The Forrester study highlights the significant economic and strategic benefits of migrating to Azure to be AI-ready. Lower costs, greater innovation, better resource allocation, and improved scalability make migrating to Azure a clear choice for organizations looking to thrive in the 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, companies must be ready for it; This means having defined use cases for your AI applications, being equipped with modernized databases that integrate seamlessly with AI models, and most importantly, having the right infrastructure to drive and realize your AI ambitions. When we speak with our customers, many have expressed that traditional on-premises systems often fail to provide the scalability, stability, and flexibility necessary for modern AI applications.
TO recent Forrester study1commissioned by Microsoft, surveyed more than 300 IT leaders and interviewed representatives from organizations worldwide to learn about their experience migrating to Azure and whether that improved its impact on AI. The results showed that migrating on-premises infrastructure to Azure can support AI readiness in organizations, with lower costs to deploy and consume AI services, as well as greater flexibility and ability to innovate with AI. Here’s what you need to know before you start leveraging AI in the cloud.
Challenges customers face with on-premises infrastructure
Many organizations attempting to implement on-premise AI encountered significant challenges with their existing infrastructure. The main challenges cited with local infrastructure were:
- Old and expensive infrastructure: Maintaining or replacing outdated on-premises systems is costly and complex, diverting resources from strategic initiatives.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 needed for AI and machine learning (ML) workloads, requiring substantial investments for infrequent peak capacity needs.
- High capital costs: The substantial upfront costs of local infrastructure limit flexibility and can be a barrier to the adoption of new technologies.
The Forrester study highlights that migration to Azure effectively addresses these issues, allowing organizations to focus on innovation and business growth rather than infrastructure maintenance.
Key benefits
- Enhanced AI Preparedness: When asked if being on Azure helped with AI readiness, 75% of respondents with Azure infrastructure reported that migrating to the cloud was essential or significantly reduced barriers to AI and machine learning adoption . Interviewees noted that AI services are available in Azure, and collocation of data and infrastructure that is billed only on a consumption basis helps teams test and deploy faster with fewer upfront costs. This was summed up well by an interviewee who was head of cloud and DevOps at a banking company:
We didn’t have to build an AI capability. It’s up there and most of our data is also in the cloud. And from a hardware-specific standpoint, we don’t have to purchase special hardware to run AI models. Azure provides that hardware today.”
—Head of Cloud and DevOps for a global banking company
- Profitability: Migrating to Azure significantly reduces the initial costs of AI deployment and the cost of maintaining AI, compared to on-premises infrastructure. The study estimates that organizations experience financial benefits of US$500K over three years and 15% lower costs for maintaining AI/ML on Azure compared to on-premises infrastructure.
- Flexibility and scalability to build and maintain AI: As mentioned above, lack of scalability was also a common challenge for 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 1.5 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 develop them without worrying about infrastructure. 90% of respondents with Azure cloud infrastructure agreed or strongly agreed that they have the flexibility to create new AI and ML applications. This compares to 43% of respondents with local infrastructure. A CTO of a healthcare organization said:
After migrating to Azure, all the infrastructure issues went away, and that’s generally been the problem when looking at new technologies historically.”
—CTO for a healthcare organization
They explained that now “the scalability (of Azure) is unsurpassed, so it adds to that scale and reactivity that we can provide to the organization.” They also said: “When we were running on-premise, AI was not as easily accessible as it is from a cloud perspective. It is also much more available, accessible and easy to start consuming. “It allowed the company to start thinking outside the box because the capabilities were there.”
- Comprehensive organizational improvement: Beyond the cost and performance benefits, the study found that moving to Azure accelerated innovation with AI by impacting people at all levels of an organization:
- From the bottom up: training and reinvesting in employees. Forrester has found that investing in employees to develop understanding, skills, and ethics is critical to using AI successfully. Both interviewees and respondents expressed difficulties finding trained resources to support AI and ML initiatives in their organizations.
- Migrating to the cloud freed up resources and changed the types of work needed, allowing organizations to upskill employees and reinvest resources in new initiatives like AI. A VP of AI at a financial services organization shared, “As we continue on this journey, we haven’t reduced the number of engineers because we’ve become more efficient, but we are doing more. You could say we’ve invested in AI, but in everything we’ve invested in (my entire team), none of these people were new additions. “These are people we could reassign because we are doing everything else more efficiently.”
- Top down: created a broader culture of innovation in organizations. As new technologies, like AI, disrupt entire industries, companies need to excel at all levels of innovation to succeed, including adopting platforms and ecosystems that help drive innovation. For interviewees, migrating to the cloud meant that new resources and capabilities were available, making it easier for organizations 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 ML.compared to only 34% of those with local infrastructure. An executive director of cloud and DevOps at a banking organization said, “Migration to Azure changes the mindset from the organization’s perspective when it comes to innovation, because services are easily available in the cloud. You don’t have to go to the market to look for them. “If you look at AI, originally only our data space ran on it, whereas today it is used across the entire organization because we were already in the cloud and it is available.”
Learn more about migrating to Azure to be AI ready
The Forrester study highlights the significant economic and strategic benefits of migrating to Azure to be AI-ready. Lower costs, greater innovation, better resource allocation, and improved scalability make migrating to Azure a clear choice for organizations looking to thrive in the AI-driven future.
Ready to start your immigration journey? Here are some resources to learn more:
- Read the Complete Forrester TEI Study about migrating to Azure to be AI ready.
- He solutions that can support your organization’s migration and modernization goals.
- Our hero offerings providing financing, unique offerings, expert support and best practices for all use cases, from migration to AI innovation.
- Learn more in our eBook and video on how to migrate to innovate.
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