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DRIVERS OF CHANGE : MEETING THE ENERGY AND DATA CHALLENGES OF AI ADOPTION
The age of artificial intelligence ( AI ) has sparked growing excitement across industries with new tools like ChatGPT promising a competitive edge . However , as organizations feel the push to integrate AI into their operations , their supporting infrastructure may not set them up for success .
Most organizations lack the necessary infrastructure to handle the high-performance data demands and energy requirements essential for maximizing AI ’ s benefits . In fact , legacy systems often cannot support the massive AI data pipelines required to get the most from machine learning models . And while AI brings immense promise , its impact on energy requirements can be surprising .
Research Findings
The challenge for IT leaders is not just about creating a durable AI architecture ; it ’ s also about embracing AI in a way that aligns with their priority ESG objectives . To help pinpoint the hurdles of AI adoption in parallel to organizational sustainability goals , Pure Storage has partnered with Wakefield Research to survey more than 500 IT buyers at companies of 500 employees or more in four major global markets ( US , UK , France , Germany ).
The survey found that for 88 % of those who have adopted AI , the need for computing power has surged dramatically . p
These hidden costs of AI pose a challenge to the successful implementation of critical corporate initiatives , including those aimed at achieving environmental goals . As AI continues to accelerate in adoption , IT teams require a meaningful data strategy to ensure they can efficiently and effectively operationalize AI through the right infrastructure .
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