LAYING THE GROUNDWORK FOR A ROBUST DATA STORAGE FOUNDATION IN THE AI ERA

Alex McMullan, CTO International at Pure Storage elaborates on the key factors that enterprises need to consider in order to transform their data environments to better meet the demands of AI.

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AI, and particularly Gen AI, may have been at the forefront of global attention these past few years, but we're starting to hear growing concerns about an impending AI reckoning as many enterprises aren't seeing the ROI from their AI investments. Gartner calls this the trough of disillusionment and a normal phase that all technologies go through. For now, market observers still think AI spending will continue to grow. According to IDC, the top 1,000 companies in Asia will allocate more than half of their IT spending to AI initiatives by 2025.

But if AI is going to pull through this trough of disillusionment, there is one critical area that needs to be addressed and that is the underlying IT infrastructure, including data storage. Pure Storage’ recent Innovation Race study found that 80% of global CIOs and decision makers feel that their companies need to enhance existing infrastructure to effectively support the increasing demands of AI deployments.

Enterprises of all sizes are increasingly recognising the limitations of their existing storage architectures. Many are locked into legacy systems that lack the performance and reliability to support AI workloads. So, how can enterprises transform their data environments to better meet the demands of AI?

Understanding Al data storage challenges