The Semiconductor Surge: Assessing AI-Driven ETF Outperformance and Future Risks

The VanEck Semiconductor ETF (SMH) surged by 48.7% in 2025, a performance fueled by the AI infrastructure boom and the meteoric rise of key semiconductor players like Micron, TSMC, and AMD. This outperformance reflects a broader structural shift in the tech sector, where AI model development and monetization are accelerating faster than anticipated, creating insatiable demand for GPUs, ASICs, and custom silicon. However, as investors look ahead to 2026, the question remains: Can this momentum sustain itself, or are the risks of overreliance on AI progress and OpenAI's spending trajectory beginning to materialize?

The AI Infrastructure Boom: A Tailwind for Semiconductors

The AI-driven demand for semiconductors is rooted in the energy-intensive nature of training and deploying large models. U.S. cloud providers are projected to spend $600 billion on AI infrastructure in 2026, doubling their 2024 outlays. OpenAI, a pivotal player in this ecosystem, has outlined ambitious infrastructure goals, including adding 100 gigawatts of new grid capacity annually starting in 2026 to close the "electron gap" with China. This demand is not merely speculative: AI workloads are expected to consume over half of data center electricity by 2028, driven by the 80–90% share of computing dedicated to model training and inference.

For SMH, the ETF's exposure to companies like Micron, TSMC, and AMD has been a double-edged sword.

Micron, the ETF's fourth-largest holding, saw its stock surge 240.2% in 2025 as AI demand spiked for DRAM and NAND memory. TSMC, meanwhile, has leveraged its leadership in advanced manufacturing to secure contracts with AI chipmakers like NVIDIA, with its 3nm process capacity projected to exceed 200,000 wafers monthly by year-end 2026. AMD's position as a second-source supplier for AI GPUs has also bolstered its performance, reflecting the sector's diversification beyond a single dominant player.

Sustainability of Demand: Energy, Efficiency, and Innovation

The sustainability of AI-driven semiconductor demand hinges on two critical factors: energy infrastructure and technological efficiency. Data center electricity consumption is expected to surpass 1,000 terawatt-hours (TWh) by 2026, nearly doubling 2022 levels. By 2028, AI-specific servers alone could consume 165–326 TWh annually, straining grids and challenging sustainability goals. To mitigate this, major tech firms are investing in clean energy partnerships. For instance, Microsoft's collaboration with Constellation Energy to power data centers with nuclear energy underscores the sector's pivot toward decarbonization.

However, energy consumption is only one side of the equation. Innovations in demand response, grid integration, and energy-efficient algorithms are critical to reducing waste and emissions. TSMC's transition to 2nm and A16 (1.6nm) nodes, coupled with its advanced packaging capabilities (e.g., CoWoS), exemplifies how manufacturing efficiency can offset energy costs. Similarly, Micron's ability to meet only half to two-thirds of customer demand for DRAM in 2026 highlights the sector's capacity constraints, even as HBM sales are already sold out for the year.

Risks on the Horizon: Overreliance and Supply Chain Vulnerabilities

Despite the sector's robust fundamentals, risks loom large. OpenAI's $1.4 trillion spending plan over the next eight years, while ambitious, introduces volatility if the company faces financial or competitive challenges. Moreover, the semiconductor industry's reliance on a handful of AI-driven workloads-such as large language models-leaves it exposed to a slowdown in AI progress or regulatory headwinds.

Supply chain instability and talent shortages further complicate the outlook. TSMC's $50 billion capital expenditure plan for 2026, aimed at scaling 2nm and 3nm production, is a testament to the industry's need for continuous investment. Yet, such spending requires stable demand and geopolitical cooperation, both of which are uncertain in a fragmented global landscape.

Conclusion: A High-Conviction Bet with Caveats

The VanEck Semiconductor ETF's 2025 performance was a masterclass in thematic investing, capitalizing on the AI infrastructure boom. With TSMC projected to grow 31% in 2026 and Micron's DRAM demand remaining resilient, the ETF is well-positioned to continue outperforming in the near term. However, investors must remain vigilant. The sector's long-term success depends on balancing AI's insatiable appetite for compute with sustainable energy solutions and diversified demand. While the fundamentals are strong, the risks of overreliance on OpenAI's spending trajectory and the energy transition cannot be ignored. For now, SMH remains a compelling play on the AI revolution-but one that demands careful monitoring.