{"id":3231,"date":"2025-06-05T11:06:08","date_gmt":"2025-06-05T16:06:08","guid":{"rendered":"https:\/\/wiki-cloud.co\/?p=3231"},"modified":"2025-06-10T11:47:50","modified_gmt":"2025-06-10T16:47:50","slug":"transform-enterprise-workloads-with-aws-transform-and-agentic-ai","status":"publish","type":"post","link":"https:\/\/wiki-cloud.co\/en\/2025\/06\/transform-enterprise-workloads-with-aws-transform-and-agentic-ai\/","title":{"rendered":"Transform enterprise workloads with AWS Transform and Agentic AI"},"content":{"rendered":"

Introduction<\/strong><\/h3>\n

In an increasingly dynamic business environment, the ability to adapt quickly to technological changes has become a key factor for competitiveness. Organizations that depend on legacy applications or obsolete architectures, many of which were developed years or even decades ago, face significant challenges, such as difficulty in scaling, high maintenance costs, limited integration with modern technologies and slower development cycles.<\/p>\n

Modernizing these applications is not simply a technical issue; it's a strategic necessity to drive innovation, improve customer experience, and reduce time to market. However, transforming complex and critical systems is no simple task. It requires careful planning, a deep understanding of existing dependencies, and an approach that minimizes operational risks.<\/p>\n

Transforming or modernizing enterprise workloads continues to be a critical challenge for many organizations. Despite the advancement of cloud computing, data shows a strong reliance on traditional infrastructures.<\/p>\n

<\/strong><\/h3>\n

Source: AWS<\/p>\n

\n
\ud83d\udca1<\/div>\n
According to Gartner<\/strong>, 70% of workloads still run in on-premises<\/em>environments, reflecting a significant opportunity and urgency for modernization.<\/div>\n<\/div>\n
\n
\ud83d\udca1<\/div>\n
According to McKinsey<\/strong>, 70% of the enterprise software used by Fortune 500 companies was written more than 20 years ago. This legacy software, while still functional, is often built on obsolete technologies that are difficult to scale, maintain, or integrate with modern solutions.<\/div>\n<\/div>\n
\n
\ud83d\udca1<\/div>\n
ISG Research<\/strong> ISG Research highlights that the average time to complete a migration or modernization is 1.5 years, which it reveals the complexity and duration of these processes when there is a lack of appropriate tools or automated approaches.<\/div>\n<\/div>\n

In this context AWS Transform<\/strong> enters into play (previously presented as Amazon Q Developer transformation capabilities at re:Invent 2024), an AWS commitment to modernizing these types of applications, infrastructure, and systems by leveraging the capabilities of Artificial Intelligence (AI) and Agentic AI, which is currently available to the public (GA) since mid-May 2025.<\/p>\n

What is AWS Transform?<\/strong><\/h3>\n

<\/strong><\/h3>\n

AWS Transform<\/strong> is a revolutionary service that uses Agentic AI with the goal of accelerating and simplifying the migration and modernization of infrastructure, applications and source code. In other words, it is a service that uses specialized AI agents that help eliminate the heavy lifting of transformation by automating complex migration and modernization tasks for .NET, Mainframe and VMware application workloads. Additionally, it offers an assessment service, where workload migration planning and business case generation is performed.<\/p>\n

AWS Transform<\/strong> through Agentic AI utilizes AWS advances in foundational models, LLMs, machine learning, neural networks, automated reasoning, and AI infrastructure to deliver a fully advanced migration and modernization experience.<\/p>\n

Currently AWS Transform<\/strong> offers three types of transformation agents which are for .NET applications, Mainframe (COBOL z\/OS) applications and VMware.<\/p>\n

After running many transformations for various customers by AWS, it can be concluded (data AWS Blog) that:<\/p>\n

\n
\ud83d\udca1<\/div>\n
The AWS Transform for .NET<\/strong> can modernize Windows-based .NET applications to Linux up to four times faster than traditional methods and achieve savings of up to 40% in licensing costs.<\/div>\n<\/div>\n
\n
\ud83d\udca1<\/div>\n
The AWS Transform for Mainframe<\/strong> can break down monolithic COBOL z\/OS applications into components that can run in the cloud in minutes instead of months.<\/div>\n<\/div>\n
\n
\ud83d\udca1<\/div>\n
The AWS Transform for VMware<\/strong> can automate the conversion of VMware on-premises network configurations to their AWS equivalents up to 80 times faster than manual techniques.<\/div>\n<\/div>\n

AWS Transform<\/strong> leverages the conversational expertise of Amazon Q<\/strong>, which acts as an expert transformation assistant. This assistant actively collaborates in defining modernization and\/or transformation project objectives, evaluating business plans and cost savings projections. It also facilitates the review and adaptation of transformation and\/or modernization plans, as well as the validation of suggestions related to code and infrastructure, all through specialized agents<\/strong>.<\/p>\n

AWS Transform<\/strong> enables seamless collaboration across cross-functional teams through a unified web experience<\/strong>, where it is possible to manage tasks, track progress and coordinate efforts at every stage of the process. In this way, AWS Transform<\/strong> provides full control and continuous visibility into transformation and\/or modernization plans, ensuring execution aligned with business objectives.<\/p>\n

<\/strong><\/h3>\n

Benefits<\/strong><\/h3>\n

The key benefits of using AWS Transformation are highlighted below:<\/p>\n