Enterprise AI is no longer confined to business operations and customer service; it's moving into the core engineering layer where software gets built. A new strategic partnership between NTT DATA, a $30 billion technology services company serving 75% of the Fortune Global 100, and Cursor, an AI coding platform, signals a fundamental shift in how large organizations approach digital transformation. Instead of bolting AI onto existing systems, enterprises are redesigning their entire software development processes around AI-native architectures.

This represents a departure from how many companies have historically adopted AI. Rather than treating artificial intelligence as an add-on feature or a business automation tool, organizations are now embedding intelligence directly into the engineering and delivery engine that builds and maintains their mission-critical systems. The reasoning is straightforward: if AI is going to transform how businesses operate, it needs to be woven into the foundation of the software that runs those businesses.

What Does AI-First Software Development Actually Mean?

Traditional enterprise software was designed to execute predefined workflows and business rules. A customer service system follows a script. An inventory system tracks stock levels. These applications work well for stable, predictable operations, but they struggle when businesses need to adapt quickly or handle complex, unstructured data.

AI-first software development flips this approach. Instead of building rigid workflows first and adding intelligence later, organizations design applications around intelligence from the beginning. This means software that can analyze large volumes of data, generate insights in real time, support operational decision-making, automate repetitive workflows, and continuously improve based on feedback.

"Enterprise modernization is no longer just about moving systems to the cloud; it is about reimagining how software is built and operated in the age of AI," said Abhijit Dubey, CEO and Chief AI Officer at NTT DATA.

Abhijit Dubey, CEO and Chief AI Officer, NTT DATA

For NTT DATA, this partnership with Cursor means deploying AI agents directly into the development environment where engineers write code. Cursor's platform allows developers to write, review, refactor, and modernize code with what the company calls "codebase-wide context," meaning the AI understands the entire structure of a software system, not just individual code snippets. This capability is paired with enterprise-grade governance features, including organization-wide privacy controls, single sign-on authentication, centralized administration, and audit-ready policy enforcement.

Why Are Enterprises Rebuilding Systems Around AI Now?

Several converging pressures are driving this shift. First, legacy systems built decades ago often have fragmented data environments where critical information is scattered across disconnected applications. This fragmentation makes it nearly impossible to deploy AI effectively, because AI thrives on access to unified, high-quality data. Modern AI-first architectures help consolidate these data sources, creating a foundation for analytics and intelligent automation.

Second, competitive pressure is intensifying. According to McKinsey's 2024 research, 78% of organizations now use AI in at least one business function, and 79% of business leaders believe AI adoption is essential to remain competitive. The Work Trend Index 2024 found that 75% of knowledge workers already use AI in their daily work, signaling that AI adoption is no longer optional.

Third, customer expectations have shifted dramatically. Today's customers expect personalized experiences, faster responses, and seamless digital interactions. AI-first applications help organizations meet these expectations by understanding user behavior, analyzing context, and delivering more relevant experiences.

How to Implement AI-First Software Development in Your Organization

• Unify Your Data Foundation: Before deploying AI agents in your engineering layer, consolidate fragmented data sources across disconnected applications. This creates the high-quality, accessible data that AI systems need to function effectively.
• Establish Enterprise-Grade Governance: Implement centralized controls for AI tools, including privacy modes, single sign-on authentication, granular agent controls, and audit-ready policy enforcement. This ensures AI adoption remains aligned with organizational standards and regulatory requirements.
• Start with Priority Teams: Rather than rolling out AI coding tools across your entire engineering organization at once, deploy them first to priority teams and establish a center of excellence to scale capabilities gradually and learn from early adopters.
• Redesign Workflows Around Intelligence: Move beyond patching legacy systems. Modernize applications to support AI capabilities like real-time insights, automated decision-making, and continuous learning from user interactions and feedback.

NTT DATA is initially deploying Cursor Enterprise to priority engineering teams and plans to expand deployments as adoption scales globally. The company also plans to establish a Cursor Center of Excellence to help scale these capabilities across global practices and industries.

What Business Benefits Does This Approach Deliver?

Organizations rebuilding systems around AI are not simply upgrading technology; they are creating a foundation for long-term business growth. The benefits include higher operational efficiency through automation of repetitive tasks, faster decision-making enabled by real-time insights, improved scalability without proportional workforce increases, better customer experiences through personalization, and greater business agility to respond to market changes.

For NTT DATA's clients, this partnership translates into real-world results. By using AI agents in the engineering layer, the company can modernize legacy codebases faster, accelerate cloud and AI transformation initiatives, and drive greater consistency across delivery environments. Critically, this keeps modernization efforts aligned with enterprise-wide AI strategies, preventing the fragmentation that often occurs when different departments adopt AI independently.

"NTT DATA is putting AI at the core of how engineers modernize complex systems," said Jordan Topoleski, Chief Operating Officer at Cursor.

Jordan Topoleski, Chief Operating Officer, Cursor

The shift toward AI-first software development also has geographic implications. As enterprises worldwide accelerate this transformation, Vietnam is emerging as a strategic destination for AI development and software innovation. The country produces thousands of IT graduates annually and has attracted significant investment from global technology companies. Vietnam's AI market is projected to reach approximately $1.5 billion by 2030, supported by government initiatives and increasing investment in digital transformation.

The partnership between NTT DATA and Cursor represents more than a vendor relationship; it signals how enterprise AI is maturing. Rather than treating AI as a business tool that employees use, leading organizations are embedding AI into the systems and processes that build and maintain their entire technology infrastructure. This approach addresses a fundamental challenge: if AI is going to drive business transformation, it needs to be native to how software is designed, built, and operated at scale.