The Strategic Case for Expanding AI Infrastructure Tax Credits and Its Impact on U.S. Tech Dominance

The U.S. is at a pivotal juncture in its quest to maintain global leadership in artificial intelligence. While the CHIPS and Science Act of 2022 has laid the groundwork for domestic semiconductor manufacturing, its indirect support for AI infrastructure remains insufficient to address the sector's evolving needs. As private investment in AI surges-reaching $252.3 billion globally in 2024, according to the 2025 AI Index Report-the federal government must expand tax incentives beyond semiconductors to catalyze private-sector innovation and secure long-term dominance in AI.

The CHIPS Act: A Semiconductor-First Approach

The CHIPS Act's 25% Advanced Manufacturing Investment Tax Credit (AMITC) has incentivized companies to invest in semiconductor production, indirectly bolstering AI infrastructure by ensuring access to foundational hardware, according to the Tax Adviser. For instance, firms like Rightmove have allocated £18 million to AI development in 2026, leveraging such incentives to digitize processes. However, the Act's narrow focus on semiconductors overlooks other critical AI infrastructure components, such as cloud computing, data centers, and specialized software tools.

While the CHIPS for America Fund has allocated $49.5 billion for semiconductor facilities, according to the Tax Adviser, the U.S. still lags in AI-specific incentives compared to its global competitors. For example, China and the EU have not been explicitly analyzed for AI tax credits in the provided data, but their aggressive investments in AI research and development suggest a growing gap in U.S. policy alignment.

Gaps in U.S. Policy and the Need for AI-Centric Incentives

The Biden administration's CHIPS Act and the Trump-era tariff policies have created a fragmented landscape for AI infrastructure. While tariffs aim to incentivize domestic manufacturing, they risk inflating costs for companies like TSMC, whose U.S. expansion could see a $6.4 billion price hike due to a 10% tariff on materials, according to Sourceability. Meanwhile, the rescission of Biden-era export restrictions on AI chips has introduced compliance uncertainty, complicating long-term planning for firms, according to Sourceability.

Moreover, federal R&D funding for AI remains far below the National Security Commission on Artificial Intelligence's (NSCAI) $16 billion target for FY25, with only $3.3 billion allocated in 2025, according to the Tax Adviser. This underinvestment in foundational research-critical for advancements in AI interpretability and cybersecurity-leaves the U.S. reliant on private-sector commercialization efforts, which prioritize short-term gains over long-term innovation.

The Global AI Investment Landscape and U.S. Leadership

The U.S. currently leads in AI investment, with private funding reaching $109.1 billion in 2024-triple that of China and the UK, according to the 2025 AI Index Report. This dominance is driven by a combination of federal incentives and private-sector agility, as seen in companies like C3 AI, which has expanded its AI solutions across defense, banking, and utilities, according to Business Wire. However, the lack of AI-specific tax credits beyond semiconductors risks ceding ground to nations with more holistic policies.

For example, while the Inflation Reduction Act (IRA) offers broad incentives for clean energy and EVs, according to the Deloitte Tax Article, it lacks targeted provisions for AI infrastructure. In contrast, states like Ohio and New York have allocated billions in semiconductor incentives, according to the Deloitte Tax Article, but these efforts remain siloed and insufficient to address the full spectrum of AI needs.

Strategic Recommendations for Expanding Tax Credits

To secure U.S. leadership, policymakers should:
1. Expand AI-Specific Tax Credits: Introduce direct incentives for cloud computing, data center construction, and AI software development, mirroring the CHIPS Act's success in semiconductors.
2. Harmonize Federal and State Incentives: Create a unified framework to prevent policy fragmentation and reduce compliance costs for firms.
3. Boost Federal R&D Funding: Align with NSCAI targets to ensure foundational research keeps pace with commercialization efforts.

Conclusion

The CHIPS Act has been a catalyst for semiconductor manufacturing, but its indirect support for AI infrastructure is no longer sufficient. As global competition intensifies and private investment surges, the U.S. must adopt a more comprehensive approach to AI tax incentives. By expanding policy-driven support beyond semiconductors, the nation can secure its position as the global AI leader while addressing critical gaps in workforce development, research, and infrastructure.