This comprehensive guide, geared for tech managers and architects, explores how artificial intelligence can transform the landscape of legacy application modernization, with a special focus on mainframe COBOL systems. It bridges the knowledge gap between traditional mainframe expertise and modern development practices, providing practical strategies for organizations facing the “COBOL cliff” - the convergence of aging systems, billions of lines of critical COBOL code, and a rapidly retiring generation of COBOL experts. From fundamental COBOL concepts to cutting-edge AI-assisted migration tools, this book offers a complete roadmap for IT professionals navigating the complex journey of legacy modernization while preserving decades of embedded business knowledge.
Legacy systems, particularly those running on mainframes and written in COBOL, continue to power critical operations across banking, insurance, government, and many other sectors - processing approximately 70% of global banking transactions and remaining essential to 45 of the top 50 banks, 4 of the top 5 airlines, and 67 of the Fortune 100 companies. Yet organizations face mounting challenges: diminishing expertise (with the average COBOL programmer around age 60), increasing maintenance costs (technical debt averaging $361,000 per 100,000 lines of code), and limited agility.
This book presents a systematic approach to understanding, documenting, and transforming these legacy applications using artificial intelligence as a strategic enabler. It demonstrates how AI can accelerate the extraction of business rules, support code conversion, enable automated testing, and facilitate knowledge transfer. Through case studies, technical deep dives, and practical tutorials, readers will gain both theoretical knowledge and hands-on experience with tools and methodologies that make modernization more efficient, less risky, and increasingly automated.
Chapter 1: The COBOL Cliff: Understanding the Legacy Imperative
Chapter 2: Deconstructing COBOL: A Foundation for Modernization
Chapter 3: Architectural Assessment: Mapping the Legacy Landscape
Chapter 4: Strategic Modernization Options: A Decision Framework
Chapter 5: AI-Powered Modernization: Transforming Legacy Systems with Intelligence
Chapter 6: Translating COBOL to Modern Languages: Architectural Considerations
Chapter 7: Cloud Integration and Platform Selection: An Architectural Perspective
Chapter 8: API-Enabling Legacy Systems: Encapsulation and Integration