While AI is top of mind in the public consciousness, the cloud is entering a new phase in its maturation. Organizations have started reassessing what’s in the cloud, what isn’t, and why. Is it providing enough value to the business to justify the investment?
It’s hard to look back on the last decade-plus of cloud implementation without realizing that, for many companies, the intent behind moving to the cloud has changed over time. This is an incredibly powerful technology that offers tremendous benefits in terms of agility, scalability, security, access to new markets, and more. But it isn’t necessarily a way to save money. Cost is becoming a secondary consideration, and one that should be looked at relative to cloud’s benefits – not relative to the cost of on-prem data centers.
Cloud optimization is one of the largest cost-saving opportunities in IT today, and with the true cost of cloud having caught a lot of enterprises by surprise, we’re moving quickly to aggressive FinOps adoption as organizations look to improve governance and visibility into their cloud spending.
We heard from some executives about incredibly optimized and well-run cloud deployments that have rocketed them to the head of the pack in terms of business value, and from others about how they’re looking to revisit their cloud usage and considering moving back to on-prem in some areas. Cloud optimization is one of the largest cost-saving opportunities in IT today, and with the true cost of cloud having caught a lot of enterprises by surprise, we’re moving quickly to aggressive FinOps adoption as organizations look to improve governance and visibility into their cloud spending.
In keeping with the theme of the session, there’s both an AI angle here and an early warning for AI adopters. Like cloud, AI can improve agility and efficiency – but also like cloud, the temptation to over-deploy looms large, while disentangling may be a challenge. And just as organizations are looking to cut down on their excessive cloud usage, using AI (which generally runs in the cloud and is compute-intensive) can drive costs up all over again.
Read more takeaways from Spark 2023:
Part 1: The Generative Generation
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