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The 2026 BMC Mainframe Survey: What’s Next for the Mainframe
How AI is Shaping the Next Era of Mainframe Transformation
Join BMC experts as they reveal new findings from the 2026 BMC Mainframe Survey and explore how organizations are moving from AI experimentation to real-world adoption built on trust, governance, and measurable business outcomes.
Learn why confidence and investment in the mainframe remain at near-record levels, how AI is transforming operations, development, and modernization initiatives, and what mainframe leaders are doing to strengthen cyber resilience, security, and data readiness as they prepare for what’s next.
Key Takeaways:
- Discover the latest trends shaping mainframe growth, investment, and AI adoption.
- Learn where organizations are achieving measurable value from AI, AIOps, and agentic AI—and where they’re headed next.
- Understand the security, governance, and data strategies organizations need to build trust and scale AI.
Speakers
Priya Doty, Vice President of Solutions Marketing, BMC Software Inc
Alan Warhurst, Director, Product Management, BMC Software Inc
event summary
How AI, trust, and modernization are reshaping the future of enterprise mainframes
As AI moves from experimentation to operational reality, enterprises are rethinking how mission-critical platforms drive growth, resilience, and innovation. Industry leaders share how trust, governance, and workforce transformation are shaping the next phase of mainframe strategy.
core insights
From platform stability to intelligent transformation
Organizations are no longer focused on whether the mainframe has a future. The focus has shifted to how AI and modernization can expand its business value.
1
Mainframe investment continues despite AI disruption
Organizations increasingly view the mainframe as a strategic business platform rather than a legacy system. Continued workload growth, expanding data volumes, and ongoing investment demonstrate its role in supporting critical enterprise operations.
2
Trust is becoming the foundation of AI adoption
Interest in AI is accelerating, but organizations are prioritizing recommendations and guided decision-making over fully autonomous actions. Governance, security, and risk management are emerging as prerequisites for broader AI deployment.
3
Expertise is shifting from knowledge retention to knowledge scaling
As experienced talent retires and environments become more complex, organizations are looking to AI to capture institutional knowledge, support developers, and accelerate operational decision-making. The goal is not replacing experts, but extending their impact.
what this means
Turning AI potential into measurable business outcomes
AI adoption is increasingly tied to operational performance, resilience, and modernization goals. Organizations that combine governance with practical use cases are positioning themselves to move faster while reducing risk.
Key takeaways:
- Prioritize business outcomes before selecting AI technologies.
- Establish governance frameworks that balance innovation with security and compliance.
- Capture institutional knowledge and make it accessible through AI-enabled workflows.
- Expand automation across operations, testing, and modernization initiatives.
- Build trust incrementally by progressing from AI assistance to recommendations and governed autonomous actions.
“I wanna do this, but I wanna do this in safe, manageable way for sure.”
Alan Warhurst, BMC Software
Turn AI ambition into a practical plan
The BMC AI Readiness Discovery Workshop helps enterprise teams assess readiness across data, workflows, and governance, and define a clear path to scalable AI adoption.