With the cloud being the best delivery option for enterprises to reap the benefits of AI, companies need to re-architect their data and move applications into a centralized, secure place to enable AI to do its magic.

As enterprises across the globe seek to reap the benefits of artificial intelligence and generative AI, cloud computing is very often the best delivery option due to its services focus and massive scalability.

This means that enterprises need to re-architect their data and move applications into a centralized, secure place to enable AI to do its magic.

“You have to have a good data strategy to have an AI strategy,” said Erik Duffield, CEO of New York-based cloud solution provider Hakkoda. “AI has really put a time pressure and competitive pressure on customers to get their data house in order. Because the next big thing is coming, and it’s going to involve AI. And if they don’t leverage their data correctly—if they don’t have the speed and agility with their data—they won’t be in the front of taking advantage of what AI has to offer.”

Solution providers are helping customers achieve their AI goals by focusing on migrating customers’ data and workloads into cloud environments.

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Many large Hakkoda customers, particularly in the financial services and health-care industries, have shifted their on-premises IT environment to the cloud as part of their AI strategy.

“In order to enable and leverage the latest technology around AI, data really needs to be in the cloud. That gives you the scale and the price/performance of being in the cloud,” said Duffield. “We’re doing real production AI work that’s really fun and helping our customers achieve the true benefits of AI.”

Cloud Is Needed ‘For AI To Work’

Kevin Ichhpurani, Google Cloud’s global channel chief, said a typical customer is looking at around 80 use cases when it comes to AI. However, for these customers to achieve their desired outcomes with an AI solution, a common data framework is needed across all the different use cases.

“One of the biggest challenges customers have today with deploying new business models or use cases with GenAI is they have to get their data state in order,” said Ichhpurani, corporate vice president of global ecosystem and channels at Mountain View, Calif.-based Google Cloud. “They have to eliminate data silos. They have to deduplicate their data and label the data. So data re-architecture is a huge opportunity for cloud computing and partners.”

Ichhpurani said that “for AI to work” customers need to modernize their applications and move to the cloud where everything is centralized, secure, governed and easily available.

“Yes, GenAI is a massive opportunity for the channel, but it’s also going to make the adoption and the movement to the cloud accelerate,” he said.

Cloud Helps AI Proofs Of Concept Become Reality

Tyler Prince, global channel chief at Bozeman, Mont.-based Snowflake, echoed a similar strategy for his company’s AI future with channel partners.

After partners perform AI proofs of concept to customers showing how the technology can improve business objectives, customers immediately ask, “Am I ready to do that? How do I do that?” Prince said.

“The answer is, ‘Well, you need to have your data centralized and able to share in a very secure, compliant and governed way,’” Prince said. “GenAI is turning into an incredible opportunity for Snowflake and our partners to help companies that are asking insightful questions about, ‘How does GenAI transform my business?’ and then, ‘How do I do that?’ I see AI as basically a perfect use case for cloud.”

Ben Kessler, president of Chicago-based solution provider 66degrees, said many of his customers’ AI journeys involve migrating apps and data to a cloud platform.

“People need to have their data in the cloud so they can actually put the right analytics applications in the cloud,” Kessler said. “If you have your data in the cloud, the right workloads modernized, then you can deploy the GenAI application. We’re seeing tremendous demand from customers for us to build their AI and GenAI applications but also to modernize their data footprints in the cloud so they can take advantage of advanced analytics and advanced AI.”

Cloud Technology ‘Best Suited’ To Deliver GenAI

By 2027, research firm Gartner predicts more than 70 percent of enterprises will use industry cloud platforms to accelerate their business initiatives, including AI, up from less than 15 percent in 2023.

“Because of its scale and shared services model, cloud technology is best-suited for the delivery of GenAI-enabled applications at scale and the development of general-purpose foundation models,” said Sid Nag, vice president and analyst at Gartner.

Gartner also predicts that by 2026, over 80 percent of enterprises will have used GenAI APIs and models and/or deployed GenAI-enabled applications in production environments, up from less than 5 percent in early 2023.

Both of Gartner’s predictions around GenAI bode well for solution providers.

“The biggest secret is many, many clients don’t have their data modernized right now so they can’t take advantage of AI,” said 66degrees’ Kessler. “It’s critical right now to ensure your clients’ data is modernized. That’s what we’re doing right now and why we’re growing.”