Forrester’s study highlights the significant economic and strategic benefits of migrating to Azure as it is AI-ready. Lower costs, higher innovation, better resource allocation and improved scalability make migrating to Azure the 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 harness the power of AI, businesses must be AI-ready; that means having defined use cases for their AI applications, being equipped with modernized databases that seamlessly integrate with AI models, and most importantly, having the right infrastructure to drive and realize their AI ambitions. When we talk to our customers, many have expressed that traditional on-premise systems often fall short in providing the necessary scalability, stability and flexibility required for modern AI applications.
A recent Forrester study1, commissioned by Microsoft, surveyed more than 300 IT executives and asked representatives of organizations around the world to learn about their experiences migrating to Azure and whether it has increased their impact on AI. The results showed that migration from on-premises infrastructure to Azure can support AI readiness in organizations with lower costs to build and use AI services, plus improved flexibility and ability to innovate with AI. Here’s what you should know before you start using AI in the cloud.
Challenges faced by customers with on-premises infrastructure
Many organizations attempting to implement AI on-premise have encountered significant challenges with their existing infrastructure. The main challenges cited with local infrastructure were:
- Aging and costly infrastructure: Maintaining or replacing aging on-premise systems is costly and complex and diverts resources from strategic initiatives.
- Infrastructure instability: Unreliable infrastructure affects business operations and profitability, creating an urgent need for a more stable solution.
- Lack of scalability: Traditional systems often lack the scalability needed for AI and machine learning (ML), requiring significant investment for occasional peak capacity needs.
- High capital costs: Significant initial costs for local infrastructure limit flexibility and can be a barrier to adoption of new technologies.
A Forrester study highlights that migrating to Azure effectively addresses these issues, allowing organizations to focus on innovation and business growth rather than infrastructure maintenance.
Key benefits
- Improved AI readiness: When asked if using Azure helped with AI readiness, 75% of survey respondents with Azure infrastructure said cloud migration was essential or significantly reduced barriers to AI and ML adoption. Respondents noted that AI services are readily available in Azure, and colocation of data and infrastructure that is billed only on a consumption basis helps teams test and deploy faster with lower upfront costs. One interviewee who was the head of cloud and DevOps for a banking company summed it up well:
We didn’t have to go and build an AI capability. It’s up there and most of our data is in the cloud as well. And in terms of hardware specific to running AI models, we don’t need to procure special hardware. Azure provides that hardware today.”
— Head of Cloud and DevOps for a global banking company
- Cost effectiveness: Migrating to Azure significantly reduces initial AI deployment costs and AI maintenance costs compared to on-premises infrastructure. The study estimates that organizations will see $500K more in financial benefits over three years and 15% lower AI/ML maintenance costs in Azure compared to on-premises infrastructure.
- Flexibility and scalability to build and maintain AI: As noted above, lack of scalability was a common challenge for survey respondents with on-premises infrastructure as well. Respondents with on-premises infrastructure cited a lack of scalability with existing systems as a problem when deploying AI and ML 1.5 times faster than those with Azure cloud infrastructure.
- Interviewees shared that migrating to Azure gave them easy access to new AI services and the scalability they needed to test and build them without worrying about infrastructure. 90% of survey respondents agreed or strongly agreed with Azure cloud infrastructure that they have the flexibility to build new AI and ML applications. This compares to 43% of respondents with on-premise infrastructure. The healthcare organization’s CTO said:
After migrating to Azure, all the infrastructure issues disappeared, and that’s generally been a problem when you look at new technologies historically.”
—CTO for a healthcare organization
They explained that now, “(Azura’s) scalability is second to none, so it adds to the scale and responsiveness we can provide to the organization.” They also said, “When we were running on-prem, AI wasn’t as readily available as it is from a cloud perspective. It is much more affordable, accessible and easy to start consuming. It allowed the company to start thinking outside the box because the capabilities were there.”
- Holistic organizational improvement: In addition to cost and performance benefits, the study found that migrating to Azure accelerated AI innovation by impacting people at all levels of the organization:
- Bottom up: qualification and reinvestment in employees. Forrester has found that investing in employees to build understanding, skills and ethics is critical to the successful use of AI. Both interviewees and survey respondents expressed difficulty in finding qualified resources to support AI and ML initiatives in their organizations.
- The migration to the cloud has freed up resources and changed the types of work needed, allowing organizations to upskill employees and reinvest resources into new initiatives like AI. A vice president of AI for a financial services organization shared, “As we’ve gone down this path, we haven’t cut the number of engineers because we’ve been more efficient, but we’re doing more. You could say we’ve invested in AI, but everything we’ve invested—my whole team—none of these people have been new additions. They’re people we could relocate because we’re doing everything else more efficiently.”
- Top down: created a greater culture of innovation in organizations. As new technologies – such as AI – disrupt entire industries, companies must excel at all levels of innovation to succeed, including the platforms and ecosystems that help innovate. For respondents, migrating to the cloud meant that new resources and capabilities were readily available, making it easier for organizations to take advantage of new technologies and opportunities with reduced risk.
- Survey data shows that 77% of respondents with Azure cloud infrastructure find it easier to innovate with AI and ML.compared to only 34% of those with local infrastructure. The executive director of cloud and DevOps for a banking organization said: “Migrating to Azure is changing the way an organization thinks about innovation because services are readily available in the cloud. You don’t have to go to the market and look for them. If you look at AI, originally it was just our data space that worked on it, whereas today 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 as it is AI-ready. Lower costs, higher innovation, better resource allocation and improved scalability make migrating to Azure the 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.
- Solutions that can support your organization’s migration and modernization goals.
- Our core offerings that provide funding, unique offerings, expert support and best practices for all use cases, from migration to AI innovation.
- Learn more in our e-book and video on how to transition to innovation.
Reference
- Forrester Consulting The Total Economic Impact™ of Migrating to Microsoft Azure For AI-Readiness Commissioned by Microsoft, June 2024
