Forrester’s research underscores the numerous financial and strategic benefits of migrating to Azure for be AI-ready. Decrease prices, elevated innovation, higher useful resource allocation, and improved scalability make migration to Azure a transparent alternative for organizations trying to thrive within the AI-driven future.
Because the digital panorama quickly evolves, AI stands on the forefront, driving vital innovation throughout industries. Nonetheless, to totally harness the facility of AI, companies should be AI-ready; this implies having outlined use-cases for his or her AI apps, being outfitted with modernized databases that seamlessly combine with AI fashions, and most significantly, having the fitting infrastructure in place to energy and understand their AI ambitions. After we speak to our prospects, many have expressed that conventional on-premises methods typically fall brief in offering the mandatory scalability, stability, and adaptability required for contemporary AI purposes.
A latest Forrester research1, commissioned by Microsoft, surveyed over 300 IT leaders and interviewed representatives from organizations globally to study their expertise migrating to Azure and if that enhanced their AI impression. The outcomes confirmed that migrating from on-premises infrastructure to Azure can assist AI-readiness in organizations, with decrease prices to face up and devour AI companies plus improved flexibility and talent to innovate with AI. Right here’s what you must know earlier than you begin leveraging AI within the cloud.
Challenges confronted by prospects with on-premises infrastructure
Many organizations who tried to implement AI on-premises encountered vital challenges with their present infrastructure. The highest challenges with on-premises infrastructure cited have been:
- Ageing and expensive infrastructure: Sustaining or changing getting older on-premises methods is each costly and complicated, diverting assets from strategic initiatives.
- Infrastructure instability: Unreliable infrastructure impacts enterprise operations and profitability, creating an pressing want for a extra secure answer.
- Lack of scalability: Conventional methods typically lack the scalability required for AI and machine studying (ML) workloads, necessitating substantial investments for rare peak capability wants.
- Excessive capital prices: The substantial upfront prices of on-premises infrastructure restrict flexibility and is usually a barrier to adopting new applied sciences.
Forrester’s research highlights that migrating to Azure successfully addresses these points, enabling organizations to give attention to innovation and enterprise development somewhat than infrastructure upkeep.
Key Advantages
- Improved AI-readiness: When requested whether or not being on Azure helped with AI-readiness, 75% of survey respondents with Azure infrastructure reported that migrating to the cloud was important or considerably lowered boundaries to AI and ML adoption. Interviewees famous that the AI companies are available in Azure, and colocation of information and infrastructure that’s billed solely on consumption helps groups check and deploy quicker with much less upfront prices. This was summarized properly by an interviewee who was the pinnacle of cloud and DevOps for a banking firm:
We didn’t need to go and construct an AI functionality. It’s up there, and most of our knowledge is within the cloud as properly. And from a hardware-specific standpoint, we don’t need to go procure particular {hardware} to run AI fashions. Azure gives that {hardware} at the moment.”
—Head of cloud and DevOps for international banking firm
- Price Effectivity: Migrating to Azure considerably reduces the preliminary prices of deploying AI and the price to keep up AI, in comparison with on-premises infrastructure. The research estimates that organizations expertise monetary advantages of USD $500 thousand plus over three years and 15% decrease prices to keep up AI/ML in Azure in comparison with on-premises infrastructure.
- Flexibility and scalability to construct and preserve AI: As talked about above, lack of scalability was a typical problem for survey respondents with on-premises infrastructure as properly. Respondents with on-premises infrastructure cited lack of scalability with present methods as a problem when deploying AI and ML at 1.5 instances the speed of these with Azure cloud infrastructure.
- Interviewees shared that migrating to Azure gave them quick access to new AI companies and the scalability they wanted to check and construct them out with out worrying about infrastructure. 90% of survey respondents with Azure cloud infrastructure agreed or strongly agreed they’ve the pliability to construct new AI and ML purposes. That is in comparison with 43% of respondents with on-premises infrastructure. A CTO for a healthcare group mentioned:
After migrating to Azure all of the infrastructure issues have disappeared, and that’s usually been the issue while you’re new applied sciences traditionally.”
—CTO for a healthcare group
They defined that now, “The scalability [of Azure] is unsurpassed, so it provides to that scale and reactiveness we will present to the group.” Additionally they mentioned: “After we have been operating on-prem, AI was not as simply accessible as it’s from a cloud perspective. It’s much more obtainable, accessible, and straightforward to start out consuming as properly. It allowed the enterprise to start out pondering exterior of the field as a result of the capabilities have been there.”
- Holistic organizational enchancment: Past the price and efficiency advantages, the research discovered that migration to Azure accelerated innovation with AI by having an impression on the folks in any respect ranges of a corporation:
- Bottoms-up: skilling and reinvestment in staff. Forrester has discovered that investing in staff to construct understanding, expertise, and ethics is important to efficiently utilizing AI. Each interviewees and survey respondents expressed problem discovering expert assets to assist AI and ML initiatives at their organizations.
- Migrating to the cloud freed up assets and altered the varieties of work wanted, permitting organizations to upskill staff and reinvest assets in new initiatives like AI. A VP of AI for a monetary companies group shared: “As we now have gone alongside this journey, we now have not lowered the variety of engineers as we now have gotten extra environment friendly, however we’re doing extra. You possibly can say we’ve invested in AI, however every part we now have invested—my whole group—none of those folks have been new additions. These are folks we may redeploy as a result of we’re doing every part else extra effectively.”
- Prime-down: created a bigger tradition of innovation at organizations. As new applied sciences—like AI—disrupt whole industries, firms have to excel in any respect ranges of innovation to succeed, together with embracing platforms and ecosystems that assist drive innovation. For interviewees, migrating to the cloud meant that new assets and capabilities have been available, making it simpler for organizations to reap the benefits of new applied sciences and alternatives with lowered danger.
- Survey knowledge signifies that 77% of respondents with Azure cloud infrastructure discover it simpler to innovate with AI and ML, in comparison with solely 34% of these with on-premises infrastructure. An government head of cloud and DevOps for a banking group mentioned: “Migrating to Azure modifications the mindset from a corporation perspective with regards to innovation, as a result of companies are simply obtainable within the cloud. You don’t need to exit to the market and search for them. Should you have a look at AI, initially solely our knowledge house labored on it, whereas at the moment, it’s getting used throughout the group as a result of we have been already within the cloud and it’s available.”
Study extra about migrating to Azure for AI-readiness
Forrester’s research underscores the numerous financial and strategic benefits of migrating to Azure for be AI-ready. Decrease prices, elevated innovation, higher useful resource allocation, and improved scalability make migration to Azure a transparent alternative for organizations trying to thrive within the AI-driven future.
Able to get began together with your migration journey? Listed here are some assets to be taught extra:
- Learn the full Forrester TEI research on migration to Azure for AI-readiness.
- The options that may assist your group’s migration and modernization objectives.
- Our hero choices that present funding, distinctive gives, knowledgeable assist, and greatest practices for all use-cases, from migration to innovation with AI.
- Study extra in our e-book and video on find out how to migrate to innovate.
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