As mainstream organizations continue to adopt AI technologies and applications, they increasingly understand the effects of these technologies on the underlying infrastructure.
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As mainstream organizations continue to adopt AI technologies and applications, they increasingly understand the effects of these technologies on the underlying infrastructure.
Research Report: The Critical Role of Storage in Building an Enterprise AI Infrastructure
As mainstream organizations continue to adopt AI technologies and applications, they increasingly understand the effects of these technologies on the underlying infrastructure. Though the immediate focus of many AI infrastructure projects is understandably on the compute layer, the data-intensive nature of AI also suggests that it will make a significant impact on the enterprise storage environment. However, with the AI space evolving at such breakneck pace, the precise nature and extent of these impacts has been unclear. IT leaders are faced with questions such as: Will AI workloads predominantly run on premises or in the public cloud? What type of data will these workloads primarily run on? What are the data- and storage-related challenges that will crop up across the various stages of the AI lifecycle? Who will best drive the storage decision-making for AI?
To gain further insight into these trends, we surveyed 350 IT professionals at organizations in North America (U.S. and Canada) involved with or responsible for purchase and deployment decisions for enterprise storage. The complete survey results presentation focuses on hybrid cloud deployment strategies, hybrid cloud investments, AI and hybrid cloud challenges, personnel and teams, the business and technology benefits of public cloud service providers, mainframe environments, and third-party service providers for cloud or hybrid cloud requirements.
Appendix
Further reading
Author
Simon Robinson,Principal Analyst, Cloud, IT Infrastructure, & Storage and Data Protection
Emily Marsh, Associate Research Director
