Investments in datacenter infrastructure are anticipated to surge, reaching $1.6 trillion by 2030, despite ongoing challenges such as supply chain disruptions increasing component costs. Omdia’s recent report highlights this growth trajectory, driven by continued investment in AI infrastructure despite some experts suggesting an impending market bubble.

Although AI adoption remains limited, expectations for increased user engagement and larger, more computationally intensive models suggest substantial potential growth. This expansion demands high-performance infrastructure that intensifies power consumption, thereby elevating the density and expenditure on AI hardware.

Omdia projects a 17% compound annual growth rate (CAGR) for datacenter capital expenditure, which poses questions about its sustainability. Bain & Company estimates that the industry would need to generate $2 trillion in yearly sales by 2030 to support such investments, raising concerns about the elusive returns for vendors and users alike.

Industry executives recently dismissed comparisons between AI and previous market bubbles, maintaining optimism about long-term growth prospects. Omdia’s analysis includes multiple scenarios that consider order pipelines and demand against constraints like Nvidia’s GPU backlog and stagnant datacenter construction.

In addition to AI-specific servers, a general refresh cycle for standard servers is also contributing to increased shipments, with major buyers deferring routine upgrades in favor of higher-capacity systems.

Pricing pressures due to supply constraints, particularly in memory components, may lead to higher server costs, potentially rising by 15%. Adjustments in datacenter engineering are anticipated to accommodate AI’s evolving infrastructure needs, calling for innovative approaches in hardware and energy management.

Datacenter professionals must remain vigilant and responsive to these shifts, maintaining openness to technological advancements to navigate this dynamic environment.