Assessing Legal and Regulatory Risks in the U.S. AI Sector: Trump's AI Action Plan and Its Long-Term Implications

The U.S. artificial intelligence (AI) sector stands at a pivotal juncture, shaped by the Trump administration's ambitious AI Action Plan. Unveiled in July 2025, the plan prioritizes deregulation, infrastructure expansion, and global competitiveness, but it also raises critical legal and regulatory risks for investors. From environmental litigation to intellectual property (IP) disputes, the plan's aggressive policy shifts could redefine the sector's landscape—and its long-term viability.

The Trump AI Action Plan: A Deregulatory Push

The plan's three pillars—Accelerating Innovation, Building Infrastructure, and Leading Internationally—are designed to fast-track U.S. AI leadership. However, this approach introduces legal risks that infrastructure developers, data center operators, and IP stakeholders must navigate.

1. Environmental Litigation and NEPA Reforms
   The plan proposes streamlining federal permitting for data centers and semiconductor manufacturing by expanding Title 41 (FAST-41) and creating NEPA categorical exclusions for AI infrastructure projects. While this accelerates development, it risks triggering lawsuits from environmental groups. For example, the proposed nationwide Clean Water Act Section 404 permit for data centers—which would bypass pre-construction environmental reviews—could face challenges under the Endangered Species Act or state-level environmental statutes.

**

Investors in data center developers like Digital Realty (DLR) or Equinix (EQIX) should monitor litigation trends. A 2023 study by the Brookings Institution found that 60% of major infrastructure projects face delays due to environmental lawsuits.

1. Intellectual Property Conflicts in Open-Source AI
   The plan encourages the development of open-source and open-weight AI models to foster innovation. While this democratizes access, it also creates IP risks. Open-source licensing (e.g., Apache 2.0, MIT) often requires derivative works to remain open, which could clash with proprietary strategies. For instance, companies like NVIDIA (NVDA) and AMD (AMD), which rely on licensed AI chip architectures, may face disputes over IP ownership if competitors exploit open-source models to bypass patents.

Additionally, the “Preventing Woke AI” executive order mandates that federal agencies only procure “ideologically neutral” AI models. This could lead to legal challenges over bias claims, as seen in recent lawsuits against Microsoft and Google over AI-generated content.

1. Data Privacy and Cross-Border Conflicts
   The plan's focus on exporting American AI technology stacks to allies raises data privacy concerns. While the U.S. lacks a federal data privacy law akin to the EU's GDPR, the plan's emphasis on “secure-by-design” AI may inadvertently expose companies to international litigation. For example, AI systems trained on U.S. data and deployed abroad could violate foreign data localization laws, such as India's Digital Personal Data Protection Act or China's Data Security Law.

Investors in AI-as-a-Service providers like IBM (IBM) or Salesforce (CRM) must weigh the risk of cross-border compliance costs.

**

Strategic Risks for Infrastructure Developers

The plan's push to expand data center infrastructure using federal lands and energy subsidies is a double-edged sword. While it reduces upfront costs, it also exposes developers to:
- Land Use Disputes: Projects on federal lands may face opposition from tribal groups or conservation organizations.
- Energy Grid Strain: Upgrading the U.S. electric grid to support AI infrastructure could lead to regulatory delays or rate hikes for energy providers.
- Cybersecurity Vulnerabilities: The plan's focus on “secure-by-design” AI may not address systemic risks in supply chains, such as vulnerabilities in third-party semiconductors.

Investment Implications and Mitigation Strategies

For investors, the Trump AI Action Plan creates both opportunities and risks. Here's how to navigate them:

1. Hedge Against Environmental Litigation
   Prioritize companies with strong ESG (Environmental, Social, Governance) ratings or those investing in green data center technologies. For example, NextEra Energy (NEE) is expanding renewable energy solutions for AI infrastructure, positioning itself as a low-risk player.

1. Diversify IP Portfolios
   Encourage companies to secure patents in niche AI applications (e.g., biosecurity, autonomous systems) rather than relying solely on open-source models. This reduces exposure to IP conflicts.

2. Monitor Global Data Privacy Trends
   Invest in AI companies with robust compliance frameworks for international markets. For instance, Snowflake (SNOW) has tailored data governance solutions for EU and APAC clients, mitigating cross-border risks.

**

Conclusion: A High-Risk, High-Reward Sector

The Trump AI Action Plan is a bold bet on deregulation and global dominance, but its long-term viability hinges on managing legal and regulatory risks. Investors who align with the plan's goals while hedging against environmental, IP, and privacy challenges will be best positioned to capitalize on the AI boom. As the sector evolves, vigilance and adaptability will be key to navigating the shifting regulatory landscape.