AWS Transform’s agentic AI speeds app modernization

Legacy systems drain your progress. Years of patches pile up. Manual fixes take months - or years. Costs spiral as tech debt grows. ZDNet reports (opens in new tab) that firms spend up to 70% of their IT budgets just managing old tech. That leaves little room to build new things.

AWS Transform brings agentic AI to this problem. This isn't just another script. AWS Transform agentic AI modernization plans, adapts, and learns as it handles Windows, .NET, mainframe, and VMware moves.

Why does this matter? Migrations run up to 5x faster. Costs drop up to 70%. Your team stops fighting fires. As "Tech debt" experts note on LinkedIn (opens in new tab), you can finally modernize at scale. You reduce risk. You get ahead - without pausing daily work.

TL;DR: What's New with AWS Transform

Key highlights from AWS re:Invent December 2025:

• Autonomous agents now handle full-stack Windows modernization - .NET apps, SQL Server, custom code - without constant oversight
• 5x faster migrations for mainframe, VMware, and Windows workloads with up to 70% lower long-term costs
• Real results: Air Canada and Thomson Reuters cut migration time from months to weeks using agentic AI capabilities
• Custom language support for homegrown frameworks and legacy code that doesn't fit standard tools

What's New - AWS Transform Agentic AI in Action

Autonomous Agent Handles Full-Stack Windows Modernization

Manual modernization meant endless meetings. Code reviews dragged on. Teams spent months migrating apps one piece at a time. They hoped nothing broke.

Now the AWS Transform agentic AI modernization agent changes that. You feed it your code. It refactors apps and databases on its own.

Example: Air Canada handed over their Windows stack. It was a mess - .NET apps, SQL Server databases, custom connectors tangled together. The agent parsed millions of lines in hours. It flagged old libraries. It rebuilt workflows. It suggested better database designs. No human had to map every detail.

ZDNet showed (opens in new tab) Amazon literally dropped an old server from a crane. That's what this approach does to tech debt - demolishes it instead of chipping away slowly.

Deep Support for .NET, SQL Server, and Mainframe

Breaking free from old systems used to feel risky. With AWS Transform's new tools, it's more like a guided walk.

The agent includes built-in support for complex full-stack Windows modernization. That means deep ties to .NET apps and SQL Server databases.

Example: Thomson Reuters faced years of mainframe logic. COBOL mixed with C# APIs. Client data flowed through both. Running this through the agent took days - not quarters. It caught bugs before they hit production.

Thomson Reuters cut costs by 30% and sped up modernization 4x (opens in new tab) using AWS Transform. They now modernize over 1.5 million lines of code every month.

Large firms can now tackle mainframe and VMware shifts with less disruption to users or daily ops.

Continuous Learning for Custom Languages

Legacy systems rarely fit neat boxes. Homegrown frameworks hide everywhere. Odd scripting languages link key processes. The agent doesn't blink - it learns as it goes.

One global insurer fed AWS Transform 20 years of batch jobs. Three different languages. The AI mapped code ties automatically - even when docs were missing. It refactored business logic step by step. Devs got real-time feedback to review.

This isn't lift-and-shift. It's learning that improves with each run. Future migrations get smarter across any tech stack or language in your org (as LinkedIn experts discuss (opens in new tab)).

You get ongoing upgrades without stalling daily work.

Bottom line: AWS Transform's December 2025 release brings true autonomy to legacy upgrades. It handles custom frameworks at scale. It learns and evolves from real-world patterns we've all seen. For teams exhausted from wasting hours on repetitive migration work, this is a game-changer - less grind, more time to actually innovate.

Real Impact: Air Canada, Thomson Reuters, and Beyond

Air Canada Cuts Mainframe Time From Months to Weeks

Air Canada faced an aging mainframe that blocked digital growth. Manual modernization had failed before. Too slow. Too risky for flight systems.

AWS Transform agentic AI modernization changed the game. It parsed millions of lines of COBOL code overnight, no need for an army of consultants. The agents smartly mapped out all the dependencies, flagged dead code, and even suggested Java replacements for our custom rules.

What changed: Tasks that took six months - like untangling batch processing - shrank to weeks. The team shifted focus. They built new customer features instead of chasing bugs in 1980s code.

Air Canada modernized their systems using AI-driven agents that work at a pace old tools can't match.

Thomson Reuters Slashes Tech Debt Fast

"Tech debt" has long strangled innovation at firms like Thomson Reuters (opens in new tab). Their .NET suite spanned decades. Thousands of linked modules. No dev wanted to touch them.

When they deployed AWS Transform across their apps, the backlog shrank fast.

Example: An ageing permissions module with hidden dependencies got refactored into cloud-native microservices. It took days - not months.

Thomson Reuters cut costs 30% and sped up transformation 4x (opens in new tab). They now process over 1.5 million lines monthly. Automated rewrites meant less firefighting and more feature shipping.

Data shows up to 40% of modernization projects stall due to manual cleanup. Autonomous agents tackle this complexity at scale.

How to Modernize with AWS Transform Agentic AI

Map Your Legacy Stack First

Modernizing starts with knowing what you have. Think of it like taking stock before renovating an old building. You need to see every corner.

Catalog your full-stack Windows assets. List every .NET app, SQL Server database, VMware image, and mainframe workload. Document how they connect.

Once mapped, AWS Transform's agentic AI can analyze what's ready for fast modernization versus what needs careful work. This isn't just a checklist. It's about finding tangled tech debt that slows releases and frustrates teams.

As LinkedIn highlights (opens in new tab), manual modernization eats up time and delays innovation.

Automate .NET and SQL Server Migration

Now that your stack is fully mapped out, the real transformation kicks off. This is where AWS Transform's agentic AI modernization really shines, especially for .NET apps and SQL Server databases.

This isn't lift-and-shift in disguise. It's smart replatforming at scale. The agent parses app logic. It rewrites code for cloud. It migrates data. It spins up automated tests - all without constant human watch.

Example: A financial firm used AWS Transform to modernize a 15-year-old full-stack Windows platform. Over two million lines of custom code. The AI flagged outdated libraries automatically. It suggested optimal replacements. This would have taken months by hand.

Thomson Reuters (opens in new tab) now modernizes 1.5 million lines monthly using these tools - cutting what used to take months into two-week sprints.

Set Up Continuous Upgrades

Migration isn't the finish line. It's the start of future agility. With AWS Transform in place, continuous improvement becomes built-in.

Set up automated monitoring from day one. Performance issues get flagged instantly. New security practices roll out without waiting for quarterly reviews. Compatibility problems get patched by the system itself.

These autonomous upgrades mean teams spend less time fighting old bugs. More time building features users actually want.

AWS Transform's agentic AI modernization doesn't just drag your legacy workloads into the future, it keeps evolving with you, so you're never left behind in the past.

Your Next Move

Legacy tech used to mean hard choices. Slow projects. Ballooning costs. Teams stuck fixing old code instead of building new products.

Agentic AI has changed that story. With AWS Transform, companies shift from firefighting to fast-forward. Old codebases get new life without draining your best people or your budget.

We've watched teams move from patching legacy apps to launching new products. Sometimes within weeks of starting their migration. That's the real win - freeing time and talent for what moves the business ahead.

If you're staring down an aging system or feeling boxed in by tech debt, try a different approach. Agentic AI can rewrite your modernization story. Upgrades happen at speed. You finally reclaim room to grow.

The bottom line? Don't let old code set your pace. Take control with tools built for transformation.

Explore more about how AI agents transform business workflows and boost productivity in our detailed guide on agentic AI (opens in new tab). Discover practical insights, real-world examples, and hands-on approaches to start harnessing the power of autonomous AI in your operations today. Read the full article here.

Ready to see what happens when legacy stops holding you back?

Let's explore how AWS Transform can accelerate your journey to modernizing agentic AI. Reach out (opens in new tab) to start planning your next chapter.