For decades, COBOL applications have been the backbone of mission-critical systems in banking, insurance, government, and retail. These systems – often running on mainframes – have proven their reliability and scalability, processing millions of transactions daily with near-perfect uptime. Yet, as digital transformation accelerates, the limitations of these legacy platforms – rigid architectures, outdated interfaces, and dwindling talent pools – are becoming increasingly apparent.
Throughout my career, I have partnered with numerous clients on their cloud modernization journeys. Historically, these efforts were hindered by limited visibility into legacy business rules, mounting technical debt, and the high cost and complexity of modernization initiatives. Today, generative AI is reshaping the landscape by removing these barriers and enabling us to reimagine legacy systems, accelerate the shift to cloud-native platforms, and unlock agility, innovation, and cost efficiency at unprecedented speed.
The challenge of modernizing COBOL
Modernizing COBOL is not just a technical endeavor – it’s a strategic imperative. But it’s also notoriously difficult. COBOL systems are monolithic, deeply integrated, and often poorly documented. They rely on legacy transaction monitors like CICS and IMS, batch job orchestration via JCL, and data stored in formats like VSAM and EBCDIC. The user interfaces – 3270 green screens – are unintuitive and incompatible with modern digital experiences.
The technical debt accumulated over decades makes these systems fragile. Business logic is buried in millions of lines of procedural code, often referred to as “mystery code.” Integration points are tightly coupled to outdated protocols, and data migration is a minefield of encoding conversions and schema mismatches. Add to that a shrinking pool of COBOL-literate engineers, and it’s no wonder many organizations hesitate to modernize.
But hesitation comes at a cost. The longer these systems remain untouched, the greater the risk of operational disruption, the greater the missed business opportunities for innovation.
AI-powered legacy transformation: A new approach
Enter generative AI. We’re now pioneering a transformation methodology that combines AWS’s Transform capabilities with Pega Blueprint™ to reimagine legacy applications as modern, low-code solutions.
Here’s how it works:
Step 1: Define success
We begin by working with clients to frame the client’s scope and transformation objectives. Success criteria are established, baseline metrics are captured, and a roadmap is created. This sets the stage for a focused, outcome-driven modernization journey.
Step 2: Analyze legacy code with AWS Transform
Using AWS Transform and tools like AWS Q Developer, we extract execution flows, data structures, and semantic rules from COBOL, .NET, Java, and other legacy languages. This AI-enabled analysis helps us understand the business logic embedded in the legacy code – without relying solely on scarce human expertise.
Step 3: Generate Pega Blueprints with GenAI
Once the legacy code is analyzed, we ingest the extracted assets into Pega Blueprint. This tool reimagines the application as a business workflow, complete with:
- Core business rules: Verified and visualized for clarity.
- External data exchange: Mock REST APIs simulate real-world integrations.
- Data models: Synthetic data stored locally in Pega’s system of record.
- Scaffolded applications: Interactive screens and workflows that are AI generated based on insights from the legacy application.
This approach allows clients to “touch and feel” the future state of their application within weeks. It’s not just a proof of concept, it’s a working prototype that validates business rules, user interactions, and data mappings.
Step 4: Validate, verify, prioritize
We load synthetic data, run validations, and conduct business functional verification to ensure the new application mirrors the legacy system’s behavior. This iterative process builds confidence and allows for refinement before full-scale implementation.
Why this matters
The combination of AWS and Pega offers a powerful foundation for legacy application modernization:
- Accelerated design & discovery: Achieve transformation in as little as six weeks, enabling faster delivery and reducing time to value.
- Intuitive, modern UX: Delight customers and employees with intuitive workflows and responsive interfaces that reduce friction and boost engagement.
- Lower TCO: Cut operational costs by minimizing dependency on niche skills and leveraging a scalable, cloud-native architecture that grows with your business.
This isn’t just about replacing old systems; it’s about unlocking innovation. With Pega’s low-code platform and cloud-native capabilities, organizations can scale faster, tap into larger talent pools, and focus on delivering differentiated customer experiences.
We dove deeper into this transformation journey during our Fireside Chat on Mainframe Modernization during the AWS Innovate: Migrate and Modernize virtual event. The replay is available on demand.
Ready to explore how AI is reshaping legacy systems and empowering organizations to build future-ready applications?
Pega is a bronze level sponsor at AWS re:Invent. I’ll be available for meetings, and at our booth, so be sure to come see the Pega team.
There’s also several Lightning Talks at AWS re:Invent that I’d recommend attending:
- Matt Healy and I are speaking on AI driven application modernization at scale, be sure to join our session on Tuesday, 12/2 from 4:30 – 4:50 PM PT at the Global Impact Pavilion.
- Don Schuerman is speaking on Predictable AI Agents with Pega and Amazon Bedrock on Wednesday, 12/3 from 4:30 – 4:50 PM PT at the Global Impact Pavilion.
- Customize your mainframe modernization with composable AI featuring Unum on Wednesday 12/3 at 1:30 PM at Caesar's Palace, Las Vegas.