OpenAI Requests CHIPS Act Expansion for AI Data Centers - Policy and Market Impact Analysis

This analysis is based on recent reports from Bloomberg [1] and other sources published on November 7, 2025, detailing OpenAI’s request to expand CHIPS Act tax credits to cover AI data centers and infrastructure. OpenAI Chief Global Affairs Officer Chris Lehane sent a letter to the White House requesting that the Advanced Manufacturing Investment Credit (AMIC) be broadened from its current semiconductor focus to include AI data centers, server production, and electrical grid components [1][3]. The proposal aims to support OpenAI’s massive $1.4 trillion commitment to computational resources over the next eight years [4], potentially reshaping the competitive landscape for AI infrastructure while raising important policy questions about government subsidies and market sustainability.

OpenAI’s request seeks to leverage existing CHIPS Act infrastructure that was significantly expanded in July 2025, when the Advanced Manufacturing Investment Credit was increased from 25% to 35% for qualified semiconductor projects beginning construction before the end of 2026 [5][7]. The current AMIC applies to tangible property used in advanced manufacturing facilities placed in service after December 31, 2022 [10]. However, expanding coverage to data centers would likely require legislative action, as the Treasury Department currently has limited discretion to interpret the law’s scope [9].

The proposal represents a significant policy shift from semiconductor manufacturing to downstream infrastructure applications. OpenAI argues that such expansion would “lower the effective cost of capital, de-risk early investment, and unlock private capital” for AI infrastructure development [3]. The company frames this as essential for maintaining U.S. competitiveness against infrastructure expansion in China and Gulf states [9].

The hyperscale data center market is experiencing explosive growth, valued at $209.2 billion in 2024 and projected to reach $724.9 billion by 2030, representing a 23% compound annual growth rate [6]. This expansion is primarily driven by increasing demand for AI workloads, cloud computing, and big data analytics [6]. Major cloud providers are making substantial investments, with Microsoft alone planning to invest $80 billion in AI data centers in 2025 [8].

The AI semiconductor market is dominated by NVIDIA, which commands an estimated 85-94% market share in AI GPUs as of November 2025 [11]. However, the sector has experienced significant volatility in early November 2025, with NVIDIA losing approximately $450 billion in market capitalization over a three-day period, sparking discussions of a potential “AI bubble” [12]. This volatility underscores the market’s sensitivity to policy developments and infrastructure investment patterns.

OpenAI’s letter specifically highlights critical bottlenecks in the electrical grid supply chain, including transformers, HVDC converters, switchgear, and transmission lines, which currently have lead times measured in years rather than months [9]. The company argues that federal support could help shorten these lead times and ensure sufficient scale for critical components [9].

The AI infrastructure boom is placing unprecedented demands on electrical grids. Goldman Sachs projects that $720 billion in global grid investment will be needed through 2030 to meet rising AI-driven demand [8]. This has led to increased interest from investors entering the market through joint ventures, utility spin-offs, and Independent Power Producers (IPPs) [8].

The policy proposal reveals deep interdependencies between AI development, semiconductor manufacturing, and electrical infrastructure. OpenAI’s request underscores that AI advancement is not just about chips but requires comprehensive infrastructure support including power grids, cooling systems, and specialized electrical equipment. This creates opportunities across multiple sectors but also amplifies systemic risks if any component faces constraints.

OpenAI’s internal analysis predicts that a $1 trillion investment in AI infrastructure could boost GDP by 5% or more in the first three years [2]. This suggests significant economic multiplier effects that could justify policy support, though these projections need careful validation given the rapidly evolving nature of AI technology and potential implementation challenges.

The proposed tax credit expansion could significantly reshape competitive dynamics among data center providers. Current market leaders including Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, IBM Cloud, and Oracle Cloud Infrastructure [8] are engaged in massive capacity expansion. Tax credits could alter the economics of these investments, potentially favoring companies with better access to capital and more sophisticated tax planning capabilities.

The expansion of CHIPS Act credits to data centers would require congressional approval, introducing significant political risk. The current administration’s support for AI leadership may not translate into bipartisan legislative action, particularly given concerns about corporate subsidies and taxpayer exposure. Even if approved, implementation would require complex regulatory guidance from the Treasury Department [10].

The rapid pace of AI technology evolution means that infrastructure built today may become obsolete relatively quickly. Tax credits that lock in specific technology approaches could inadvertently support less optimal solutions as the technology continues to evolve. This creates a policy challenge of supporting current infrastructure needs without anchoring the industry to potentially outdated approaches.

Recent market volatility suggests concerns about the sustainability of current AI investment levels [12]. While tax credits could improve the economics of AI infrastructure investments, they may also create dependencies on government support that could prove politically fragile over time. The policy could inadvertently mask underlying market fundamentals and create investment distortions.

For companies positioned to benefit from the policy changes, the expansion could provide significant competitive advantages. A 35% tax credit on data center construction and equipment would effectively reduce the cost basis of these investments by more than one-third, potentially accelerating deployment timelines and improving return on investment calculations. This could be particularly beneficial for companies with strong balance sheets and existing infrastructure expertise.

OpenAI’s request to expand CHIPS Act tax credits represents a significant development in AI infrastructure policy, seeking to broaden the current 35% semiconductor-focused tax credit to include AI data centers, server production, and electrical grid components [1][3]. The proposal addresses real challenges in financing massive AI infrastructure investments, with OpenAI committing $1.4 trillion over eight years [4], while highlighting critical supply chain bottlenecks in electrical components [9].

The hyperscale data center market is projected to grow from $209.2 billion in 2024 to $724.9 billion by 2030 [6], driven by AI workload demands. The policy could benefit semiconductor manufacturers, data center providers, and electrical equipment suppliers, but raises questions about the appropriate role of government subsidies and the sustainability of current investment patterns amid recent market volatility [12].

Stakeholders should monitor legislative developments closely, as the proposal requires congressional action and faces implementation challenges. The policy’s success will depend on balancing support for AI competitiveness with concerns about market distortions and political sustainability of subsidies.