BMC, a provider of software solutions for business enablement, has made AI innovation updates across its Control-M and BMC AMI portfolios.
Advances for business-driven automation target issue resolution and workflow creation
The updates were made to simplify workflow creation, automate issue resolution, act on expert mainframe knowledge, and more.
“AI is rapidly democratizing access to complex workflows and also supports the continued advancement of the mainframes that power the world’s largest organizations,” said Ram Chakravarti, chief technology officer at BMC.
“We’re removing technical barriers by letting people describe what they need in plain language, taking the mystery out of automation, and closing the gap between a good idea and a working solution. Our AI innovations for the mainframe help our customers build a resilient and continuously advancing mainframe, and help them advance their digital transformations. All of the new AI innovations announced today leverage the power of AI to unlock value from data and drive business insights,” Chakravarti continued.
AI Workflow Creator
This new AI innovation operates as a Gen AI copilot for guided workflow design.
The Creator shifts automation ownership from IT to business practitioners, enabling organizations to capture domain expertise that can be poorly documented or lost in translation.
Business users just need to express their intent, and the Creator will craft a workflow that matches it.
It provides faster workflow creation and onboarding for new users and accelerates productivity for experts.
Expanded AI integrations with RPAs, apps, and more
BMC has also added additional integrations to its Control-M solution, which already includes out-of-the-box integrations spanning enterprise applications, databases, cloud services, RPA platforms, and collaboration tools.
New additions for the solution include AWS Bedrock, Google Vertex AI, and Crew AI. This will empower practitioners to orchestrate multiple AI agents for complex, AI-centric workflows. Through this orchestration with Control-M, teams can accelerate innovation and scale their AI initiatives.
Event-Driven Workflows
BMC also made updates to the Control-M Event-Driven Workflows. The capability already allows organizations to respond to business and data events in real time.
With the new updates, Control-M can now listen to events from systems such as Kafka, Amazon SQS, and RabbitMQ.
The update enables Control-M to automatically trigger or adjust workflows based on the signals it can now listen to.
This enables event-aware orchestration, improving agility and reducing latency across modern data and application pipelines.
According to BMC, the new capability bridges the gap between batch and real-time processing for instant responsiveness and operations – available for both Control-M self-hosted and SaaS environments.
Mainframe Expertise On-Demand
The Knowledge Expert Chat capability of BMC AMI Assistant can embed AI-driven guidance across nine BMC AMI development and operations solutions.
It is available to licensed customers of the development and operations solutions at no additional cost.
Informed by BMC documentation and domain knowledge, the capability delivers clear, natural-language answers to allow teams to resolve issues faster, reduce knowledge bottlenecks, improve system performance, and maintain service reliability without switching tools or relying on experts.
Updates to the Knowledge Hub Capability
The Knowledge Hub capability in BMC AMI Assistant complements the Knowledge Expert Chat capability to address growing skills and knowledge gaps.
It is currently available in managed beta to qualified customers and will enable organizations to surface scattered institutional knowledge for availability in AI-driven interactions. This helps close skills gaps, reduce dependency on individuals, enhance operational resilience, and support modernization decisions.
Consolidating DevOps Telemetry
BMC AMI zAdviser Development Team Analysis is a system that provides AI-powered application analysis to help development leaders make faster, more informed decisions.
In a new update, DevOps Telemetry will be consolidated, including activity metrics, productivity data, and failure patterns, creating a unified narrative report for each application.
This helps IT leaders identify stability risks, uncover knowledge concentration, prioritize improvements, and reduce operational exposure without fragmented dashboards.
“As organizations push to move faster while managing increasing complexity, we’re seeing growing demand for AI capabilities that embed intelligence directly into everyday workflows. Rather than standing apart as isolated tools, these AI-driven approaches help teams translate intent into action, contextualize systems behavior, and surface relevant expertise at the moment it’s needed,” says Steven Dickens, CEO and principal analyst of HyperFRAME Research.
“The result is faster decision-making, reduced friction across operations, and more resilient, business-aligned automation across the enterprise.”
Not long ago, Kyndryl and Google Cloud teamed up to modernize mainframes as demand increased. Learn more about the collaboration and how the companies are using Gen AI to streamline modernization.