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AI, Semiconductors & Quantum Computing: What Lies in Store for 2027?
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Key Takeaways
AI spending is forecast to reach $3.64 trillion in 2027, making monetization and efficiency key tests.
Semiconductor revenues could hit $1.94 trillion in 2027, with memory chips and fab equipment driving growth.
Quantum revenues are projected to reach $1.1 billion in 2027, led by public-sector spending.
Artificial intelligence (AI) has dominated technology investment in 2026, driving heavy spending on data centers, advanced chips and computing infrastructure. Semiconductor demand has benefited from this expansion, particularly in high-bandwidth memory and advanced manufacturing. Quantum computing, meanwhile, remains an emerging investment opportunity, with companies working to turn research breakthroughs and commercial partnerships into viable businesses.
In 2027, investors are expected to focus more on companies that can convert rising demand for AI, semiconductor and quantum technologies into actual revenue and earnings growth.
The scale of investment is substantial. Gartner forecasts worldwide AI spending of $2.67 trillion in 2026, up 49.5% year over year, in its September report. Its August forecast put global semiconductor revenues at $1.56 trillion in 2026 and $1.94 trillion in 2027. These projections clearly show the economic importance of AI infrastructure. However, they also raise questions about capital efficiency, supply constraints and the sustainability of demand.
Macroeconomic conditions will influence this investment cycle. On Oct. 13, the International Monetary Fund projected global economic growth of 3.1% in 2026, identifying AI investment as a source of support while warning of risks from geopolitical conflict, higher energy prices and rising bond yields. Meanwhile, the Federal Reserve raised its federal funds target range to 3.75%-4% in September, citing elevated inflation. Higher financing costs can weigh on capital-intensive projects and valuations, making investment returns particularly important in 2027.
AI: Monetization Becomes the Key Test
Gartner forecasts worldwide AI spending to reach $3.64 trillion in 2027, with AI infrastructure accounting for approximately $1.98 trillion. AI services and software are also projected to expand, reflecting growing efforts to integrate AI into business applications. Gartner has noted that enterprises are increasingly emphasizing cost control, usage tracking and measurable outcomes.
The key question is whether AI-driven revenue growth and productivity gains can justify the substantial investment in computing infrastructure. In 2027, enterprise adoption, inference demand and the deployment of AI agents are expected to be important indicators to watch. Microsoft (MSFT - Free Report) , through its Azure cloud and AI offerings and Palantir Technologies (PLTR - Free Report) , through its enterprise AI platform, are two companies investors can monitor for evidence of AI monetization, customer adoption and operating efficiency.
Semiconductors: Memory and Manufacturing Take Center Stage
Gartner projects semiconductor revenues to approach $1.94 trillion in 2027, including $1.08 trillion from memory. This forecast highlights the importance of high-bandwidth memory (HBM), DRAM and NAND alongside AI processors. SEMI separately expects global 300mm fab equipment spending to rise 14% to $151 billion in 2027, supported by advanced-node and memory investment.
These projections create opportunities across foundries, chip-design companies and equipment suppliers. Micron Technology (MU - Free Report) , a major memory-chip manufacturer and Lam Research (LRCX - Free Report) , a supplier of semiconductor manufacturing equipment, offer exposure to two important parts of this investment cycle.
Gartner projects global quantum-computing revenues to reach $1.1 billion in 2027, compared with $869.9 million in 2026. It expects public-sector spending to lead industry demand, reaching $245 million in 2027. These figures suggest a developing market rather than widespread commercial adoption.
Investors can monitor IonQ (IONQ - Free Report) , which develops trapped-ion quantum computing systems and D-Wave Quantum, which focuses on quantum annealing and related computing solutions.
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AI, Semiconductors & Quantum Computing: What Lies in Store for 2027?
Key Takeaways
Artificial intelligence (AI) has dominated technology investment in 2026, driving heavy spending on data centers, advanced chips and computing infrastructure. Semiconductor demand has benefited from this expansion, particularly in high-bandwidth memory and advanced manufacturing. Quantum computing, meanwhile, remains an emerging investment opportunity, with companies working to turn research breakthroughs and commercial partnerships into viable businesses.
In 2027, investors are expected to focus more on companies that can convert rising demand for AI, semiconductor and quantum technologies into actual revenue and earnings growth.
The scale of investment is substantial. Gartner forecasts worldwide AI spending of $2.67 trillion in 2026, up 49.5% year over year, in its September report. Its August forecast put global semiconductor revenues at $1.56 trillion in 2026 and $1.94 trillion in 2027. These projections clearly show the economic importance of AI infrastructure. However, they also raise questions about capital efficiency, supply constraints and the sustainability of demand.
Macroeconomic conditions will influence this investment cycle. On Oct. 13, the International Monetary Fund projected global economic growth of 3.1% in 2026, identifying AI investment as a source of support while warning of risks from geopolitical conflict, higher energy prices and rising bond yields. Meanwhile, the Federal Reserve raised its federal funds target range to 3.75%-4% in September, citing elevated inflation. Higher financing costs can weigh on capital-intensive projects and valuations, making investment returns particularly important in 2027.
AI: Monetization Becomes the Key Test
Gartner forecasts worldwide AI spending to reach $3.64 trillion in 2027, with AI infrastructure accounting for approximately $1.98 trillion. AI services and software are also projected to expand, reflecting growing efforts to integrate AI into business applications. Gartner has noted that enterprises are increasingly emphasizing cost control, usage tracking and measurable outcomes.
The key question is whether AI-driven revenue growth and productivity gains can justify the substantial investment in computing infrastructure. In 2027, enterprise adoption, inference demand and the deployment of AI agents are expected to be important indicators to watch. Microsoft (MSFT - Free Report) , through its Azure cloud and AI offerings and Palantir Technologies (PLTR - Free Report) , through its enterprise AI platform, are two companies investors can monitor for evidence of AI monetization, customer adoption and operating efficiency.
Semiconductors: Memory and Manufacturing Take Center Stage
Gartner projects semiconductor revenues to approach $1.94 trillion in 2027, including $1.08 trillion from memory. This forecast highlights the importance of high-bandwidth memory (HBM), DRAM and NAND alongside AI processors. SEMI separately expects global 300mm fab equipment spending to rise 14% to $151 billion in 2027, supported by advanced-node and memory investment.
These projections create opportunities across foundries, chip-design companies and equipment suppliers. Micron Technology (MU - Free Report) , a major memory-chip manufacturer and Lam Research (LRCX - Free Report) , a supplier of semiconductor manufacturing equipment, offer exposure to two important parts of this investment cycle.
Quantum Computing: Commercial Progress Remains Uneven
Gartner projects global quantum-computing revenues to reach $1.1 billion in 2027, compared with $869.9 million in 2026. It expects public-sector spending to lead industry demand, reaching $245 million in 2027. These figures suggest a developing market rather than widespread commercial adoption.
Investors can monitor IonQ (IONQ - Free Report) , which develops trapped-ion quantum computing systems and D-Wave Quantum, which focuses on quantum annealing and related computing solutions.