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When Every Second Counts: From Alerts to Answers with AI-Driven Operations
When mainframe issues strike, every minute matters—but traditional monitoring often leaves teams chasing alarms instead of solving problems.
In this industry insights session, guest speaker IDC Research Director Shannon Kalvar and BMC mainframe experts explore how AI-driven insight and enterprise observability are transforming operations: by giving teams more context—helping them identify meaningful alerts, analyze likely causes across systems, and act faster with guided assistance.
Learn how leading organizations are using AI to reduce MTTR, minimize SLA exposure, and build more confident, proactive operations teams—even as experienced staff become harder to find.
You’ll learn:
- How AI-driven insight enables earlier anomaly detection and faster probable cause analysis
- How contextual AI-driven alerting cuts through noise to highlight issues that matter
- Why enterprise observability is critical for proactive incident response
Strategies to reduce MTTR, minimize SLA exposure, and build operational resilience
Speakers
Shannon Kalvar, Research Director, IDC
Alan Warhurst, Director Product Management, BMC Software
Jeremy Hamilton, Director Technology Solutions, BMC Software
event summary
Why AI-driven operations are redefining incident response and IT resilience
As IT environments become increasingly complex and interconnected, traditional approaches to operations struggle to keep pace. Industry leaders discuss how AI-driven operations can help organizations reduce noise, accelerate decision-making, and preserve critical expertise in an evolving workforce landscape.
core insights
From alerts to decisions: Building smarter operational practices
Organizations are shifting their focus from simply detecting issues faster to understanding and resolving them more effectively.
1
Alert volume is outpacing human capacity
Modern IT environments generate massive volumes of alerts from a single incident, making it increasingly difficult for teams to identify the true source of a problem. Organizations need intelligent signal correlation and prioritization to reduce noise and focus on what matters most.
2
Operational knowledge is becoming a strategic asset
As experienced personnel retire, organizations risk losing the expertise that enables rapid diagnosis and informed decision-making. Capturing and sharing institutional knowledge is becoming essential to maintain operational resilience and continuity.
3
Decision intelligence is the next frontier
Reducing detection time is important, but organizations gain greater value when they accelerate understanding, context-building, and decision-making. AI can help connect signals, dependencies, and business impact to guide faster and more informed actions.
what this means
Turning insight into operational advantage
Organizations that reduce operational noise and improve decision-making can redirect valuable time toward modernization, innovation, and future readiness. Faster understanding leads to better outcomes, lower risk, and greater operational efficiency.
Key takeaways:
- Prioritize signal correlation to identify probable causes faster and reduce alert fatigue.
- Capture institutional knowledge to reduce dependence on individual expertise.
- Define clear decision frameworks that determine where automation can safely assist.
- Improve visibility across interconnected systems to strengthen operational awareness.
- Invest time saved through automation into modernization and future capacity planning.
“Observation is not orientation. Mean time to detect is an observation. Mean time to understand is an orientation.”
Shannon Kalvar, IDC