I have recently read an interesting study review of research conducted by IDC, and sponsored by Rocket Software, that shows that enterprises are allocating 25–30% of IT budgets toward mainframe modernization, with AI readiness and cybersecurity topping the priority list. It also claims that many organizations struggle to realize value due to cybersecurity risks, technical debt, data silos, and shortages of AI and cloud skills.

As product manager for mainframe modernization solutions, I think that this study underscores both challenge and opportunity. Mainframes remains critical to core operations, yet 26% of organizations specifically plan to modernize them to improve integration and workload optimization. I believe the key takeaway is that success will depend not only on migrating workloads to the cloud, but also on strategically extending mainframes into AI, hybrid cloud, and automation ecosystems while embedding security and resiliency. Enterprises that treat their mainframes as first-class citizens in modernization roadmaps will be better positioned to reduce technical debt, unlock data for AI, and bridge the skills gap through focused training.

When it comes to data, this highlights a long-standing issue: critical data is often trapped in mainframe systems, siloed from cloud platforms and modern analytics tools. Unlocking this data is not simply a technical exercise — it is the foundation for driving AI readiness, improving customer experience, and enabling real-time business insights. When mainframe data remains isolated, enterprises risk making decisions with incomplete or outdated information. By contrast, when mainframe data is liberated through APIs, replication pipelines, or event-driven architectures, it becomes fuel for AI models, digital services, and cross-enterprise innovation. The organizations that succeed will be those that stop treating the mainframe as a closed box and instead position it as a core data engine, seamlessly connected to the broader IT landscape.

Looking ahead, investing not only in technical upgrades but also in people — training teams to use new integration tools, building AI-ready pipelines, and ensuring cybersecurity should be designed into every modernization step. The opportunity is significant: mainframes already process mission-critical workloads at scale and with unmatched reliability. By extending these systems into hybrid and AI ecosystems, enterprises can achieve faster innovation and stronger resilience.