A recent survey by The Futurum Group reveals that 65% of enterprise compute decision makers plan to adopt optical computing to address power and performance bottlenecks in AI infrastructure. The research also highlights significant intent to deploy quantum accelerators and neuromorphic chips as organizations look beyond traditional silicon architectures.
Due to a structural power generation gap where AI infrastructure construction outpaces grid connection timelines, industry professionals expect over 33% of data centers to operate on 100% onsite power by 2030. This shift is driving the adoption of high-efficiency hardware and the movement of AI inference workloads toward the network edge to bypass grid constraints.
Enterprise AI techniques have become so specialized that no single workload type is primary for the majority of enterprise decision-makers. New research from Futurum suggests that enterprises are shifting toward heterogeneous infrastructure optimized for distinct computational profiles including inference, fine-tuning, and domain-specific training.
The AI infrastructure market is undergoing a fundamental architectural shift as agentic AI and reinforcement learning drive a resurgence in CPU demand. This shift has created a supply crisis for high-core-count processors as CPUs evolve from simple head nodes into critical system orchestrators for disaggregated inference.
Futurum's flagship annual foundry research covers TSMC, Samsung, Intel Foundry, [...]
According to a survey by [The Futurum Group](https://futurumgroup.com/press-release/gpu-alternatives-poised-to-outgrow-gpus-in-2026/), enterprise technology leaders plan to increase spending on XPUs by an average of 22.1% in 2026, outpacing the 18.7% growth projected for GPUs. This shift is driven by the demand for specialized processors that offer superior performance-per-watt for specific AI model architectures.
Futurum’s New Silicon Data provides clear visibility into the global AI hardware landscape, combining performance metrics, supply-chain capacity, and vendor analytics in one unified dataset. Covering everything from foundry nodes and HBM packaging to system-level efficiency, it helps executives and investors quantify real performance, cost, and availability risks across competing AI platforms.
The Intel–NVIDIA partnership represents a strategic alignment where NVIDIA gains broader CPU compatibility and AI PC market share, while Intel restores its relevance in AI servers and secures a $5 billion equity stake. This collaboration reshapes competitive dynamics for AMD and Arm, positioning both companies for long-term ecosystem entrenchment.
Futurum research projects that the global data center semiconductor market will grow at a 21.6% CAGR to exceed $500 billion by 2029. The growth is primarily driven by massive investments in AI compute and the expansion of GPU and XPU markets, with NVIDIA maintaining a dominant share.
Futurum’s 2Q 2025 State of the Market Report indicates that the global semiconductor market is on track to reach $1 trillion by 2032. Despite historical volatility, the industry's long-term annual growth rate has stabilized at approximately 6%, driven by consistent R&D investment and AI-driven demand.
