Mainframe Modernization Market

A key factor driving mainframe modernization is the rapid retirement of experienced professionals, which creates a critical skills gap and elevates operational risks. Many organizations in banking, insurance, and government have depended on the “institutional knowledge” of senior developers for decades; as these experts near retirement age, over 60% are now above 50, and much of the essential knowledge to maintain and modify mainframe applications leaves with them. This makes modernization not just advantageous but essential, since new hires often lack deep expertise in COBOL, JCL, or assembler. For instance, Legal & General, a leading UK financial services firm, prioritized retaining and transferring developer and tester knowledge before initiating their mainframe overhaul, supporting their workforce with new tools and gradual modernization rather than sudden changes. Companies like IBM are tackling this issue by incorporating AI and automation into their modernization tools to close the skills gap, while Ensono has highlighted the rise in mainframe retirements and the increasing costs and challenges of recruiting or training new mainframe talent.

One of the biggest challenges in mainframe modernization is the complex task of migrating legacy codebases, which often consist of millions of lines of undocumented code and tightly coupled business logic. Legacy applications, developed over decades using COBOL, PL/I, or assembler, usually lack up-to-date documentation, making it hard to understand dependencies and avoid breaking essential processes. This often turns many mainframe environments into “black boxes,” hindering innovation and creating resistance to changes. For example, organizations like European banks face multi-year timelines for modernization because their applications support core payment and compliance systems that cannot afford downtime. To address this, companies like Royal Cyber and Micro Focus use static code analysis tools and smart parsers to map dependencies and find reusable code segments before starting any transformation. Nonetheless, the risk of data loss and business disruption remains high unless the migration is carefully planned and executed, leading organizations to adopt hybrid or phased modernization strategies supported by both automation and expert guidance.

A major opportunity in mainframe modernization is the swift growth of adoption among small and mid-sized businesses (SMEs), driven by modular, consumption-based, and cloud-native modernization solutions. Traditionally, SMEs faced challenges with high costs, limited resources, and risks tied to mainframe upgrades. However, companies like AWS and Astadia now provide AI-driven code refactoring and “starter” modernization packages, allowing SMEs to upgrade specific applications gradually, often beginning with less critical workloads. Additionally, the increased availability of automation and managed migration services enables smaller firms to overcome the industry-wide legacy skills shortage, opening new opportunities for digital agility and competitiveness.

Ensuring continuous business operations during mainframe modernization remains a key challenge, especially for organizations with 24/7 operational needs like those in banking, utilities, and government. Even short outages can lead to significant financial losses, reputational damage, and regulatory fines. Legal & General addressed this by actively involving their developers and ensuring strong support during the upgrade, keeping policyholder services stable for their 5.5 million pension customers throughout the process. Technology companies such as CGI and IBM emphasize the importance of phased rollouts, dual-run (blue/green) deployments, and automated testing to reduce risks during migration. Other effective practices include thorough regression testing, sandbox environments, and monitoring tools for real-time anomaly detection, all helping companies modernize critical workloads while maintaining normal operations. By focusing on business continuity with these techniques, organizations can innovate without sacrificing reliability or regulatory compliance.