en.Wedoany.com Reported - NTT DATA and Cursor have announced a partnership to embed multi-model AI agents into engineering and delivery processes, aiming to help enterprises accelerate the modernization of legacy codebases. This decision is seen as a structural shift in software development approaches for large IT service providers, intended to enhance delivery consistency.
The collaboration leverages AI-native agents provided by the Cursor platform, which are capable of writing, reviewing, refactoring, and modernizing code based on the full codebase context. The platform also integrates governance features, including organization-wide privacy mode, single sign-on, centralized management, fine-grained agent control, and auditable policy enforcement, to meet enterprise compliance requirements in regulatory and distributed team collaboration scenarios.
NTT DATA's CEO and Chief AI Officer defines modernization as "reimagining how software is built in the AI-driven era," rather than merely migrating to the cloud. Industry data shows that, according to Gartner's forecast, by 2028, 75% of enterprise software engineers will use AI code assistants, a significant increase from less than 10% in early 2023. AI agents operate directly within the developer environment, reducing repetitive manual work for engineers during complex refactoring or large-scale migrations. Industry research indicates that, with standardized governance policies, AI-assisted coding tools can boost developer productivity by 15% to 35%.
The broader industry context also underscores this trend. IDC projects that global spending on AI-centric systems will reach approximately $300 billion by 2026, with modern developer productivity being a key driver. McKinsey data shows that 60% to 70% of developer time in large organizations is spent on maintenance and modernization tasks. In terms of governance, the Linux Foundation's AI and Data Initiative emphasizes the importance of formal governance and human oversight, while enterprises tend to adopt frameworks such as the NIST AI Risk Management Framework or the OECD AI Principles.
Competition in the AI-assisted development space is intense, with tools like GitHub Copilot, Amazon Q Developer, and Google Cloud already widely deployed. Multi-model coding platforms differentiate themselves through deep integration with developer environments, while global service providers leverage scale and deployment experience. This deployment positions NTT DATA as one of the major global service companies placing AI agents at the core of its engineering model, while its partner gains access to large-scale enterprise environments to validate its approach.
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