Rewriting the rules of software development— Fujitsu’s AI is putting rocket fuel into software development —

Article | 2026-2-17
15 minute read
Challenging the entrenched conventions of system development, Fujitsu has developed the "AI-Driven Software Development Platform." Leveraging its proprietary AI technology and LLMs, the platform gains a profound understanding of existing system architectures, autonomously and comprehensively automates complex modifications, from requirements definition through testing. Having achieved a staggering 100-fold boost in productivity through internal implementation, this platform represents a paradigm shift that elevates human-AI collaboration to a new dimension. We are on the cusp of a major transformation that will unlock entirely new business horizons.
For decades, software development has operated under a familiar set of assumptions. In a world where corporate IT systems are intricately interconnected, and development teams must adjust to changing regulations and business rules, the “person-month” model has been the accepted way of delivering software projects.
The limitations faced are real. Complexity makes systems harder to change, manual processes slow innovation, and traditional commercial models often stifle incentives for productivity. But although companies recognize these constraints, there has been little they could do to break free, leaving them stuck in entrenched patterns, with digital transformation moving slower than strategy demands.
Overturning this long-standing impasse, Fujitsu has launched a new service: the “AI-Driven Software Development Platform”. At its core are Fujitsu’s proprietary AI technologies and large language models (LLMs), which allow the system to understand the complex structures of existing corporate IT systems. They manage the full development cycle, from requirements definition and design to coding and integration testing. They can even incorporate tacit knowledge that is often unique to individuals or teams. When laws or regulations change, AI agents can autonomously update systems, extracting requirements directly from legal documents and implementing modifications end-to-end. Internal deployments at Fujitsu demonstrated dramatic results: tasks that once required three “person-months” were completed in just four hours, delivering roughly 100 times the productivity of conventional methods.
But this is not simply a model in which humans draft specifications and AI generates code. It goes far beyond that. It is a fundamental shift in how systems are built, one in which AI takes on the complete automation of development, dynamically adapting to changes of regulation, and business environments and parameters.
Fujitsu is applying this approach internally, transforming its long-established system integration (SI) business, accelerating in-house development capabilities, and setting a new benchmark for “blazing-fast” productivity. What emerges is not incremental improvement, but a redefinition of how system development can and should work.
The "three challenges" in System Development: Structural Barriers to Transformation
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"LLM × Requirements Definition AI × Tacit Knowledge": Achieving Complete Automation Through Internal Implementation
"Japanese systems, especially those of large corporations, have been built while responding to various rule changes. The current state of system development, maintenance, and modification largely relies on manual work. It's an area that requires a certain level of craftsmanship," points out Hideto Okada, Head of AI Strategy & Business Development at Fujitsu. At the same time, technological innovation is steadily advancing, and he felt that "system development must change now." Based on this understanding of the challenges, the "AI-Driven Software Development Platform" project officially started in the spring of 2025. The goal is to complete automation of system development. "We challenged ourselves to realize a world where pressing a button could completely automate the repair of business applications," Okada recalls.



