Mainframe Blog

Mainframe Transformation with AIOps: Smarter Operations, Greater ROI

4 minute read
Matt DeLaere, Nick Mears

Organizations that rely on legacy mainframe monitoring tools often face costly inefficiencies, including SLA violations, regulatory compliance risks, and application slowdowns. These hidden costs can increase capital expenditure and operational inefficiencies—even impact overall business resilience. Luckily, there are alternatives to reduce, if not eliminate, that are based on AIOps practices. As artificial intelligence (AI) and generative AI (GenAI) mature, organizations can integrate AI with monitoring and observability tools for a new level of system visibility.

Addressing the role GenAI can play in optimizing mainframe operations, John McKenny, BMC Senior Vice President and General Manager of Intelligent Z Optimization and Transformation, says, “GenAI is revolutionizing mainframe AIOps by transforming reactive operations into proactive, data-driven systems. Organizations embracing these technologies gain enhanced insights, minimized risks, and optimized costs.”

In a recent webinar, “7 Hidden Costs of Ignoring AIOps,” BMC’s Mark Banwell, Alan Warhurst, and Jeremy Hamilton explored these challenges, sharing insights on how AIOps with GenAI capabilities and advanced automation can transform mainframe operations.

One of the topics covered in this webinar focused on the not-so-insignificant hurdles organizations face with legacy mainframe monitoring tools. This includes visibility gaps, which make it difficult for teams to detect issues before they escalate. Legacy monitoring also comes with manual processes and siloed tools that create bottlenecks in operational workflows. As a result, IT teams are forced to put out fires rather than proactively manage performance. Without actionable insights, the consequences can be severe, leading to unexpected downtime and higher costs.

The solution: Leveraging GenAI and AIOps for smarter operations

BMC AMI Ops solutions leverage advanced AI capabilities to improve monitoring, reduce inefficiencies, and eliminate legacy constraints. This empowers organizations to detect issues proactively for improved MTTD (mean time to detect) and kick off resolution processes, helping IT teams significantly cut mean time to repair (MTTR). End result, teams ensure consistent system performance and minimize downtime. Also, the ability to integrate predictive analytics with automated compliance monitoring leads to enhanced regulatory adherence and reduces the risk of costly SLA breaches.

During a recent podcast, The Game-Changing Benefits of AIOps for Modern Mainframe Operations,” Hamilton likened this AI-powered automation to the five senses in the human body. “The machine learning portion is seeing, hearing, and sensing what’s going on in the environment, while the GenAI component takes it further—analyzing, interpreting, and enabling seamless communication between users and systems. That’s where you get to the hybrid aspect—bringing all of these capabilities together for a more intelligent, automated, and predictive mainframe operation.”

So just like the five senses acting together, combining the power of AI for a more holistic view of system operations—and automating issues before they impact availability—can help reduce costs and enable organizations to provide services, combined with a user experience, that can meet or even exceed customer expectations.

The real-world impact: ROI and operational benefits

Also during the webinar, Warhurst shared his perspective on how AIOps is reshaping mainframe operations: “Organizations often struggle with fragmented monitoring solutions that provide data but not insights. AIOps changes this by offering a holistic approach that not only identifies issues but also predicts and prevents them before they escalate, reducing unplanned downtime and improving overall performance.”

One important note, the financial impact of adopting BMC AMI Ops solutions can be substantial. A recent Forrester Total Economic Impact™ study, commissioned by BMC, showed that the composite organization created for the study (based on interviews with four BMC AMI Ops Monitoring customers) experienced significant benefits after implementing AIOps-powered monitoring and automation. This includes a 50 percent reduction in downtime, leading to improved service availability and enhanced customer satisfaction. Also, by replacing outdated legacy monitoring tools, the organization reduced operational expenses by up to 80 percent. This resulted in millions in savings over three years. Plus, when factoring in labor cost savings as teams reallocated IT staff to higher-value tasks, this resulted in an estimated $493,000 in savings.

Overall, the financial gains resulted in a 130 percent ROI, with a net present value of $2.94 million.

This is why organizations are increasingly looking to BMC AMI Ops Monitoring to minimize performance bottlenecks, increase operational efficiency, and ensure service continuity.

Industry-Leading root cause analysis with GenAI-guided issue resolution

BMC AMI Ops Insight provides best-in-class automated root cause analysis enhanced by the GenAI-driven BMC AMI Assistant, delivering real-time diagnostics, plain-language explanations, and recommended next steps. By automatically detecting, diagnosing, and suggesting resolutions, it accelerates Mean-Time-to-Detect (MTTD) and Mean-Time-to-Resolve (MTTR), reducing downtime and improving service reliability. Unlike traditional tools, BMC AMI Ops Insight doesn’t just surface alerts—it guides sysprogs and IT operations teams through issue resolution, making expertise more accessible at all skill levels.

With BMC AMI Ops, teams can combine built-in intelligence with AI-powered analytics to optimize performance, enhance system reliability, and proactively manage with actionable insights. Organizations leveraging BMC AMI Ops see a dramatic improvement in overall operational efficiency, with a reduced need for manual intervention and better risk management. When moving from a reactive posture to proactive management with BMC AMI Ops Insight, anomalies can be found and addressed before they escalate into SLA-impacting issues.

What’s next? Applying AIOps to drive real-world results

As discussed in the webinar, transforming mainframe operations with AIOps and GenAI isn’t just about reducing costs—it’s about creating a more efficient, resilient, and future-ready mainframe. We invite you to explore how employing AIOps can address your greatest pains, replacing them with intelligent automation, AI-powered, GenAI-capable, and streamlined operations, and how BMC AMI Ops solutions can help. Let’s continue the conversation and drive innovation together.

For more information on how AIOps can help your organization, watch the on-demand webinar, “7 Hidden Costs of Ignoring AIOps.” We also invite you to listen to our in-depth podcast, The Game-Changing Benefits of AIOps for Modern Mainframe Operations,” which expands on these themes and provides additional real-world perspectives.

AI-Driven Strategies for Mainframe Operations

How can emerging AI solutions help improve the monitoring and availability of your mainframe systems? Join this webinar, to learn how predictive AI, automation, and high-availability strategies are helping to reimagine mainframe operations, including examples of real-world applications.


These postings are my own and do not necessarily represent BMC's position, strategies, or opinion.

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About the author

Matt DeLaere

Matt DeLaere serves as a Solution Marketing Manager for BMC, where he is responsible for generating an array of mainframe-related content. He is a graduate of Hillsdale College with a B.A. in American Studies.

About the author

Nick Mears

Nick Mears (new author) As Principal Solutions Marketing Manager at BMC Software, Nick leads global solutions marketing initiatives within BMC Software's AMI team for AI-driven and DevOps-focused data management and mainframe-centric SaaS and on-prem applications. In this role, Nick helps data management and software development organizations that feature AI, ML, and intelligent automation capabilities increase the efficiency, availability, stability, and release velocity of enterprise-grade data management and DevOps applications. Nick has over 15 years of experience supporting technology companies and enterprise-grade software with customer-oriented value.