Building for AI: Modernizing applications with Microsoft Azure

Applications are central to enterprise performance, and they’re being entirely transformed by agentic AI. This new era of agentic automation is revolutionizing application modernization and redefining what applications can do for organizations.

No longer mere static systems, applications are evolving to become intelligent, adaptive and intent-centric. “Frontier firms,” as Microsoft describes them, are redefining their applications as data-driven and adaptive, infused with decision-making power and serving as catalysts for innovation.

Powered by agentic AI and Microsoft Azure, forward-looking organizations are transforming how applications deliver value across experiences, improve productivity and influence industry outcomes. But what does this look like? And what do organizations need to know?

Let’s explore three key paradigm shifts that are changing the way organizations think about their approach to building modern applications.

1. Reimagine applications as intent-centric for value transformation

Traditional enterprise systems rely on developers and business analysts to define every rule, process and workflow to ensure consistent operations. As a result, applications are designed once and behave the same way for every user.

In an ongoing shift, modern applications are becoming increasingly proactive systems that understand and act on business intent. Yet understanding intent is only part of the equation. Real value is realized when applications can translate intent into coordinated, autonomous action across the enterprise. Platforms built on Azure embed AI agents that streamline processes, enforce compliance and deliver personalized experiences. Intelligent workflows then automate decision-making, reduce manual intervention and improve reliability at scale.

Sophisticated workflow engines orchestrate the AI agents at the core of these applications and coordinate the seamless handoff of tasks between human actors and AI agents. This design streamlines business operations and boosts throughput because individuals can process more requests without increasing resource allocation.

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Giving AI agents reliable access to the data they need is a fundamental challenge in agent-augmented applications. Humans can bridge information gaps through informal, ad hoc communication, but agents are constrained to the systems and data sources to which they are explicitly connected.

Organizations are confronting this constraint by consolidating fragmented data into a unified platform that becomes a shared environment enabling agents to collaborate and act seamlessly. However, giving agents access to business-critical data requires strong guardrails to avoid exposing or unintentionally propagating sensitive data while agents pursue their goals.

AI agents in action for efficient order management

NTT DATA worked with a global security provider seeking to modernize and streamline their order management processes to support a rapidly expanding partner ecosystem. At the time, employees had to handle customer orders manually — receiving requests by email or phone, then entering each order into the enterprise resource planning system for tracking. Order details and supporting assets were exchanged separately, often verbally or through additional emails.

This legacy system presented numerous challenges. It depended on highly trained employees who understood every detail of the company’s operations, including complex product bundles, pricing models and availability constraints. As a result, onboarding new employees was difficult, as it required deep operational knowledge from the outset. Manual processes also increased the risk of human error and inconsistency, while the absence of built-in compliance controls left the system vulnerable to misuse or fraud by users with privileged access. Collectively, these issues increased operational costs and exposed the company to meaningful financial and reputational risk.

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To address these challenges, NTT DATA developed a comprehensive, cloud-native, AI-driven platform allowing external customers to interface directly and seamlessly with the system when placing orders. AI agents are embedded throughout the order lifecycle to help human operators validate and process orders efficiently. The system executes order validations, performs error and fact checks, and ensures compliance with corporate policies.

Built on scalable, Microsoft Azure-based architecture, the solution has exceptional fault tolerance with high operational reliability and accuracy. Confidential information is shared securely with customers without human intervention, ensuring both privacy and compliance.

The platform has also significantly improved employee efficiency. New hires become productive up to 80% faster, with minimal training. Operational costs are down 40%, the same employee base now handles many more orders thanks to automation, and AI guardrails ensure that information is shared only with authorized actors.

The takeaway

Think about modernizing where your people and your customers feel the most pain. Target manual, archaic business processes that slow them down. Combine autonomous AI agents with clear guardrails and human-in-the-loop oversight so that expertise scales and risk stays controlled.

2. Increase developer productivity through AI-augmented development

Agentic AI is redefining the software development lifecycle by embedding intelligence into every stage of the process. Traditional development models often struggle with complexity, extensive manual coding and lengthy testing cycles. Developers are required to write every line of code, enforce standards and perform repetitive quality assurance activities to deliver robust solutions.

AI agents now elevate each phase of the development lifecycle, making the process easier and faster. This increased velocity translates into business agility. CIOs see it in shorter time to market and tighter alignment between IT and business priorities. Developers experience it as greater freedom to innovate and the satisfaction of seeing their work create tangible impact more quickly than ever before.

AI copilots for efficient software development

A clear example of this evolution is the adoption of AI copilots within modern development platforms, such as NTT DATA’s aXet AI coding assistant. These copilots integrate directly into the developer workflow to offer real-time guidance, automate boilerplate code and assist with complex logic. Through embedded AI, developers can reduce errors, improve maintainability and speed up delivery. This approach also strengthens collaboration, as AI copilots help standardize coding practices and optimize performance across diverse projects.

Powered by Microsoft AI technologies, aXet automates key aspects of the development lifecycle — from generating production-ready scaffolding code for user interfaces and application programming interfaces to reverse-engineering existing applications and translating outdated business logic into modern languages such as Java, .NET or Node.js. The platform also automatically generates unit tests, enforces code quality through integrated static and dynamic application security testing scans, and produces thorough documentation, enabling teams to deliver faster, higher-quality and more maintainable solutions.

By integrating these copilots, driven by Microsoft AI, into NTT DATA’s internal engineering platform, we have enabled developers to deliver high-quality, production-grade applications faster and more efficiently. These tools automate foundational and repetitive development tasks while human teams focus on innovation and tasks with higher business value.

NTT DATA has used aXet to help a large-scale logistics company in the Asia-Pacific region to rewrite their PHP-based legacy applications into a modernized, .NET-based solution up to 40% faster than through conventional means.

The takeaway

To modernize your organization, also modernize how you build. Adopt AI-assisted engineering in code generation, refactoring and testing, standardize pipelines and measure outcomes such as lead time changes, deployment frequency and change-failure rate.

3. Support industry-specific innovation — sustainably

Modernization is no longer about simply converting legacy systems into microservices. Instead, it’s a step toward building intelligent applications that support new business experiences and processes, augmented by agentic AI. The cloud-native Microsoft Azure ecosystem provides the foundation for solutions that are both scalable and closely aligned with industry-specific needs.

By combining the flexibility of microservices and serverless architectures with the intelligence of agentic AI, organizations can create applications that deliver measurable business outcomes. These applications address unique operational challenges, regulatory demands and cross-sector sustainability goals.

Applying intelligence to electric vehicle charging

In the energy and mobility industries, for example, NTT DATA partnered with a charging-network operator to implement a unified management application for public, fleet and workplace charging. The application supports the design and operation of complex charging ecosystems for electric vehicles, delivering advanced security, seamless interoperability and deep integration with existing systems for safe and reliable charging.

With embedded AI agents, such applications can predict demand, automate load balancing and support green energy initiatives, making them critical enablers of the global transition to electric mobility. Their modular design allows them to adapt to diverse business models, from public charging networks to private and enterprise-based deployments.

Built on Microsoft Azure cloud infrastructure, our solution delivers resilience, scalability and efficient workload management. Sustainability is a core design principle, achieved through optimized power distribution, the promotion of renewable energy use, and smart load management to improve overall energy efficiency.

A similar transformative impact is seen in industries such as healthcare, finance and manufacturing. Healthcare providers use AI-powered diagnostics and patient engagement tools to improve outcomes and reduce costs, while financial institutions deploy fraud detection and hyperpersonalized services to enhance trust and customer loyalty. In manufacturing, AI-enabled predictive maintenance and real-time optimization minimize downtime and boost efficiency.

Across these sectors, the outcome is clear: Industry-specific innovation that speeds up transformation, delivers operational excellence and supports long-term sustainability objectives.

The takeaway

Move beyond one-size-fits-all modernization. Build cloud-native, AI-enabled applications tailored to your industry’s realities, combining modular architectures, embedded intelligence and sustainability by design to deliver outcomes that scale responsibly and endure over time.

Access valuable expertise through NTT DATA

Modernizing applications is no longer about simply moving to the cloud or rewriting legacy systems; instead, it’s about creating intelligent, adaptive applications and redefining their value to an organization.

Microsoft Azure, combined with agentic AI, provides the foundation for this transformation by offering the speed, intelligence, and flexibility required to build applications that drive business processes forward. The question is how fast organizations can use these capabilities to reimagine what’s possible.

As a Microsoft AI Cloud Partner Program member — one of the first globally to achieve this designation — NTT DATA offers deep Azure experience and proven expertise across 12 advanced specializations, including application modernization, DevOps with GitHub, low-code development and intelligent automation.

Our more than 24,000 Azure-certified professionals and Microsoft Most Valuable Professionals are helping organizations modernize, apply AI with purpose and extend the intelligent cloud into every part of their business. Will yours be next?

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