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Flexential's 2025 State of AI Infrastructure Report

In its recently published report, Flexential, a prominent player in secure data center solutions, has highlighted a significant shift in organizational planning towards AI infrastructure requirements. With the increasing demands of artificial intelligence applications, businesses are beginning to look years ahead, completely redefining traditional IT forecasting methodologies.

The 2025 State of AI Infrastructure Report reveals compelling statistics: a remarkable 79% of enterprises are already planning their data center capacities more than a year in advance. Among these organizations, 62% are taking a proactive approach, strategizing for one to three years into the future, while 17% are setting their sights even further, planning three to five years ahead. This extended time frame is necessary due to the substantial investments and long procurement cycles that AI workloads necessitate.

Ryan Mallory, President and COO of Flexential, shared insight into the pressing situation, stating, "Vacancy rates are tightening, and lead times are extending as AI requirements grow. What used to be a two-year runway is now the minimum planning horizon to stay competitive. Providers and enterprises must act early and be flexible because waiting for certainty will cost time, capital, and opportunities. Once capacity is unavailable, there are no quick fixes."

This trend underscores the intensifying pressures that IT leaders face, especially in an increasingly competitive and constrained market. A staggering 94% of surveyed IT professionals expressed confidence in their planning processes. However, this confidence might be overestimated. Among the 16% of respondents who reported plans that look less than a year into the future, a striking 70% claim to be well-prepared for their infrastructure needs. This discrepancy suggests varying levels of readiness within different organizations.

Furthermore, as the evolution of AI technology ramps up, numerous challenges remain. Issues like bandwidth shortages and excessive latency have affected many organizations; 59% of survey respondents reported bandwidth shortages last year, while 53% faced excessive latency in their operations. This reveals that successful AI implementation is as much dependent on network capabilities as it is on raw computing capacity.

Adding another layer of complexity, workforce limitations continue to hinder AI progress. Only 5% of respondents reported encountering no skills or staffing gaps related to AI in the past year. Notably, 61% identified gaps in managing specialized computing infrastructure, followed closely by 53% facing issues in data science or engineering and 47% in advanced networking technologies. Compounding these shortages are broader hiring challenges, with over half of the respondents citing insufficient upskilling or training programs as primary obstacles for developing their AI workforce.

Interestingly, despite the evident staffing problems, only 10% of participants identified a lack of skilled personnel as the main barrier to their AI expansion efforts, indicating a prioritization of infrastructure challenges over workforce issues. This insight reflects a strategic focus on the immediate operational necessities of businesses as they navigate the AI landscape.

The report further clarifies how organizations are adapting to the changing environments. For instance, 68% of respondents still prioritize public clouds as the primary storage location for AI training data, while 54% rely on colocation services to enhance their performance needs. On-premise storage plays a marginal role, with only 20% of organizations utilizing local facilities for AI training data, and merely 36% planning to use these environments for training workloads.

Adoption rates for GPU-as-a-service are on the rise, with 40% of workplaces engaging external vendors for these services, up from 34% last year. Meanwhile, public cloud deployments saw an increase, rising from 30% to 34% across surveyed organizations.

Moreover, it has become ubiquitous across businesses that some form of AI training is being offered, with the formats varying from embedded tools (63%) to in-house programs (62%) and external certifications (59%).

Mallory emphasizes the importance of foresight in infrastructure planning, stating, "The question isn't just whether a provider has the infrastructure you need today, but whether it's building the systems and energy solutions to meet the AI workloads you'll want tomorrow. Bringing new capacity online takes years, not months, and that timeline has real consequences. The most successful companies recognize that planning is a competitive advantage."

Flexential has identified high growth and potential in several regions, including Atlanta, Dallas, and Denver, and continues to invest in these areas to meet the surging demands of AI.

To delve deeper into the insights shared in the 2025 State of AI Infrastructure Report and to navigate the complexities of AI infrastructure planning, organizations can explore various resources provided by Flexential, including workshops and webinars designed to help businesses achieve their ambitious plans for AI.