The race to control the data and infrastructure that powers artificial intelligence is paired with the race to enact laws and policies that will facilitate control of this technological revolution. While the passage of the EU AI Act 2024 marked a high water mark for comprehensive legislation governing AI, the more recent trend is to ease regulatory restrictions on technology in the name of competition and innovation. As the latest Global AI Law and Policy Tracker shows, many countries continue to debate impactful policies and test new governance models as the risks and rewards of AI investments become clearer every day.
steady flow of bills
While the EU is considering suspending implementation of some AI laws, other countries are also working to pass new AI laws. For example, South Korea completed its AI Framework Law in January 2025. The law strengthens transparency and safety requirements and provides a range of incentives, including support for research and development and AI adoption and workforce readiness. Similarly, Japan enacted the AI Promotion Act in May 2025. This is a light regulation that encourages companies to cooperate with government security measures and gives governments the power to publish the names of companies that use AI to violate human rights. Additionally, China has promulgated AI Labeling Regulations, generally requiring service providers to add explicit and implicit labels to AI-generated content, as defined by China’s existing set of AI regulations.
The list of AI bills is even more frightening. These include Argentina’s Personal Data Protection in AI Systems Bill, which seeks to regulate the use of personal data used in the development of AI systems beyond Argentina’s existing data protection laws, and India’s proposed Digital India Act, which aims to update India’s regulatory regime for cyberspace and provide provisions governing AI-generated content. The proposal also includes Brazil’s Bill No. 2. 2338/2023, which creates a risk-based framework that imposes risk assessment and challenge mechanisms on high-risk systems, as well as Vietnam’s AI bill, which emphasizes human-centrism, risk-based management, and differentiation of regulation according to a company’s position in the AI supply chain.
There are also new laws that indirectly impact AI development. Australia has amended its privacy laws to regulate disclosures about automated decision-making, and the UK’s passage of the Data (Use and Access) Act has amended the UK General Data Protection Regulation in ways aimed at fostering innovation and economic growth, including clarifying when personal data can be used for scientific research and liberalizing the legal basis available for automated decision-making.
The rise of AI hubs
While countries are building regulatory guardrails, many are simultaneously expanding policies to attract AI development and infrastructure investment. Chile is one example, ranking first in a Latin American AI index as it expands data center construction, installs additional undersea fiber optic cables, and promotes local AI startups. On the other side of the continent, Brazil plans to invest $4 billion in AI business projects, infrastructure, training initiatives, public service improvements, and regulatory frameworks.
Many Gulf countries aim to become AI hubs as well. For example, the United Arab Emirates hosts a growing startup and research community, as well as cutting-edge supercomputing resources, including Stargate UAE, a partnership between the Emirates, the United States, and OpenAI to build frontier-scale computing capacity in the UAE and enable AI tools across critical sectors. Additionally, Saudi Arabia aims to leverage its young and vibrant population and centralized governance ecosystem to host events, attract investment, and become a leading exporter of data and AI by 2030.
South Korea also aims to become a center of AI innovation. The country has launched a national AI development support platform, the “AI Open Innovation Hub,” and plans to build the world’s highest capacity AI data center.
Signals of deregulation
Of course, signals for deregulation are also on the horizon. Most worrisome is talk that the EU may postpone implementation of AI legislation, summarized in the European Commission’s Digital Omnibus on AI Regulation Proposals published in mid-November 2025. The proposal points to several implementation challenges, including delays in the designation of competent authorities and a lack of uniform standards for high-risk AI requirements and necessary guidance tools. Several changes to the law were proposed, including delaying the start-up of provisions governing high-risk AI systems to align enforcement with the availability of compliance tools. Other proposed amendments include relaxing documentation requirements for small businesses and increasing the Office of AI’s oversight authority over general-purpose AI models. Although this proposal is just a suggestion, it foreshadows future negotiations over the implementation and regulatory implications of the AI Act.
Additionally, the Australian Productivity Commission released a report that partially avoids over-regulation of AI. The report points to the chilling effect that burdensome regulation has on investment and emphasizes the importance of pursuing regulatory goals at the lowest possible cost to innovation. Similarly, Canada’s Competition Bureau released a report showing that regulations specific to the AI sector can hinder innovation, burden growth, and create barriers to entry for startups.
The United States is also at the forefront of the deregulation trend, with President Donald Trump issuing executive orders to remove barriers to AI development and foster innovation, as well as executive orders aimed at unlocking prosperity through deregulation. These executive orders herald the administration’s AI Action Plan, which aims to accelerate innovation and build infrastructure by removing bureaucracy and burdensome regulations. Additionally, a December 2025 executive order outlines further efforts by the White House to limit state AI laws in the United States.
Governance by standards
In the absence of binding legislation, operational and technical standards continue to fill the void, not to mention avoiding the pitfalls of traditional lawmaking. For example, the Government of Canada established the AI and Data Standards Collaborative to develop standards based on tested, multi-stakeholder needs and ensure consistency across national and international frameworks. This collaboration advances the idea that standards make products and services safer while also fostering innovation.
The Australian Department of Industry, Science and Resources has released a voluntary AI safety standard. It consists of 10 guardrails for developing safe and responsible AI, including requirements for testing, transparency, and accountability. The standard aims to balance risk and reward to ensure reliable AI in high-risk environments, while also enabling AI to thrive in low-risk environments.
Other countries working in this area include China, where the Standards Bureau has announced three standards to improve the security of generated AI, and India, where the Ministry of Electronics and Information Technology is working with industry players to develop various standards on metrics such as reliability, explainability, and privacy. Similarly, the Kenya Bureau of Standards has released a draft IT AI Code of Practice that provides guidance for AI applications based on a common framework. Additionally, the UK’s AI Standards Hub is an initiative dedicated to global AI standardization.
Copyright questions
The use of copyrighted data to train AI systems remains a contentious legal issue. Recent developments on this front include a public consultation process initiated by Hong Kong’s Department of Business and Economic Development and the Intellectual Property Department to assess potential updates to copyright law to create exceptions for the analysis and processing of computational data. Along these lines, the U.S. District Court for the Northern District of California has determined that training an AI model based on a copyrighted work likely constitutes fair use. However, the court also found that storing the same works in a central library constitutes fair use only if those works were obtained legally.
Less recently, but relatedly, Japan has amended its copyright law to allow the use of copyrighted works for the purpose of developing or training AI, as long as the purpose is not to reproduce the expressive content of the copyrighted work. Additionally, the Israeli Ministry of Justice issued an opinion stating that the use of copyrighted material for machine learning purposes is permissible.
continued international cooperation
Amid these policy decisions, international cooperation on AI governance continues. Singapore has distinguished itself as a diplomatic leader, announcing a commitment with the United States to create interoperability between the two countries’ governance frameworks and signing agreements to cooperate on AI safety and innovation with Australia and the EU AI Secretariat. Similarly, Brazil’s data protection authority, the Dados National Protection Agency, met with France’s DPA, the National Freedom of Information Commission, to strengthen cooperation on AI, data protection, and digital education. Additionally, Brazil and Nigeria signed a memorandum of understanding to strengthen cooperation on AI development and technology transfer. Additionally, Canada has joined several other G20 countries in drafting a set of principles to guide the adoption of AI in the telecommunications industry, focusing on growth, security and social benefits. Finally, the UK and Qatar pledged to strengthen cooperation in AI research.
conclusion
Despite the emerging trend of deregulation, laws and policies governing AI continue to proliferate, even in new and creative expressions. While some jurisdictions continue to debate comprehensive legislation and others consider the effectiveness of standards, most jurisdictions remain convinced that international cooperation and diplomacy are essential to the successful governance of this disruptive technology. Stay up to date on evolving policy positions by following IAPP’s Global AI Law and Policy Tracker.
Will Simpson, AIGP, CIPP/US, is a Westin Fellow at IAPP.
