct 14, 2026

   “Regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating artificial intelligence (AI). The regulatory and policy landscape for AI is an emerging issue in jurisdictions worldwide, including for international organizations without direct enforcement power like the IEEE or the OECD. Since 2016, numerous AI ethics guidelines have been published in order to maintain social control over the technology. Furthermore, organizations deploying AI have a central role to play in creating and implementing trustworthy AI, adhering to established principles, and taking accountability for mitigating risks. The European Union adopted in 2024 a common legal framework for AI with the AI Act. AI governance is a term used in policy, industry, and academic contexts to describe how AI systems are directed and overseen. A 2025 systematic literature review defined it as encompassing the questions of who is accountable for AI systems, what elements are governed, when governance occurs within the development lifecycle, and how it is implemented through frameworks, tools, or models.”

2. 2

   Regulation of artificial intelligence in the United States (Wikipedia)

   WikipediaPublished Oct 12, 2026Checked Oct 14, 2026

   “The United States federal government and state governments have developed some regulation of artificial intelligence, including executive orders, federal laws, and state laws. Federal agencies have also developed some sector-specific regulations related to AI. At the federal level, the Biden administration released an October 2023 executive order about AI safety and security, Executive Order 14110, with directives related to AI development and deployment. President Trump revoked that executive order in January 2025 and issued Executive Order 14179. In December 2025, President Trump signed Executive Order 14365, an executive order directing federal agencies to develop a unified national approach to AI policy, evaluate state AI laws for potential conflicts, challenge them through legal action, and condition certain federal funding on state compliance, while exempting state laws related to child safety, data center infrastructure, and state government procurement. In 2025, Congress passed legislation targeting AI-generated deepfakes, the TAKE IT DOWN Act. Several U.S. states have enacted laws related to artificial intelligence. Some are already in effect, including in California.”

3. 3

   High-risk without safeguards? The EU AI Act and the push for deregulation of medical AI.

   BMJ digital health & AI (Van et al.)Published Sep 30, 2026Checked Oct 14, 2026

   “This narrative review analyses the Health Innovation Package and related legislative developments under the EU simplification agenda and examines their impact on the relationship between the AI Act and medical device law. It shows that the proposed reform would retain the high-risk classification of AI-enabled medical devices while removing most associated AI Act obligations. In effect, this decouples risk classification from the safeguards that give it regulatory meaning, including requirements on data governance, risk management, human oversight and postmarket monitoring. Rather than resolving regulatory overlap, the amendments shift the centre of gravity back to product-focused medical device law without ensuring equivalent AI-specific safeguards. These changes may narrow attention to fundamental rights, weaken oversight in clinical use and increase legal uncertainty regarding accountability and responsibility. In a domain where AI systems directly shape clinical decisions and patient outcomes, these changes risk undermining the conditions for safe, equitable and accountable deployment of medical AI.”

4. 4

   When hospitals build their own AI: a comparison of the EU and US regulatory framework.

   BMJ digital health & AI (Palmieri et al.)Published Sep 17, 2026Checked Oct 14, 2026

   “Hospitals are increasingly shifting from being passive purchasers of artificial intelligence (AI) systems to active developers of medical AI, particularly in the form of in-hospital machine learning tools tailored to local clinical needs. This paper examines how the European Union (EU) and the USA regulate in-hospital-developed AI-based medical devices, focusing on the legal and institutional conditions that shape innovation, oversight and diffusion. Through a comparative analysis across three dimensions-responsiveness to clinical need, distribution of innovative capacity and pathways for scaling and diffusion-the paper shows that both systems enable hospital-based innovation but embed it in different regulatory logics. The EU adopts a structured model that treats hospitals as regulated innovators operating under defined institutional obligations, whereas the USA relies on a more permissive and less institutionally differentiated framework in which hospital innovation emerges as a by-product of general software regulation.”

5. 5

   Algorithmic governance at work: a legal-sociological and policy analysis of AI regulation, institutional power and labor rights.

   Frontiers in sociology (Olimid et al.)Published Aug 19, 2026Checked Oct 14, 2026

   “The results indicate that AI regulation across Europe, the Americas, and the Asia-Pacific is increasingly intersecting around human rights and personal data protection, risk-based governance, and accountability mechanisms, particularly in the employment environment. Legal frameworks emphasize transparency, non-discrimination, and the need for human oversight in AI-powered workplace decisions.ConclusionThe conclusions highlight that across Europe, the Americas and the Asia-Pacific, AI regulation is increasingly organized around six dimensions: protection of human rights and data privacy in the workplace; governance frameworks addressing reskilling, job transformation and adaptation to AI-driven work models; risk-based oversight of AI systems; AI civil liability regimes affecting employee rights and HR practices; promotion of ethical AI to foster trust and mitigate bias; and strengthened monitoring, accountability and non-discrimination mechanisms.”

6. 6

   Governing AI for Mental Health: Fragmented State Approaches and the Case for a Federal Framework.

   JMIR mental health (Aldhalimi)Published Jul 28, 2026Checked Oct 14, 2026

   “This Viewpoint aims to identify the governance approaches that US states are using to regulate the use of AI in mental health and analyze the limitations of each. A 4-state case analysis was conducted using the statutory text of bills and laws in Illinois, Utah, New York, and Nevada. Two governance approaches were identified. The first regulates the use of AI in clinical contexts, and the second regulates the technology itself. Some states have combined elements of both approaches to address AI use more comprehensively. While these approaches aim to mitigate harm, they differ in where they believe risk lies in the use of AI for mental health support. The limitations of these divergent approaches include uneven protections for consumers and regulatory uncertainty for developers, vendors, deployers, and clinicians. Because AI in mental health operates across both clinical and consumer domains, neither approach alone can address the risks associated with its use for mental health support. A coordinated, risk-based federal regulatory floor is needed to ensure consistent protections across states.”

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   AI is less regulated than milk, says Microsoft president

   BBC NewsPublished Oct 12, 2026Checked Oct 14, 2026

   “Brad Smith calls for global rules on AI, and says the UK is in the "best position" to lead the charge.”