What if the systems your business can’t live without are also the ones holding you back? Mainframes remain the backbone of critical operations in banking, insurance, healthcare, and government. Their reliability is unmatched, but so is their complexity. With aging infrastructure, limited documentation, and a shrinking pool of skilled professionals, many organizations are struggling to evolve without risking operational stability.
At McLaren Strategic Solutions (MSS), we believe modernization isn’t about ripping and replacing; it’s about reimagining what’s possible. In 2025, Artificial Intelligence (AI) isn’t just another tool. It’s a translator, accelerator, and enabler, helping organizations extract value from legacy systems while preparing for the digital future.
This blog explores how MSS leverages AI to modernize mainframes, with real-world results, enterprise-grade strategies, and sustainable transformation.
There has never been a more critical time to modernize. Enterprises face multiple headwinds: a retiring workforce with deep but undocumented knowledge of legacy systems, increasingly stringent compliance mandates, and an accelerating pace of digital transformation.
Traditional modernization methods, manual documentation, line-by-line code refactoring, and staged cloud migration are often too slow and expensive.
MSS harnesses AI to shift this paradigm. Through intelligent automation, large language models (LLMs), and graph-based analysis, AI now deciphers legacy code, extracts embedded business rules, simulates outcomes, and proposes modern equivalents—all faster, safer, and more cost-effectively than ever before.
A. Automated Code Comprehension and Rule Extraction
Legacy systems written in COBOL or PL/I often lack proper documentation. AI-powered tools, like IBM’s Application Discovery and Delivery Intelligence (ADDI), can now map logic, dependencies, and data flows across millions of lines of code in a matter of days.
At MSS, we integrate these capabilities into modernization assessments to accelerate discovery and reduce risk from the very beginning.
B. Intelligent Code Transformation
Unlike static translators, AI understands the business logic behind legacy code, enabling cleaner, modular, and future-ready systems. MSS validates AI-generated outputs through human-in-the-loop reviews to ensure compliance, security, and accuracy.
C. Smart Test Case Generation and Synthetic Data
Testing is often the bottleneck. AI can auto-generate test cases from historic logs or inferred execution paths. It also creates synthetic data that mimics real production datasets, crucial for industries like BFSI, where privacy and compliance are paramount.
MSS embeds these capabilities into its delivery pipelines to ensure faster, safer testing cycles.
D. Real-Time Anomaly Detection and Observability
Modernized mainframes still require vigilance. MSS deploys AI-infused observability tools to detect:
This enables real-time responses in financial, healthcare, and regulatory environments.
E. DevOps Automation and Continuous Modernization
AI accelerates DevOps by generating CI/CD pipelines, automating Zowe CLI tasks, and integrating with Jenkins workflows.
At MSS, we champion Continuous Modernization—an approach where AI-driven enhancements happen incrementally, without the need for massive re-platforming.
The impact of AI in mainframe modernization is already visible across MSS’s client base. Key outcomes include:
According to industry reports, 86% of enterprises are now piloting or scaling AI-powered modernization, including risk-averse sectors like healthcare and financial services.
MSS plays a key role in this transformation by combining deep domain expertise, secure AI adoption frameworks, and end-to-end modernization programs.
The future isn’t about abandoning mainframes—it’s about enhancing them with intelligence. Newer systems like the IBM z16/z17 feature on-chip AI acceleration (e.g., Telum processors), enabling inferencing to run directly on the mainframe for:
MSS helps organizations design hybrid modernization architectures, where business-critical processing remains on mainframes, while AI-driven analytics, orchestration, and experience layers live in the cloud, offering the best of both worlds.
1. Begin with AI-Led Discovery: Use AI tools to assess legacy portfolios and prioritize transformation candidates.
2. Adopt an Augmented Team Model: Blend MSS’s legacy expertise with AI automation to scale safely and smartly.
3. Embed Governance and Compliance: Ensure every AI-generated artifact is transparent, auditable, and explainable.
4. Think Continuous: Move away from big-bang re-platforming. Let AI power ongoing transformation and deployment.
5. Measure Impact: Track metrics like code maintainability, test coverage, defect density, and ROI from day one.
Modernizing mainframes with AI isn’t just a technical upgrade; it’s a strategic shift in how enterprises manage risk, agility, and innovation.
AI helps organizations shift from reactive maintenance to proactive transformation, where systems grow smarter, testing becomes automated, and innovation happens continuously. For enterprises managing legacy sprawl and regulatory complexity, this evolution is no longer optional—it’s essential.
At McLaren Strategic Solutions, we embed AI not as a shortcut but as a strategic enabler of long-term resilience, agility, and value creation.
Enabler of long-term resilience and value creation.
Ready to modernize smarter, not harder? Connect with our experts to explore AI-powered strategies that modernize without compromise.
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