Forrester’s study highlights the significant economic and strategic benefits of migrating to Azure to prepare for AI. Reduced costs, increased innovation, better resource allocation, and improved scalability make migrating to Azure a clear choice for businesses looking to thrive in an AI-driven future.
As the digital landscape rapidly evolves, AI is at the forefront, driving significant innovation across industries. However, to fully harness the power of AI, businesses must be ready to use it. This means having defined use cases for their AI applications, being equipped with modernized databases that integrate seamlessly with AI models, and most importantly, having the right infrastructure in place to power and deliver on their AI ambitions. When we speak with our customers, many tell us that traditional on-premises systems often fail to provide the scalability, stability, and flexibility needed for modern AI applications.
A Recent Forrester study1commissioned by Microsoft, surveyed more than 300 IT managers and interviewed representatives from organizations around the world to learn about their experiences migrating to Azure and whether it improved their impact on AI. The results showed that migrating from on-premises infrastructure to Azure can drive AI readiness across organizations, with lower costs to set up and consume AI services, and improved flexibility and ability to innovate with AI. Here’s what you need to know before you start leveraging AI in the cloud.
Challenges faced by customers with on-premises infrastructure
Many organizations that have attempted to implement AI on-premises have encountered significant challenges with their existing infrastructure. The top challenges cited regarding on-premises infrastructure were:
- Aging and costly infrastructure: Maintaining or replacing aging on-premises systems is both costly and complex, diverting resources from strategic initiatives.
- Infrastructure instability: Unreliable infrastructure impacts business operations and profitability, creating an urgent need for a more stable solution.
- Lack of scalability: Traditional systems often lack the scalability required for AI and machine learning (ML) workloads, requiring substantial investments for infrequent peak capacity needs.
- High investment costs: The substantial upfront costs of on-premises infrastructure limit flexibility and can be a barrier to adopting new technologies.
Forrester’s study highlights that migrating to Azure effectively solves these issues, allowing organizations to focus on innovation and business growth rather than infrastructure maintenance.
Key Benefits
- Improving AI Readiness:When asked if being on Azure helps with AI readiness, 75% of respondents with Azure infrastructure said that moving to the cloud was essential or significantly reduced the barriers to AI and ML adoption. Respondents noted that AI services are readily available in Azure and that colocation of data and infrastructure billed only on a per-consumption basis helps teams test and deploy faster with lower upfront costs. This was summed up well by one respondent who was responsible for cloud and DevOps for a banking company:
“We didn’t need to build an AI capability. It’s up there, and most of our data is also in the cloud. And from a hardware standpoint, we don’t need to go out and get special hardware to run AI models. Azure provides that hardware today.”
— Cloud and DevOps Manager for a global banking company
- Cost efficiency:Migrating to Azure significantly reduces the upfront costs of deploying AI and the cost of maintaining AI, compared to on-premises infrastructure. The study estimates that companies see financial benefits of over $500,000 over three years and 15% lower AI/ML maintenance costs in Azure compared to on-premises infrastructure.
- Flexibility and scalability to create and maintain AI:As mentioned above, lack of scalability was also a common challenge for survey respondents with on-premises infrastructure. Respondents with on-premises infrastructure cited the lack of scalability of existing systems as a challenge when deploying AI and ML at a rate 1.5x higher than those with Azure cloud infrastructure.
- Respondents said migrating to Azure gave them easy access to new AI services and the scalability they needed to test and develop them without worrying about infrastructure. 90% of respondents with Azure cloud infrastructure agreed or strongly agreed that they have the flexibility to build new AI and ML applications. This compares to 43% of respondents with on-premises infrastructure. A CTO at a healthcare organization said:
After migrating to Azure, all the infrastructure issues are gone, and that’s usually the problem when you look at new technologies in the past.
—Technical Director of a healthcare organization
They explained that now, “the scalability (of Azure) is unmatched, which adds to that scalability and responsiveness that we can offer to the organization.” They also said, “When we were operating on-premises, AI was not as readily available as it is from a cloud perspective. It’s much more available, accessible, and easy to use as well. That allowed the business to start thinking outside the box because the capabilities were there.”
- Holistic organizational improvement: Beyond cost and performance benefits, the study found that migrating to Azure accelerates AI innovation by impacting people at every level of an organization:
- From the bottom up: training and reinvestment in employees. Forrester found that investing in employees to build understanding, skills, and ethics is critical to successfully using AI. Interviewees and survey respondents reported difficulty finding skilled resources to support AI and machine learning initiatives in their organizations.
- The migration to the cloud has freed up resources and changed the types of work needed, allowing organizations to upskill their employees and reinvest resources in new initiatives like AI. A VP of AI at a financial services organization said, “As we’ve gone through this journey, we haven’t reduced the number of engineers as we’ve gotten more efficient, but we’re doing more. You could say we’ve invested in AI, but all we invested in—my entire team—wasn’t new people. These were people we could redeploy because we’re doing everything else more efficiently.”
- From top to bottom: creating a greater culture of innovation within organizations. As new technologies like AI disrupt entire industries, businesses must excel at every level of innovation to succeed, including adopting platforms and ecosystems that foster innovation. For respondents, migrating to the cloud means new resources and capabilities are readily available, allowing businesses to take advantage of new technologies and opportunities with reduced risk.
- Survey data indicates that 77% of respondents with Azure cloud infrastructure find it easier to innovate with AI and MLcompared to only 34% of companies with on-premises infrastructure. An executive cloud and DevOps lead for a banking organization said, “Migrating to Azure changes the mindset of an organization when it comes to innovation because the services are readily available in the cloud. You don’t have to go to market to find them. If you look at AI, originally it was just our data space running on it, but now it’s used across the organization because we were already in the cloud and it’s readily available.”
Learn more about migrating to Azure for AI readiness
Forrester’s study highlights the significant economic and strategic benefits of migrating to Azure to prepare for AI. Reduced costs, increased innovation, better resource allocation, and improved scalability make migrating to Azure a clear choice for businesses looking to thrive in an AI-driven future.
Ready to get started on your migration journey? Here are some resources to learn more:
- Read it Forrester TEI Full Study on migrating to Azure for AI readiness.
- THE solutions which can support your organization’s migration and modernization goals.
- OUR Hero Offerings that provide funding, unique offerings, expert support and best practices for every use case, from migration to innovation with AI.
- Learn more in our e-book and video on how to migrate to innovate.
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