In a significant demonstration of artificial intelligence's growing impact on enterprise technology, Amazon Web Services has revealed that its AI-powered modernization tool, Transform, has saved an estimated 335 developer years of work in the last twelve months. The announcement, made during Amazon's third-quarter earnings call, underscores a broader trend of enterprises leveraging AI to tackle complex and historically labor-intensive IT challenges. The 335-year figure, which equates to approximately 700,000 hours of manual effort, highlights the substantial productivity gains being realized through the automation of legacy system migration and modernization.[1][2][3][4][5] This development comes as AWS reported a 20% year-over-year revenue increase to $33 billion, its fastest growth rate in 11 quarters, largely attributed to the surging demand for AI-related workloads.[1][2][6][3]

AWS Transform, which became generally available in May 2025, functions as a generative AI-powered assistant designed to streamline the complex process of moving outdated enterprise workloads to the cloud.[1][7] The service deploys specialized AI agents to automate a wide array of intricate tasks that have long been a bottleneck for digital transformation initiatives.[8][7] These tasks include application discovery, dependency mapping, code analysis, refactoring, and migration wave planning.[8][7][9] By automating these processes, Transform significantly reduces project timelines and the potential for human error, allowing companies to modernize hundreds of applications in parallel.[10][8] The platform specifically targets some of the most challenging legacy environments, including VMware, mainframes running COBOL, and older .NET applications, which are still prevalent in many large organizations.[7][9] For instance, the service can decompose monolithic mainframe applications into modern, cloud-optimized Java applications and help migrate .NET applications from Windows to open-source alternatives like Linux, which can reduce licensing costs by up to 40%.[10][8][7][11]

The real-world impact of AWS Transform was further illustrated by specific customer examples. During the earnings call, Amazon CEO Andy Jassy noted that customers have already used the tool to analyze a staggering one billion lines of mainframe code.[1][2] He highlighted the case of Thomson Reuters, which utilized Transform to process 1.5 million lines of code per month, achieving modernization speeds up to four times faster than with other migration tools.[1][8] This acceleration is crucial for large enterprises, where 70% of Fortune 500 companies still rely on software written over two decades ago.[7] The service's capabilities extend to complex network configurations as well; for VMware migrations, tasks that could traditionally take two weeks, such as network setup and translation, can now reportedly be completed in about an hour.[7] This efficiency is achieved through a multi-agent, multi-model approach, leveraging various foundational models through AWS Bedrock and graph neural networks to analyze dependencies and orchestrate the migration process.[7][12]

The success of AWS Transform is a key component of Amazon's broader strategy to dominate the enterprise AI space. The company's strong third-quarter performance, which saw AWS achieve an annualized revenue run rate of $132 billion, was explicitly linked to customer adoption of its AI services.[1][2] Beyond Transform, Jassy also pointed to the rapid growth of Kiro, Amazon's agentic coding tool, which has seen its user base double to over 200,000 developers since its preview release.[1][2] Another critical piece is the AgentCore platform, which enables developers to build and scale their own AI agents. Jassy mentioned that Cohere Health is using AgentCore to develop agents that could cut medical review times by 30% to 40%.[1] These tools collectively signal a shift in software development and IT management, where AI assistants are becoming integral to improving productivity, reducing costs, and accelerating innovation.

In conclusion, the claim that AWS Transform has saved 335 developer years is more than just a headline-grabbing metric; it represents a tangible shift in how businesses approach digital transformation. By automating the most arduous aspects of modernizing legacy systems, AWS is not only delivering significant cost and time savings to its customers but also lowering the barrier for enterprises to adopt modern cloud-native architectures. This development, coupled with the impressive growth in AWS's AI-driven revenue, solidifies the central role that artificial intelligence will play in the future of enterprise computing. As AI tools become more sophisticated, the productivity gains seen with Transform are likely to be replicated across a wide spectrum of business operations, fundamentally reshaping the nature of work in the technology industry and beyond.