Forrester’s research highlights the significant economic and strategic benefits of migrating to Azure for AI readiness. Cost savings, increased innovation, better resource allocation, and improved scalability make migrating to Azure a clear choice for organizations 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 leverage the power of AI, enterprises need to be AI-ready. This means defining use cases for AI apps, having a modernized database that seamlessly integrates with AI models, and most importantly, building the right infrastructure to realize and deliver on their AI ambitions. When we talk to customers, many tell us that their existing on-premises systems often don’t provide the scalability, reliability, and flexibility that modern AI applications require.
Recent Forrester research1This Microsoft-commissioned study surveyed more than 300 IT leaders and interviewed representatives from organizations around the world to understand their experiences migrating to Azure and how it has improved their AI impact. The results show that migrating from on-premises infrastructure to Azure can help your organization become more AI-ready, reducing the cost of building and consuming AI services and increasing your 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 using on-premise infrastructure
Many organizations that have attempted to implement AI on-premises have faced significant challenges with their existing infrastructure. Some of the key challenges cited with on-premises infrastructure include:
- Aging and expensive infrastructure: Maintaining or replacing aging on-premise systems is costly and complex, and takes away resources from investing in strategic initiatives.
- Infrastructure instability: Unreliable infrastructure impacts business operations and profitability, creating an urgent need for more reliable solutions.
- Lack of scalability: Existing systems often lack the scalability needed for AI and machine learning (ML) workloads, requiring significant investments to accommodate even infrequent peak capacity demands.
- High cost of capital: The significant up-front costs of building on-premises infrastructure can limit flexibility and impede the adoption of new technologies.
Forrester’s research highlights that migrating to Azure effectively addresses these challenges, allowing organizations to focus on innovation and business growth rather than maintaining infrastructure.
Key Benefits
- Enhanced AI Readiness: When asked if being on Azure helped them prepare for AI, 75% of survey respondents with Azure infrastructure reported that migrating to the cloud was essential or significantly reduced the barriers to AI and ML adoption. Interviewees noted that AI services are readily available on Azure, and that co-location of data and infrastructure, billed only for what they consume, allows teams to test and deploy faster with less up-front cost. This was summed up well by an interviewee who was head of cloud and DevOps at a banking company.
We didn’t have to go build out our AI capabilities. It’s there, most of our data is in the cloud. And from a hardware-specific perspective, we don’t have to procure special hardware to run our AI models. Azure provides that hardware today.”
—Head of Cloud and DevOps at a global banking company
- Cost Effectiveness: Migrating to Azure significantly reduces the initial cost of deploying AI and the ongoing costs of maintaining AI compared to on-premises infrastructure. The study estimates that organizations will see financial benefits of more than $500,000 over three years and a 15% reduction in the cost of maintaining AI/ML on Azure compared to on-premises infrastructure.
- Flexibility and scalability to build and maintain AI: As noted above, lack of scalability was also a common challenge for survey respondents using on-premises infrastructure. Respondents using on-premises infrastructure cited lack of scalability of existing systems as a challenge when deploying AI and ML at 1.5x the rate of respondents using Azure cloud infrastructure.
- Interviewees said migrating to Azure gave them easy access to new AI services and the scalability they needed to test and deploy them without worrying about infrastructure. Ninety percent of survey 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 who use on-premises infrastructure. As one healthcare organization’s CTO put it:
After migrating to Azure, all of our infrastructure issues disappeared, which historically was a common problem when looking at new technologies.”
—CTO of a medical institution
They now explain, “The scalability of Azure is unmatched, which adds to the scale and responsiveness that we can provide to our organization.” They also say, “When we were running on-premises, AI was not readily accessible from a cloud perspective. It’s much more readily available, accessible, and easy to use. It’s allowed our business to think outside the box.”
- Overall organizational improvement: Beyond cost and performance benefits, the study found that migrating to Azure impacts people at all levels of an organization, accelerating innovation through AI.
- Top down: Upskilling and reinvesting in employees. Forrester found that investing in employees to build understanding, skills, and ethics is critical to successfully deploying AI. Both interviewees and survey respondents expressed difficulty finding skilled resources to support AI and ML initiatives in their organizations.
- Migrating to the cloud frees up resources and changes the types of work required, allowing organizations to upskill their workforce and reinvest resources in new initiatives like AI. “We’ve made more efficiencies without reducing the number of engineers as we’ve gone through this journey,” said a VP of AI at a financial services organization. “You can say we’ve invested in AI, but every single person we’ve invested in—every single person in the entire team—isn’t a new addition. They’re people we can redeploy because we’re doing everything else more efficiently.”
- Bottom-up: We’ve expanded the culture of innovation within our organization. As new technologies like AI disrupt entire industries, companies must excel at all levels of innovation to succeed, including embracing platforms and ecosystems that drive innovation. For interviewees, migrating to the cloud meant easier access to new resources and capabilities, making it easier for organizations to take advantage of new technologies and opportunities while reducing risk.
- According to survey data, 77% of respondents who use Azure cloud infrastructure believe it is easier to innovate with AI and ML.That compares with just 34% using on-premises infrastructure. A cloud and DevOps executive at a banking organization said, “Migrating to Azure changes the mindset from an organizational perspective when it comes to innovation, because services are readily available in the cloud. You don’t have to go out and find them. When you look at AI, it used to be something that was just a data space, but today it’s already in the cloud and readily available, so it’s being used across the organization.”
Learn more about how to migrate to Azure to prepare for AI.
Forrester’s research highlights the significant economic and strategic benefits of migrating to Azure for AI readiness. Cost savings, increased innovation, better resource allocation, and improved scalability make migrating to Azure a clear choice for organizations looking to thrive in an AI-driven future.
Are you ready to start your migration journey? Here are some resources to learn more:
- Read the full Forrester TEI study on migrating to Azure for AI readiness.
- A solution that can support your organization’s migration and modernization goals.
- Our exceptional offering provides funding, unique offerings, expert support, and best practices for every use case, from AI-powered migration to innovation.
- Learn more about how to migrate for innovation in our eBook and video.
References
- Forrester Consulting The Total Economic Impact™ Of Migrating to Microsoft Azure For AI-Readiness, Commissioned by Microsoft, June 2024
