Drive AI application development through cloud modernization | Microsoft Azure Blog

If your organization aspires to harness the power of AI to improve customer experience and drive growth, cloud migration goes far beyond on-premises alternatives.

The advent of generative artificial intelligence has ushered in a new era of intelligent applications that can understand natural language, generate human-like content, and augment human capabilities. But as companies across industries begin to realize the potential of AI to revolutionize their operations, a critical first step is often overlooked: modernizing their on-premises application infrastructure.

If your organization aspires to harness the power of AI to improve customer experience and drive growth, cloud migration goes far beyond on-premise alternatives. Many of the early customers, such as H&R Block and TomTom, reiterated that what set them up for success in the AI ​​era was the fact that they had already begun modernizing their application infrastructure in Azure. A study commissioned by IDC, “Exploring the Benefits of Cloud Migration and Modernization for Intelligent Application Development,” based on interviews with 900 leading IT leaders from around the world about their experiences with migrating applications to the cloud, he brought further insights that connect the dots. In this blog, I will guide you through some insights.

Modernize or Be Left Behind: The Urgency of AI-Driven Cloud Migration

Let’s state the obvious: AI is a powerful technology, capable of creating content, code, and even entire applications. Rapid advances in generative artificial intelligence technologies such as OpenAI GPT-4 have changed the way businesses operate and interact with customers.

But generative AI models like those powering ChatGPT or image generation tools are data-hungry beasts. They require massive computing resources, flexible scaling and access to large datasets to deliver their transformative capabilities. On-premises legacy systems and data stores simply cannot keep up with the compute and data demands of modern AI workloads.

Cloud platforms provide the robust infrastructure and storage solutions necessary to support AI workloads, all fully managed by the provider. They offer virtually unlimited scalability, ensuring applications can handle fluctuating demand and deliver consistent performance. A key finding of the IDC study revealed that organizations were primarily motivated to migrate applications to the cloud by numerous business benefits, including better security and privacy, more efficient integration of cloud services and cost savings. In addition, the cloud’s inherent agility enables enterprises to rapidly experiment, iterate and deploy AI models, accelerating innovation.

In its latest version, the .NET platform is equipped to use artificial intelligence in cloud environments. Developers can integrate AI features into their applications using tools such as Semantic Core and libraries such as OpenAI, Qdrant and Milvus. Integration with .NET Aspire ensures that applications can be deployed to the cloud with optimal performance and scalability. For example, H&R Block’s AI Tax Assistant, developed using .NET and Azure OpenAI, shows how businesses can create scalable AI-driven solutions to improve user experience and operational efficiency. By incorporating .NET into your cloud migration strategy, you can streamline development and accelerate the realization of AI’s potential across your business operations.

Migrating and refactoring legacy on-premises applications to be optimized for the cloud unlocks the ability to leverage AI services, large data stores, and seamlessly scale compute. This can enable your company to not only build generative AI applications, but also fully integrate generative AI across all aspects of their intelligent systems and data feeds.

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Accelerate your AI ambitions in the cloud

A recent IDC study clearly shows a strong correlation between a company’s drive to leverage generative AI and realizing its full value through cloud migration. Let’s break down a few key considerations:

  • Data Availability: Cloud environments make it easy to consolidate and access data from multiple sources, giving AI models the information they need for training and refinement.
  • Computing power: Elastic cloud computing resources can be dynamically allocated to meet the demands of complex AI algorithms, ensuring optimal performance and cost efficiency.
  • Cooperation: Cloud tools facilitate seamless collaboration between data scientists, developers, and business partners, streamlining the AI ​​development and deployment process.

Migrating to the cloud not only enables generative AI, but also accelerates the overall speed of innovation. Cloud platforms provide a wealth of ready-to-use services such as machine learning, IoT, serverless computing, and more that allow companies to rapidly develop and deploy new intelligent features into their applications.

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Leverage AI in the cloud to outpace the competition

The urgency of migrating and modernizing applications isn’t just about keeping up with the times—it’s about gaining a competitive edge. Enterprises that embrace cloud and AI are better positioned to:

  • Attract top talent: The most talented data scientists and developers are attracted to organizations with cutting-edge technology.
  • Adapt to change: The flexibility of the cloud allows businesses to pivot quickly in response to evolving market conditions or customer needs.
  • Drive sales growth: AI-based applications can open up new revenue streams and provide exceptional customer experiences.

Ensure AI-powered innovation by modernizing your cloud

To maintain a competitive edge, cloud migration must go beyond simply picking up and moving applications. It’s about modernization – rebuilding and optimizing applications for the cloud to unlock new levels of agility, scalability and innovation. By modernizing your applications to cloud-native architectures, your business can:

  • Improve functionality: Integrate AI-based features such as chatbots, personalized recommendations, and intelligent automation into existing applications.
  • Performance Improvement: Leverage cloud-native technologies to optimize application speed, responsiveness, and scalability.
  • Cost reduction: Pay only for the resources you use, eliminating the need for expensive on-premise infrastructure.

The majority of IDC survey respondents chose to migrate applications to the cloud because it allowed them to innovate application development and realize a range of commercial benefits more quickly.

Power your intelligent application development with cloud-based AI transformation

Migrating and modernizing applications to the cloud is not only an option, but a necessity in the era of generative artificial intelligence. Companies that act quickly to embrace this transformation will be well-positioned to realize the full potential of intelligent applications, driving innovation, operational efficiency and customer engagement. The synergy between cloud computing and generative artificial intelligence creates unparalleled opportunities for businesses to redefine their strategies and achieve sustained growth in a competitive environment.

By recognizing the urgency and quantifying the benefits, companies can make informed decisions about their cloud migration and modernization journeys and ensure they remain at the forefront of technological advancements and market relevance.

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