AI, Governance, and the Modern Mainframe: Key Insights from IBM’s CIO Roundtable
As AI reshapes enterprise IT, the conversation is no longer about if businesses should modernize—but how to do it responsibly and effectively. That was the central theme from a recent CIO Magazine roundtable, hosted by IBM’s Skyla Loomis, VP of IBM Z Software, and John Currie, Partner for Mainframe Application Modernization. Executives from industries including finance, insurance, and education came together to explore how AI is accelerating IT transformation—especially in the context of governance, mainframes, and hybrid architectures.
AI Governance: From Possibility to Urgency
A year ago, AI was a buzzword. Today, it’s a boardroom priority—and governance is now at the heart of the conversation.
“Governance is now at the forefront of AI conversations,” said Loomis. “The priority is ensuring AI models remain explainable, auditable, and secure.”
Executives emphasized that with AI moving into production environments, compliance and risk management can’t be afterthoughts. That’s especially true in regulated industries like financial services and healthcare. AI governance frameworks—covering transparency, oversight, risk mitigation, and ethical deployment—are now essential for responsible innovation.
A recurring theme was data control. With growing concerns over data sovereignty, many organizations prefer to deploy AI on-premises rather than in the public cloud. This approach keeps proprietary information behind their firewall and aligns more closely with compliance mandates.
AI Is Modernizing—Not Replacing—Mainframes
Mainframes aren’t going anywhere. In fact, they’re getting smarter.
“Modernization and migration are not the same thing,” said Currie. “Enterprises are realizing that a hybrid, fit-for-purpose approach provides better outcomes.”
AI is playing a central role in this evolution. From analyzing legacy code dependencies to automating refactoring, AI tools are helping enterprises unlock insights from legacy systems and improve interoperability with modern platforms. Rather than rip-and-replace, organizations are taking an incremental path—extending the life and value of their mainframes while integrating them with cloud-native applications.
“We’ve seen AI help organizations uncover hidden efficiencies in their mainframe ecosystems,” Currie said.
Rethinking “Build vs. Buy” in the AI Era
Another major theme: AI is shifting the balance between building and buying software.
With generative AI accelerating code generation, testing, and deployment, more organizations are reconsidering third-party SaaS tools in favor of fast, in-house development. One insurance executive noted their team built an AI-powered underwriting triage tool in just two weeks—what used to take months.
Still, the consensus was that AI is a force multiplier, not a developer replacement. AI-generated code still requires human oversight for validation, security, and long-term maintainability.
“AI is making it easier for companies to build—but governance, accuracy, and alignment still matter,” Loomis noted.
Hybrid IT Is the New Normal
Far from declaring the death of the mainframe, roundtable participants confirmed that hybrid strategies—combining cloud, AI, and mainframe—offer the most pragmatic path forward.
“We’re seeing enterprises take a pragmatic approach,” said Currie. “They recognize the value of mainframes but are investing in modern API-driven architectures.”
Mainframes continue to power mission-critical workloads in banking, insurance, and government, prized for their security and reliability. But the future lies in integration, not isolation. The new playbook is about APIs, automation, and cloud-native design working with core systems—not around them.
AI in Practice: Start Small, Scale Smart
Finally, participants emphasized the need to treat AI adoption as a strategic, iterative journey—not a sprint.
Companies are deploying AI sandboxes to test new use cases and validate governance policies before scaling. This experimental mindset allows them to learn, adapt, and stay compliant without sacrificing speed.
“We’re in an era where companies need to balance rapid innovation with responsible AI governance,” said Loomis.
Currie added: “AI, cloud, and mainframe modernization should all be part of a unified digital strategy that evolves with the business.”
TL;DR – 5 Key Takeaways from the IBM Roundtable
- AI governance is now table stakes. It’s about compliance, transparency, and ethical deployment—not just innovation.
- Mainframes are here to stay—but smarter. AI is modernizing, not replacing, core systems.
- Build vs. buy is back on the table. AI accelerates internal development, challenging SaaS norms.
- Hybrid IT wins. The best strategies mix cloud, AI, and mainframe into one cohesive architecture.
- Experimentation is essential. Sandboxes, small pilots, and agile teams lead to responsible scale.
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