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Cumulative investment in global data centres to hit $1.6 trillion by 2030

Cyprus Mail · 2026-06-15

AI SUMMARY

• What happened: Global investment in data centre infrastructure is projected to reach $1.6 trillion by 2030, with over $600 billion expected to be spent on artificial intelligence capital expenditures in 2026, according to Omdia. • Why it matters: This investment marks a significant shift in the data centre landscape, transforming them from support hubs into sophisticated digital manufacturing centres for AI, while also addressing challenges such as digital sovereignty and talent shortages. • What to watch next: The years 2026 and 2027 are anticipated to be crucial for data centre expansion, with regional and industrial operations likely to become key growth sectors as demand for data processing and AI capabilities increases.

**Cumulative Investment in Global Data Centres to Hit $1.6 Trillion by 2030**

Global investment in data centre infrastructure is projected to reach an impressive $1.6 trillion by 2030, according to research from Omdia. This significant financial commitment reflects a transformative shift in the data centre landscape, particularly as major technology firms are expected to allocate over $600 billion towards artificial intelligence (AI) capital expenditures in the year 2026 alone.

The findings from Omdia indicate that the AI Factory market has surpassed a pivotal threshold, evolving into an industrialised model characterised by substantial capital demands, geopolitical considerations, and intricate engineering challenges. Defined by Omdia, the AI Factory is a specialised facility designed to produce intelligence, with tokens serving as the primary output unit.

Data centres are undergoing a fundamental shift, transitioning from mere business support hubs to becoming sophisticated digital manufacturing centres that generate high-value intelligence. This evolution is marked by a new four-layer architecture that encompasses physical and energy infrastructure, network fabrics and hardware, virtualisation orchestration, and a Model as a Service ecosystem.

The current market is segmented into four distinct solution paradigms: public cloud hyperscalers, compute-native specialists, private foundation providers, and regional infrastructure operators. A recent survey involving over 200 businesses highlighted several critical challenges facing the industry, including lengthy time-to-market, digital sovereignty, talent shortages, and systemic engineering complexity.

As the industry moves away from the practice of compute hoarding, businesses are addressing the so-called "Zombie GPU effect," where costly processors remain idle during input and output wait times. In response, evaluation benchmarks are being redefined to emphasise Time-to-First-Token and vector retrieval speed. Recent studies have documented a twelvefold improvement in indexing speed and a reduction in compute costs by as much as 75%.

Major hyperscalers are navigating the balance between agility and sovereignty by offering fully integrated physical units, alongside options for hardware and software decoupling. The power density of racks has seen a significant increase, rising from between 10 and 15 kW in 2024 to projections of up to 250 kW by June 2026, as workloads transition from initial proof-of-concept stages to full production-grade deployments.

Companies such as Nebius and Sensetime are adapting their business models, moving from basic hardware leasing to a Model as a Service framework. Sensetime, in particular, is implementing a comprehensive strategy that integrates infrastructure, software, and energy management to enhance control over computing resources.

Value creation is increasingly being driven by vertical integrators and domain operators through long-term data governance and the integration of legacy systems. Inspur Cloud is actively pursuing a strategy that combines heavy-asset infrastructure with specialised industrial operations to expedite the journey towards full AI industrialisation.

Emerging regulatory frameworks, such as the EU AI Act, are compelling organisations to maintain sensitive information within physically isolated facilities. This regulatory shift has elevated the status of regional operators like G42, transforming them from traditional infrastructure landlords into key physical gatekeepers of national data.

Raymond Zhan, Senior Principal Analyst for Cloud and AI at Omdia, noted, “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.” He further emphasised that for enterprise clients, the landscape of AI factory providers is not a uniform solution; choices must be tailored to the specific business scale and the balance between steady-state and innovative workloads.

Looking ahead, Omdia anticipates that the years 2026 and 2027 will be critical for the expansion of data centre facilities, with regional and industrial operations poised to emerge as the most reliable growth sectors in the coming five years. As the demand for data processing and AI capabilities continues to rise, the investment landscape for data centres is set to evolve significantly, reshaping the future of technology infrastructure globally.

Source: Cyprus Mail
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