TSMC Accelerates Capacity Expansion Amid Rising AI Demand
Written by Emily J. Thompson, Senior Investment Analyst
Updated: Feb 02 2026
0mins
Should l Buy NVDA?
Source: Benzinga
- Capacity Expansion Pressure: TSMC is under significant pressure to expand its production capacity due to surging AI chip demand from Nvidia, with CEO Jensen Huang stating that TSMC needs to double its chip production capacity over the next decade to meet rising needs.
- Increased Capital Expenditure: TSMC plans to raise its capital spending to $56 billion in 2023, a 37% increase from last year, with expectations for significant growth again in 2028 and 2029 to support its expansion strategy.
- Customer Relationship Shift: Nvidia has become TSMC's largest customer, dethroning Apple, which is reassessing its partnership with TSMC and considering moving some low-end processor production to alternative suppliers, ending over a decade of exclusive cooperation.
- Market Reaction: In premarket trading on Monday, Nvidia shares fell 2.05% to $187.21, Apple dipped 0.42% to $258.39, and TSMC also traded lower, down 1.15% at $326.75, reflecting market concerns about future growth.
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Analyst Views on NVDA
Wall Street analysts forecast NVDA stock price to rise
41 Analyst Rating
39 Buy
1 Hold
1 Sell
Strong Buy
Current: 175.750
Low
200.00
Averages
264.97
High
352.00
Current: 175.750
Low
200.00
Averages
264.97
High
352.00
About NVDA
NVIDIA Corporation is an artificial intelligence (AI) infrastructure company. The Company is engaged in accelerated computing to help solve the challenging computational problems. Its segments include Compute & Networking and Graphics. The Compute & Networking segment includes its Data Center accelerated computing and networking platforms and AI solutions and software, and automotive platforms and autonomous and electric vehicle solutions, including software. The Graphics segment includes GeForce GPUs for gaming and personal computers (PCs), and Quadro/NVIDIA RTX GPUs for enterprise workstation graphics. Its technology stack includes the foundational NVIDIA CUDA development platform that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, frameworks, algorithms, software development kits (SDKs), and application programming interfaces (APIs). Its platforms address four markets, which include Data Center, Gaming, Professional Visualization, and Automotive.
About the author
Emily J. Thompson
Emily J. Thompson, a Chartered Financial Analyst (CFA) with 12 years in investment research, graduated with honors from the Wharton School. Specializing in industrial and technology stocks, she provides in-depth analysis for Intellectia’s earnings and market brief reports.
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- Surging Order Forecast: CEO Jensen Huang indicated that Nvidia expects approximately $1 trillion in purchase orders for its Blackwell and Vera Rubin chips by 2027, doubling last year's forecast of $500 billion, signaling sustained strong demand for AI chips.
- Future Revenue Expectations: Nvidia anticipates first-quarter revenue of $78 billion for fiscal year 2027, representing an almost 77% increase compared to the same period last year, reflecting strong growth potential in the Agentic AI applications sector, which will further drive demand for AI chips.
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- Historical Performance Insight: Since the AI arms race began in 2023, Nvidia has experienced four 20% pullbacks, each followed by a new all-time high within six months, demonstrating its strong recovery capability and market potential.
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- AI Spending Outlook: 2026 is projected to be another record year for capital expenditures, and despite cautious market attitudes towards AI spending, demand for AI continues to rise, suggesting significant growth potential for Nvidia in the coming years as elevated AI spending is crucial for achieving future goals.
- Valuation Appeal: Nvidia's current price-to-earnings ratio stands at 19.9, lower than the S&P 500's 20.4, with Wall Street forecasting a 71% revenue growth this year and 30% next year, indicating that Nvidia's stock could rebound to new highs as long as AI spending remains robust.
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