Generative AI (GenAI) is adding new challenges to enterprise multi-cloud strategies. Companies have spent years working on how to manage data across different clouds. But with GenAI, these strategies must go beyond just data storage. The real issue is making sure the data is in the right place for AI to access. This often means moving data between clouds, which can be both expensive and time-consuming.
Kyndryl’s Global Cloud Leader, Nicolas Sekkaki, notes that data must be accessible to the AI, no matter where it’s stored. If the AI runs in one cloud and the data is in another, costs can increase quickly. Roy Chua, founder of AvidThink, adds that most companies have only solved their data storage issues. Now, they must focus on data movement, which will become a big concern for CIOs.
Regulations and compliance also complicate things. Enterprises face new layers of complexity when dealing with sensitive data across multiple platforms. Gartner’s Sid Nag pointed out that hyperscalers like Google, AWS, and Microsoft are working on solutions. However, many enterprises still face issues due to cloud silos, where data is locked into one provider, limiting its usefulness for AI.
A study by Deloitte shows that up to 35% of a company’s cloud costs can come from data transfer. This shows how important it is to solve these data mobility issues. FORGE’s services help companies optimize cloud environments and reduce these costs. They offer lifecycle management, forensic analysis, and vendor selection to streamline multi-cloud strategies.
FORGE is well-positioned to help companies manage the complexities of GenAI and multi-cloud environments. By ensuring smooth data flows and optimizing vendor contracts, FORGE helps companies reduce costs and increase efficiency. Their experience helps enterprises make the most of GenAI without being held back by data and cloud challenges.
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