Enterprise AI transformation relies on the end-to-end platform: Azure was built for this moment

As enterprise AI begins to be implemented widely, we are seeing our customers adopt a multi-model approach. Businesses are opting for cutting-edge models for their advanced capabilities and smaller, specialised, open-weight models where cost-effectiveness and precise controls are needed. However, the true value lies not in the individual models themselves but in how all components work together: infrastructure, data, applications, agents, security, and operations. This integrated, compounded value is what Microsoft Azure is fundamentally designed to deliver.

A Holistic System: From Silicon to Agents

Our integration extends deeply into the underlying infrastructure of the model. Customers seek flexibility, allowing them to select models and infrastructure without the hassle of individually configuring and tuning every layer. With decades of experience in running mission-critical systems and managing some of the world’s most demanding AI services on a large scale, Microsoft believes that the extensive integration and variety available across its platform—including developer tools and AI applications—play a crucial role in its recognition as a Leader in both the 2026 Gartner® Magic Quadrant for Strategic Cloud Platform Services and The Forrester Wave: Public Cloud Platforms, Q3 2026.

While we are grateful for this recognition, we understand that it is vital for customers today to pick platforms that will shape their infrastructure for many years to come. The choice should be made based on the capabilities of the entire system, as cloud platforms now need to do much more than offer standalone services. They must support varied models and infrastructure, helping businesses to build quickly, maintain reliability, manage risks, control costs, and enhance results. When developing the next wave of AI applications, how these layers integrate is far more significant than any one feature.

Microsoft’s position as a Leader in the 2026 Gartner® Magic Quadrant follows similar recognitions in the previous three years (2025, 2024, and 2023). We think what counts most for clients is the platform’s ability to translate technology into tangible outcomes: superior performance, increased cost-efficiency, quicker delivery, and scalable critical systems.

Additionally, Microsoft was recognised as a Leader in The Forrester Wave: Public Cloud Platforms, Q3 2026. Forrester’s analysis evaluates both the robustness of current offerings and the strategic vision behind them. This acknowledgment further highlights Azure’s progression, especially as clients transition from isolated AI initiatives to comprehensive production systems.

Forrester commends Microsoft for its vision of a unified, vertically integrated Azure system.

Flexible Choices Without Complexity

Adopting a multi-model strategy doesn’t imply that every model needs to function in the same manner. The platform should facilitate these choices across diverse computing environments while ensuring uniform security, identity management, governance, and reliability.

Microsoft Foundry plays a central role in this strategy. It provides developers with a variety of model options, alongside tools to assess, secure, monitor, and manage AI systems, all powered by Azure’s infrastructure. Instead of forcing all workloads into a single model, it allows teams to tailor their choices based on specific workloads while maintaining consistency across cloud, on-premises, edge, and third-party environments.

Leveraging Data for AI’s Business Impact

While model preferences will continue to evolve, the data and business context that bring real value to AI remain constant. Customers want to handle data where it already exists, avoiding unnecessary duplication and ensuring governance is maintained. As Forrester aptly puts it: “Models may change; data is fundamental.”

Microsoft Fabric consolidates analytics and data, while Microsoft Purview implements governance across this ecosystem. Azure’s databases, including Azure SQL and Azure Cosmos DB, effectively bridge AI with existing operational data. Additionally, Microsoft IQ delivers a unified intelligence layer, ensuring applications and agents receive consistent business context across all areas. All these features enable organizations to switch models without the need for extensive data, governance, and contextual changes.

For example, UNC Health showcases the importance of this foundational structure. By updating its analytics capabilities, the institution is developing a governed data environment that meets the needs of care, operations, and research in a highly regulated sector. This is the kind of groundwork necessary for responsibly applying AI at scale.

Modernisation as a Catalyst for AI

The applications that drive a business today hold extensive business logic, data, and operational insights. They need a contemporary environment where they can maintain support for established processes while connecting to innovative AI experiences. Hence, modernisation becomes an integral part of the AI journey rather than a separate initiative. Each workload presents a decision-making opportunity: should it be migrated, updated, used as a managed service, connected to agents via secure interfaces, or rebuilt if there’s a clear business reason?

Levi Strauss & Co. elucidates how modernisation and AI can intertwine seamlessly on the same path. The company modernised its legacy systems on Azure, establishing a more robust foundation, and subsequently harnessed Microsoft Foundry to deploy agents that simplify tasks and enhance decision-making. This heritage brand didn’t need to abandon its existing operations in order to embrace AI; instead, they improved their foundational infrastructure and progressed from there.

Agents are invaluable for assisting teams in evaluating applications, strategising upgrades, refactoring code, testing modifications, and easing migration, all while allowing developers and IT staff to retain control over architecture and business decisions. With GitHub Copilot, modernization is supported for .NET and Java applications, fostering connectivity throughout the software lifecycle. Analyst feedback underscores the importance of this approach: Gartner praises Microsoft’s balanced view on application modernisation and its comprehensive software developer lifecycle, while Forrester highlights our clients’ appreciation for Microsoft’s migration and modernisation skills. The aim is straightforward: to help clients modernise the applications they already depend on so that they are prepared for the future of AI.

Empowering Every AI Ambition

As businesses implement increasing amounts of AI, the platform must become more efficient, reliable, and easier to navigate. Clients require the freedom to select the models and infrastructures that best suit their needs, all while the platform simplifies the integration of these options.

We are thrilled to be acknowledged as Leaders by both Gartner and Forrester, and we are even more excited by what these assessments reveal about the direction of the industry. We anticipate that the future of cloud will hinge on how effectively platforms can unite infrastructure, data, models, applications, and developer tools, while ensuring the flexibility needed as each layer adapts and evolves.

This is the path we are forging with Azure, and we are eager to continue developing what comes next, hand in hand with our customers and partners.

Explore the 2026 Gartner® Magic Quadrant for Strategic Cloud Platform Services. Read the report.

Check out The Forrester Wave: Public Cloud Platforms, Q3 2026. Read the report.

Gartner® Magic Quadrant for Strategic Cloud Platform Services, 2026. By Alessandro Galimberti, Carolin Zhou, Douglas Toombs, Dennis Smith, Ed Anderson, Tobi Bet, Chuck Lawton, 1 September 2026.

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