Cloud migration and application modernization have become make-or-break imperatives for enterprises, yet traditional approaches often stumble under the weight of complexity and legacy systems. Now, agentic AI is revolutionizing this challenge, offering business leaders a faster, smarter path to cloud transformation — and reshaping what's possible for organizations ready to embrace it.
The Migration Imperative and AI's Transformative Role
Cloud adoption is on the rise again in 2025, with Foundry reporting that 63% of businesses are accelerating cloud migration plans. AI is a central driver of that growth. This surge reflects a growing recognition that AI capabilities, cloud infrastructure, and application modernization are increasingly interconnected.
However, many organizations find themselves constrained by legacy workloads that are ill-suited for cloud environments. The struggle is that these same workloads contain critical applications and data that should be at the core of any AI strategy.
"Agentic AI represents a paradigm shift in how we approach enterprise IT transformation," says Swami Sivasubramanian, VP of agentic AI at Amazon Web Services (AWS). "It's not just about automating repetitive tasks. It's about having an AI system that can understand the nuances of your application landscape, make intelligent decisions, and execute migrations with minimal human intervention."
These AI systems create an entirely new migration experience by using advanced foundation models, LLMs, machine learning, graph neural networks, and automated reasoning.
Agentic AI: Your Team's New Transformation Assistant
AWS Transform, the first agentic AI service developed to accelerate enterprise modernization of .NET, VMware, and mainframe workloads, is revolutionizing cloud migration by automating manual processes while keeping IT teams in control. The service's AI agents act as transformation assistants, collaborating with customers and partners to tailor migration projects to specific needs.
The power of these agents lies in their ability to automate complex tasks that once required weeks and months of manual effort and multiple specialized teams. Where IT staff previously spent countless hours manually discovering workloads, mapping complex dependencies, and analyzing infrastructure requirements, AI agents now handle these tasks automatically and generate customized migration and modernization strategies. These strategies include precise recommendations for rightsizing, financial modeling, and cost optimization. During execution, these AI agents can autonomously migrate workloads, convert legacy code, and modernize database structures, significantly accelerating the entire process.
The results are dramatic: assessment tasks that typically take weeks are now completed in minutes, enabling data-driven decisions from day one. For .NET applications, organizations are modernizing applications up to 4x faster while achieving up to 40% reduction in licensing costs. VMware migration planning is reduced from weeks to minutes, with network translations being completed up to 80 times faster. Mainframe modernization of IBM z/OS applications is accelerated from years to months, including automated documentation generation.
"We were spending too much time upgrading old code manually. It was slowing us down and competing with our road map. Other cloud providers' tooling helped, but wasn't designed to modernize at scale or harness generative AI. We needed a leap, not just an incremental fix," explained Matt Dimich, VP, Platform Engineering Enablement, Thomson Reuters. "AWS Transform felt like an extension of our team— constantly learning, optimizing, and helping us move faster."
Experience Meets AI: Powering Transformation at Scale
An AI system is only as good as the knowledge that powers it. In enterprise transformation, decades of migration experience, industry expertise, and proven methodologies form the critical building blocks that help AI agents make informed decisions about complex workloads. This deep domain knowledge enables AI to understand not just what to migrate, but how to preserve business logic, maintain compliance, and optimize costs throughout the process.
"This shift from scripts and disconnected tools to intelligent, self-learning, automated workflows help enterprises modernize their most complex workloads with speed and confidence," explains Dr. Asa Kalavade, VP of AWS Transform. AWS brings two decades of cloud migration expertise to this challenge, incorporating lessons learned from thousands of successful migrations across Microsoft, VMware, SAP, and mainframe workloads.
The power of this approach multiplies through partner collaboration. Global leaders can embed their domain expertise directly into transformation workflows, creating what Sivasubramanian calls "a powerful force multiplier" that "allows organizations to tackle even the most complex migrations with confidence." Partners like Accenture, Capgemini, CAST Software, IBM Consulting, and Mission Cloud bring industry-specific knowledge that enhances the AI's ability to handle unique business requirements and compliance needs.
Beyond Migration: Powering the AI-Driven Enterprise
AI-powered migration is more than a move to the cloud—it's a springboard for future innovation. By modernizing applications and infrastructure with cloud-native technologies, organizations create a foundation for advanced AI and machine learning initiatives. As Sivasubramanian notes, "We're just scratching the surface of what's possible. The organizations that embrace this technology now will be best positioned to lead in the AI-driven future."
For business and technology leaders, the message is clear: AI-powered cloud migration and modernization is a transformative approach that will redefine enterprise operations in the digital age. Early adopters stand to gain significant competitive advantages in an increasingly AI-powered world.
The future of business is in the cloud, powered by AI. Are you ready to lead?
To learn how AI can accelerate your cloud journey, visit https://aws.amazon.com/ai/generative-ai/
This post was created by AWS with Insider Studios.
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