April 22, 2024
Managing costs to realize the potential of cloud and generative AI

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This is an Insight article presented by Microsoft.


The great cloud migration of recent years isn’t over yet — plenty of organizations are still busy leveling up. But today the drive towards cloud adoption is more and more propelled by the desire to leverage the potential of AI — especially generative AI, says Tony Korolis, senior product marketing manager (Azure) at Microsoft, and the team has watched the shift happen in real time. His team manages two Azure offerings: Azure Migrate and Modernize & Azure Innovate which help customers accelerate their cloud aspirations.

“Customers have been asking not only for help in migrating their existing setup, but using the cloud to start taking advantage of AI, to build innovative new products and services,” says Korolis. He adds, “In the next year the number of AI-focused customers may overtake the number of migrating customers coming through our Azure offerings.”

It’s not just the need to jump onto this movement in our industry, Korolis adds. It’s seeing early adopters succeed in bringing to real life AI use cases that had previously just been conceptual, and seeing how they impact day-to-day business and the bottom line. Plus, cloud democratizes access to the kind of scalable, cost-effective computing power that AI demands, letting companies of any size seize that advantage.

But many companies are finding that it takes some discipline as an organization to fully realize the promise of cloud. “Many organizations launch cloud strategies simply assuming cost savings are automatically going to happen,” Korolis says. “But the cloud has more than just hard dollar costs, and it takes effort and governance to realize a return on your investment.”

The true cost of cloud computing and AI

Some of the costs involved with cloud computing are obvious — the initial investment in technology, and professional services to implement a solution. There are also the consumption costs which should be managed and governed centrally. If some applications are staying on-premises, organizations should account for managing both. And then there’s the expense and time it requires to train, reskill or upskill anyone involved in a cloud strategy and implementation.

“Training staff not only takes time, but it also takes those administrators and developers away from their regular responsibilities” Korolis says. “It takes time to develop training plans, and it takes time to study for certifications as well, no matter what solution you’re deploying.”

Part of the challenge comes from the need to find talent with a background in AI, he adds. This skill gap is an industry-wide challenge — and it will require not just upskilling and reskilling, but a whole new cohort of job applicants to really fill the needs. That said, platform and technology certifications that test applicants on objective criteria are proving to be useful, Korolis says.

For instance, there are certifications like Azure AI engineer, among others. These certifications can often give engineers a head start on studying for other certifications, since some of the same foundational principles apply to other cloud workloads.

Optimizing costs while encouraging growth

Organizations that are eager to throw themselves into the AI fray are often also balancing other initiatives, including cloud migration, Korolis says. And, he adds, to stay competitive and ensure progress, keep doing both.

“The most successful practice is to divide and conquer,” he explains. “Allocate some teams to keep migrating on-premises workloads, and at the same time carve off teams of innovators who are encouraged to experiment on new projects. That’s how you create more value, faster.”

“More value, faster” is a rallying cry for many companies, but he warns that it can also mean rushing past the essential groundwork and flinging yourself into an abyss of complications down the road.

“Customers need to spend more time in the planning phase. A lot of customers want to rush past that phase and get right to deployment, but honestly, those projects often go off the rails,” Korolis says. “Planning is essential. We find that the really successful customers might spend months in the planning phase getting the cloud strategy hammered out and getting everyone in the organization aligned before they even engage an implementation partner.”

The importance of planning is one of the reasons recent Azure offerings distinguish between the planning and deployment phases, he adds.

For instance, Azure Migrate and Modernize, which helps efficiently move existing workloads to Azure at scale, helps you discover and assess the on-premises environment before you deploy, and determine the best migration plan and Azure architecture upfront.

Azure Migrate and Modernize & Azure Innovate offer customer benefits like assessments, pilot/proof-of-concepts and deployment assistance from experts. Customers receive offers that can consist of expert guidance, partner funding, Azure credits, migration tooling and technical skilling. Customers are able to accelerate their projects with these offers since they’re based on proven approaches used by thousands of other customers.

“From our standpoint, the most crucial thing to look at is which providers give you end-to-end help to get you to their cloud,” Korolis says. “What we see is that different providers have varying amounts of investment in their customers, and Microsoft’s priority is helping customers succeed.”

Learn here how Microsoft Azure is helping organizations of all sizes seize the full potential of cloud and AI-led transformation with Azure Migrate and Modernize & Azure Innovate.


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