When a critical system fails in the middle of the night, every minute of downtime can cost thousands, sometimes millions. And despite massive investments in observability and automation, teams still waste precious time hunting for answers that already exist, buried in documentation, scattered across knowledge bases, or locked in the minds of experienced professionals.
The solution isn’t more tools. It’s smarter ones. This quarter, BMC is delivering solutions that place AI, observability, and automation where your teams already operate. This unified approach fundamentally transforms how teams resolve issues and manage complexity.
Unified visibility across hybrid environments
From a business perspective, the distinction between mainframe and distributed systems is irrelevant. Customers experience services, not infrastructure. Yet operationally, these environments remain siloed, each with its own tooling and metrics.
When a mainframe transaction spike at 2 AM correlates with a microservice timeout, that connection should be immediately visible. Instead, teams waste critical minutes context-switching between separate dashboards, manually reconstructing relationships that should be automatic.
True observability requires breaking down artificial platform boundaries. BMC AMI Ops addresses this through observability support with OpenTelemetry integration, streaming z/OS metrics directly into platforms like Elastic, Splunk, Grafana, and Datadog. A mainframe spike and microservice regression now appear together in a unified view, with AI automatically correlating the relationship.
Figure 1: Observability support for BMC AMI Ops
Specialized mainframe systems remain essential while now sharing the same operational visibility as distributed systems—enabling faster incident resolution and more informed decision-making across hybrid environments.
Bridging the mainframe knowledge gap
A 55-year-old COBOL developer retires, taking 30 years of institutional knowledge with her—business rules that exist nowhere else, not in documentation, not in code comments. Her replacement is 28, prefers cloud technologies, and faces a codebase with logic buried across millions of lines written before he was born.
This scenario repeats across enterprises daily. Critical business rules are embedded in decades of mainframe code, while mainframe expertise disappears as experienced professionals retire and younger engineers gravitate toward cloud technologies. The resulting knowledge gap makes even incremental modernization difficult.
BMC addresses this through GenAI capabilities across the BMC AMI portfolio, with two critical additions this quarter:
For selective modernization: BMC AMI Assistant in BMC AMI DevX Code Insights delivers GenAI-assisted COBOL-to-Java conversion. This isn’t automatic conversion—it’s guided transformation that lets developers choose the best language for each job, then selectively extract and convert COBOL code into modular, well-designed Java. Teams focus effort where it creates the most value, resulting in safer, faster modernization.
For knowledge transfer: The knowledge expert capability embedded in BMC AMI Ops and BMC AMI zAdviser Enterprise On-Prem provides conversational, contextual guidance directly in the workflow. Veteran expertise becomes accessible to the entire team, closing skills gaps without depending on scarce talent.
Figure 2: COBOL-to-Java conversion
This aligns with broader industry movement. Our 2025 State of the Mainframe Survey found 37% of respondents now trust AI to recommend diagnostic actions, with 32% willing to let AI execute those recommendations—a shift from AI as advisor to AI as operator.
Operational insights in the flow of work
Business workflows span multiple systems, environments, and teams. When an operator needs to know “Which workloads failed in the past 24 hours?”, they check dashboards, read logs, cross-reference documentation—turning a 30-second question into a 10-minute investigation. Multiply this across hundreds of daily queries and the cognitive overhead compounds.
Too many AI solutions add complexity rather than reducing it. Real progress comes from “assisted operations”: AI that augments human expertise rather than replacing it, with intelligence embedded directly where work already happens.
Jett, our GenAI-powered advisor in Control-M SaaS, exemplifies this principle. Ask “Which workloads failed in the past 24 hours?” and receive answers grounded in actual logs, metrics, and run history—factual analysis delivered in the moment of need.
Jett’s expanded capabilities now answer, “How do I…?” questions using product documentation, maintain a prompt gallery for common scenarios, and learn from favorite queries. Knowledge that once required searching through manuals becomes immediately available.
Figure 3: Reduce mean time to resolution with the AI Assistant for Control-M SaaS
Self-service at enterprise scale
Raymond James orchestrates 700+ business applications with 700 self-service users—reducing support requests by 60% and compressing multi-week audits to a single day.
“Control-M is really about collaboration. We now have close to 700 users across the enterprise interacting with Control-M, logging in and actively looking at their applications’ status. This includes business users, developers, data teams, and more. That’s been incredibly beneficial to our story, our growth, our maturation, and the whole continuous improvement process.”
— Chris Haynes, Associate Director of IT Operations Services, Raymond James Financial
Assisted operations enable self-service while orchestration maintains compliance and scale.
Combined with modernized UI and broader cloud-platform support, Control-M continues expanding. As a new Databricks partner, Control-M delivers expanded integration capabilities across the modern data stack. Other new integrations include Control-M for SAP BTP, Azure DevOps, Informatica Cloud Services, and many more. New and enhanced integrations release monthly, ensuring Control-M orchestrates workflows wherever business operates.
Proactive data validation at scale
Bad data corrupts analytics, fails compliance checks, and undermines automated decisions. When quality issues aren’t detected early, they ripple through entire ecosystems. By the time a fraud detection model discovers flawed training data, every downstream prediction has inherited that error.
Traditional validation approaches fail at modern scale because they operate post-processing. For batch reporting, discovering issues hours later worked. For real-time decisioning—fraud detection, dynamic pricing, personalized recommendations—reactive validation is useless.
The solution requires embedding validation directly into workflows. Control-M Data Assurance, a new service for Control-M self-hosted environments, validates data at each pipeline stage. Failed checks halt execution and trigger alerts before bad data reaches downstream consumers.
Figure 4: Validate data flowing through pipelines with Control-M Data Assurance
This shifts organizations from reactive detection to proactive prevention—catching errors at the source rather than discovering corrupted records after they’ve affected 15 dependent systems. Data pipelines run reliably and deliver trusted results.
Building resilient operations for the next decade
The path forward isn’t about choosing between legacy and modernization—it’s about making heterogeneous systems work together intelligently. These releases advance that vision through three core principles:
- Operational intelligence that spans platforms seamlessly – Breaking down artificial barriers between mainframe and distributed systems
- AI assistance embedded in existing workflows – Intelligence where work already happens, not in separate tools
- First-class observability and automation for all systems – Modern capabilities regardless of architecture or age
These aren’t aspirational goals. They’re practical requirements for organizations running business-critical services across hybrid environments. Each capability reduces operational risk while accelerating innovation—especially when minutes matter most.
Learn more about how these innovations can transform your operations:
