Only 38% of companies say they are ready for AI storage

The majority of IT leaders expect a significant increase in storage volumes due to AI, but only 38% of organizations claim to be ready. Sustainability imperatives are even hindering infrastructure expansion projects. Seagate promotes "sustainable scalability" based on data lifecycle management to bridge the gap.

Sustainability and Capacity: Slowed Projects and a Persistent Gap

77% of organizations surveyed have delayed or modified their AI infrastructure expansion for sustainability or energy reasons, and 36% have made major revisions to their plans. For 52% of respondents, the major environmental concern is the energy consumption of AI, while 51% mention carbon emissions and energy usage. According to 97% of those surveyed, increasing the longevity of infrastructure contributes to sustainability, and 94% expect their storage operations to become more sustainable over the next five years. Although 38% of organizations have already begun working on their preparedness, the majority remain far from a fully prepared state.

AI Returns but Fragile Storage: Priority Shifts to Data Centers

The companies surveyed are seeing benefits from AI: 86% report moderate or significant returns, and one-third mention significant and measurable returns. At the same time, 98% of respondents believe that AI makes storage a strategic element of infrastructure. This awareness is reflected in investment choices: just over 76% place data centers among their top three priorities, and one in five makes it their top priority. The debate around data centers is intensifying, with opposition emerging in several regions. Despite these developments, the report's data highlight a gap between AI adoption and storage and data management capacity, as challenges related to access, retention, and governance multiply.

Insufficient Preparedness and Expected Peaks in Storage Volumes

62% of organizations do not consider themselves ready to face the increasing storage needs related to AI, and less than 40% believe their infrastructure is suited for this expansion. Nevertheless, 99% of IT leaders anticipate a rise in storage needs over the next three years, with 32% expecting an increase of more than 50% in demand due to AI. The main obstacles to AI deployment are data quality and preparedness (53%), followed by storage infrastructure (43%), computing availability (27%), and energy constraints (24%). This hierarchy comes after a period where the focus was primarily on computing power.

Seagate Proposes Managing AI Storage Through Data Lifecycle

Seagate emphasizes the concept of "sustainable scalability," defined as the ability to increase AI power and business value while improving infrastructure efficiency. According to the company, the growing control exerted by decision-makers, regulators, and the public over AI infrastructure growth makes this approach essential for the long-term viability of an AI-driven economy. Seagate predicts that the next phase of AI will generate more data but believes that success will depend on the ability to keep data available and ready for use while effectively managing infrastructure constraints. To bridge the preparedness gap, Seagate recommends a strategy centered on the complete data lifecycle: identifying the data to be created, the speed of access needed based on workflows, the duration of their value, and the operational measures that will guide their growth. These choices are presented as the foundation for sustainable scalability and value for AI.

Scope and Method: 2,712 Decision-Makers in Seven Countries

The publication of Seagate's "2026 Data Infrastructure Readiness Report" dates back to September 14. This document is based on a study conducted by Recon Analytics among 2,712 technology leaders from companies located in the United States, China, India, the United Kingdom, Germany, France, and Japan, between May and June 2026. The analysis focused on the level of organizations' preparedness for AI, their investments in infrastructure, storage structure, facility efficiency, sustainability, and long-term planning.