OpenAI CEO requests U.S. expand eligibility for Chips Act credit, Reuters says

AI Hardware Tax Credit: 2025 Chips Act Expansion and Economic Impact { "@context": "https://schema.org", "@type": "TechArticle", "headline": "AI Hardware Tax Credit: 2025 Chips Act Expansion and Economic Impact", "description": "A deep dive into the expanded AI hardware tax credit, its macro‑economic implications, competitive dynamics, and actionable guidance for semiconductor leaders.", "author": {"@type":"Organization","name":"TechForward Media"}, "datePublished": "2025-11-10", "mainEntityOfPage": {"@type":"WebPage","@id":"#"} } AI Hardware Tax Credit: 2025 Chips Act Expansion and Economic Impact Executive Summary Policy Context Macro‑Economic Implications Competitive Dynamics Financial Mechanics & Eligibility Risk Assessment Strategic Recommendations Future Outlook In 2025, the U.S. Treasury is poised to broaden the Chips Act’s Semiconductor Investment Tax Credit (SITC) into a dedicated AI hardware tax credit . This shift reflects the unique capital intensity of large‑language‑model (LLM) training and inference workloads and promises to reshape the domestic semiconductor landscape. Executive Summary $3–4 billion annual AI hardware tax credit targeting firms that design or manufacture silicon for LLM workloads. Eligibility requires: Verified use of chips in AI training/inference (benchmarks, deployment logs). Minimum 100 million units per year. A five‑year domestic supply‑chain partnership with U.S. suppliers. The credit could lift U.S. AI‑chip production share from ~15% to 25–30%, improving the trade balance and creating up to 30,000 skilled jobs over five years. Competitive parity with China’s $5 billion subsidy and Europe’s €3 billion Horizon Europe program. Policy Context: From Broad Semiconductor Incentives to AI‑Specific Subsidies The original Chips Act (2021) offered a generic $7 billion credit for semiconductor fabs meeting technology thresholds. However, LLM workloads demand extreme compute density, low latency, and sustained power consumption—requirement