According to Forrester’s research, organizations that migrate to Azure can reap significant financial and strategic advantages in their pursuit of AI-readiness. By slashing costs, fostering groundbreaking innovation, optimizing resource utilization, and enhancing scalability, migrating to Azure provides a clear-cut pathway for businesses seeking to succeed in the AI-powered era.
As the digital landscape rapidly transforms, Artificial Intelligence (AI) assumes a pioneering role, propelling significant advancements across multiple sectors. To fully unlock the potential of AI, companies must be AI-ready; this requires defining clear use cases for AI applications, leveraging modernized databases that seamlessly integrate with AI models, and establishing a robust infrastructure to support and drive AI initiatives. As conversations with potential clients unfold, it becomes evident that traditional on-site applications often struggle to meet the demands of modern AI initiatives, lacking the necessary scalability, reliability, and flexibility.
A 1Commissioned by Microsoft, a global survey of over 300 IT leaders and in-depth interviews with select organization representatives were conducted to gauge the extent of their expertise in migrating to cloud-based infrastructure and how this expertise influenced their AI strategies. Migrating from on-premises infrastructure to Azure enables organisations to achieve AI-readiness by reducing the upfront costs of AI adoption, improving flexibility, and fostering innovation capabilities. Before you leverage AI in the cloud, there are a few key things to consider.
Prospects operating on-premises infrastructure often grapple with limitations stemming from outdated hardware and software.
Organizations attempting to deploy AI on-premises frequently encounter significant hurdles related to their existing infrastructure. The most significant hurdles associated with maintaining on-premises infrastructure were:
- Maintaining or transforming aging on-premises programs proves to be a costly and complex endeavor, thereby diverting valuable resources away from more strategic business objectives.
- Inadequate infrastructure poses significant risks to the operational efficiency and financial viability of enterprises, underscoring the urgent need for a more robust and reliable solution?
- Traditional programmes frequently struggle with the scalability demanded by AI and machine learning applications, prompting significant upfront investments to accommodate sporadic high-performance requirements.
- The high upfront costs associated with deploying on-premises infrastructure can act as a significant barrier to embracing innovative technologies.
According to Forrester’s research, successfully migrating to Azure enables organizations to focus on innovation and enterprise development rather than infrastructure maintenance by effectively addressing key pain points.
Key Advantages
- Seventy-five percent of surveyed organizations utilizing Azure infrastructure indicated that their migration to the cloud played a significant role in overcoming barriers to artificial intelligence (AI) and machine learning (ML) implementation, with many respondents citing that being on Azure helped significantly ease or remove obstacles to adopting AI and ML capabilities. Famous for their availability, AI providers in Azure offer a seamless coexistence of knowledge and infrastructure, allowing teams to swiftly check and deploy solutions with significantly reduced upfront costs, thanks to billing solely based on consumption. The essence of our cloud-DevOps strategy was succinctly distilled by our lead expert in the field.
No explanation was needed for us to develop an AI capability. Data is stored securely in the cloud, with a significant portion of our collective knowledge safely housed online. From a hardware perspective, we’re not required to acquire specific infrastructure to deploy AI models. Azure offers that {hardware} immediately.”
What’s driving your team’s adoption of cloud computing?
- Migrating to Azure significantly lowers upfront costs associated with deploying AI and ongoing expenses for AI maintenance, compared to on-premises infrastructure. According to the research, organisations can expect a financial gain of at least USD $500,000 over three years by leveraging Microsoft’s cloud-based AI and machine learning capabilities in Azure, resulting in a 15% reduction in costs compared to maintaining an on-premise infrastructure.
- Without adequate infrastructure, on-premises systems often struggle to scale, hindering the ability of survey respondents to operate effectively. Respondents relying on on-premises infrastructure reported that their existing systems’ limited scalability hindered the deployment of AI and ML solutions, prompting them to consider cloud-based alternatives at a rate 1.5 times faster than those adopting Azure cloud infrastructure for similar purposes.
- By transitioning to Azure, interviewees gained seamless access to innovative AI solutions and the flexibility to build and scale their applications without being burdened by infrastructure concerns. Compared to 43% of those with on-premises infrastructure? The Chief Technology Officer of a prominent healthcare organization declared:
After migrating to Azure, all underlying infrastructure concerns vanished, which is typically the primary obstacle when adopting innovative technologies in the past.
—CTO for a healthcare group
They emphasized that “Azure’s scalability is unparalleled, allowing us to effortlessly scale up and respond quickly, which we’ll showcase to the group.” Moreover, they noted that “Prior to migrating to the cloud, accessing AI capabilities on-premises was much more complicated than it is now from a cloud-based perspective.” Starting to consume content is much easier and more straightforward when it’s accessible from the beginning. The platform enabled the company to step outside its industry norms, leveraging capabilities that lay beyond its traditional scope.
- Beyond cost and efficiency benefits, the study revealed that migrating to Azure significantly accelerated innovation with AI, permeating all levels of an organization.
- Investing in upskilling workers to develop a deep understanding of AI, build expertise in its applications, and cultivate ethical decision-making processes is crucial for effective utilization of artificial intelligence. Many interviewees and survey respondents reported struggling to find qualified resources to support their AI and machine learning (ML) projects within their own companies.
- As companies transitioned to the cloud, previously allocated resources became available, allowing them to retrain employees and redirect investments towards innovative pursuits such as artificial intelligence development? As we’ve navigated this AI transformation, we’ve actually increased our engineering capabilities without downsizing, allowing us to accomplish more with the same resources. We’ve invested in AI, but the key point is that our entire team was already on board, with no new hires involved. “These individuals may need to be reassigned as a consequence of our efforts to optimize operations and improve efficiency elsewhere.”
- As emerging technologies like artificial intelligence disrupt entire sectors, companies must master innovation across multiple dimensions to thrive, including capitalizing on platforms and ecosystems that fuel creative advancements? By moving their operations to the cloud, interviewees gained access to a wealth of new resources and capabilities, allowing them to more easily leverage the latest technological advancements and innovations while minimizing risk.
- compared to a mere 34% that rely solely on on-premises infrastructure. The government head of cloud and DevOps for a banking group observed that migrating to Azure fundamentally shifts a company’s mindset towards innovation, as cloud-based services become readily available. You won’t have to venture out to find what you’re looking for. As AI emerged from its infancy in our knowledge domain, an initial focus on experimentation led to limited applications. However, with our organization’s existing cloud infrastructure, access to this technology has expanded across teams.
What’s your current IT infrastructure setup and what specific AI-related workloads are you looking to migrate to Azure? Would you like guidance on how to assess your organization’s AI-readiness for cloud adoption, or perhaps recommendations on the most suitable Azure services for your AI use cases?
According to Forrester’s research, organizations stand to reap substantial financial and strategic advantages by migrating to Azure, thereby positioning themselves for seamless adoption of AI technologies. As organisations navigate the AI-driven future, decreasing prices, amplified innovation, strategic resource allocation, and enhanced scalability render Azure migration an attractive, transparent option for successful transformation.
Ready to kickstart your seamless migration experience? Here are additional resources worth exploring:
- Master the art of migrating to Azure for AI-readiness.
- The solutions that may assist your group’s migration and modernization targets.
- Our platform presents tailored funding, unique value propositions, expert assistance, and best-in-class practices for all use cases, from seamless migration to innovative applications of AI.
- Discover innovative strategies and best practices for successful migration through our comprehensive e-book and video guide?
