Transformative Changes in AI Infrastructure
The AI Factory market is entering a new era of industrialization, with Omdia identifying five key dynamics reshaping AI infrastructure in 2026. This shift is marked by significant investments and evolving operational challenges.
Cumulative global data centre investment is projected to reach $1.6 trillion by 2030. Leading technology enterprises are expected to allocate over $600 billion to AI infrastructure capital expenditure in 2026. This indicates a transition to a high-capital, geopolitically sensitive market.
An AI Factory is defined by Omdia as a new form of heavy industrial infrastructure aimed at intelligence production. It operates using a four-layer architecture: energy and physical infrastructure, hardware and networking, scheduling and orchestration, and AI application ecosystems.
Key Dynamics in 2026
Omdia’s survey of over 200 companies identifies challenges such as long time-to-market, digital sovereignty, AI talent gaps, and systemic engineering complexity. In response, Omdia highlights five dynamics shaping the industry: shifting evaluation metrics, balancing agility with sovereignty, upgrading AI cloud capabilities, capturing the ‘last mile’ of industrialization, and the rise of sovereign data factories.
Shifting evaluation metrics involve changes from FLOPS to Time-to-First-Token, with reported gains such as a 12x vector indexing speed-up. Also, up to a 75% cost reduction on API and compute redundancy is being observed in vendor case studies.
Hyperscalers are balancing agility and sovereignty through two delivery paradigms: full-stack drop-in, featuring cloud-grade AI capabilities, and software/hardware decoupling, emphasising localization of software capabilities.
AI cloud upgrades are notable as rack power density increases from 10–15 kW in 2024 to 40–250 kW by 2026. Companies like Nebius and Sensetime have already shifted their models from Bare Metal leasing.
Raymond Zhan, Senior Principal Analyst at Omdia, stated, “Future competition will no longer be defined by model parameters or GPU counts, but by a comprehensive contest of energy, liquid cooling, chips, autonomous software stacks, sovereign compliance, and long-term capital endurance.”
The report ‘Global AI Factory Market Landscape 2026’ offers a detailed analysis of these dynamics and their implications for AI infrastructure development. The coming years, particularly 2026 and 2027, are expected to be crucial for the growth of regional and industrial operations.
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Last updated: 29 June 2026, 11:58 am
