Agentic Mainframe

Connect trusted mainframe intelligence with agentic AI. Bring specialized expertise, live context, and AI agents together with governed access to mainframe capabilities, helping teams investigate complex problems, make informed decisions, and advance work while maintaining human control.

What is an agentic mainframe?

An agentic mainframe is a mainframe environment where AI agents use specialized expertise, relevant system context, and permitted capabilities to perform defined tasks within established governance and human oversight. Agents can investigate conditions, analyze evidence, recommend next steps, coordinate work, and take or support action within defined boundaries. Generative AI creates or explains content. Agentic AI can build on those capabilities to pursue a defined goal using relevant context, reasoning, and permitted tools, with human oversight appropriate to the task.

From AI assistance to agentic work

AI is transforming the mainframe by moving beyond assistance toward AI that can help advance defined work. Generative AI can explain code, summarize information, and answer questions. Agentic AI extends that model by applying specialized expertise and context to tasks that may require investigation, analysis, recommendations, coordination, and governed interaction with mainframe capabilities.

Understand → Investigate → Recommend → Act within defined boundaries

Not every AI experience needs to reach the final stage. The level of agentic behavior depends on the task, available capabilities, permissions, and required human oversight.

agentic mainframe

What makes a mainframe agentic?

An agentic mainframe connects intelligence with the context, capabilities, and controls required to perform defined work.

Specialized expertise

Apply mainframe product, domain, and organizational knowledge to specific tasks.

Task-relevant context

Ground AI in the operational, application, and data context needed for the task.

AI agents and skills

Use specialized agents and reusable expertise to investigate and advance defined work.

Connected capabilities

Give AI agents governed access to the tools, resources, and capabilities required for a task.

Coordination

Discover, connect, route, and coordinate specialized agents and capabilities when a workflow requires it.

Governance and human authority

Define identity, permissions, policies, approvals, observability, and intervention boundaries around agentic work.

Where does agentic AI apply on the mainframe?

The agentic mainframe spans AI-assisted and agentic workflows across application development, operations, and data management, while connecting trusted mainframe data with broader enterprise AI initiatives.

Application development and modernization

Use AI to understand complex applications and code, accelerate development and modernization work, and connect AI-assisted development with governed mainframe delivery processes.

Operations and troubleshooting

Apply AI and specialized agents to investigate operational conditions, identify probable cause, explain automation, and guide operators toward relevant next steps.

Database management and optimization

Apply specialized AI expertise to Db2 and IMS workflows to investigate database conditions, assemble evidence, explain findings, evaluate options, and guide performance and maintenance decisions.

Mainframe data for enterprise AI

Make trusted mainframe data available to modern analytics, AI, and enterprise decision-making so the mainframe can participate in broader enterprise AI initiatives.

How BMC AMI enables the agentic mainframe

BMC AMI brings together specialized mainframe expertise, organizational knowledge, live context, AI agents, supported models, and governed access to BMC AMI capabilities. The BMC AMI architecture for agentic AI separates key functions so knowledge, agents, models, orchestration, and access to underlying capabilities can play distinct roles.

  • Knowledge and context

    BMC AMI Knowledge Hub makes approved knowledge available to supported AI experiences and agents, while BMC AMI capabilities provide relevant operational and product context.

  • Models

    Model Services provide access to supported AI models.

  • Agents and skills

    Specialized agents perform defined work, while Agent Skills provide reusable domain instructions and expertise.

  • Discovery and coordination

    The Agent Registry supports agent discovery, the Agent Gateway connects and routes agent interactions, and the Agent Orchestrator coordinates supported agentic work where orchestration is required.

  • Governed capability access

    The MCP Gateway provides governed access to registered tools, prompts, resources, and MCP-enabled capabilities.

  • Governance

    Identity, authorization, policy, task scope, approvals, observability, logging, and auditing help keep supported agentic work within defined boundaries and human authority.

Put agentic AI to work on your mainframe

Explore how BMC AMI combines AI, specialized mainframe expertise, operational context, and governed capabilities to help organizations build toward an agentic mainframe.

Explore AI and agentic capabilities across BMC AMI

Application development and modernization

Understand, modernize, and deliver mainframe applications

Use AI to understand and modernize mainframe applications, and connect AI-assisted development with governed mainframe delivery. BMC AMI DevX Code Insights provides application and code understanding to support modernization and refactoring, while BMC AMI DevX Code Pipeline connects supported AI coding assistants with mainframe pipeline operations through its Model Context Protocol (MCP) Server (Beta), with developer approval, lifecycle controls, and audit trails.

 

Explore BMC AMI DevX

Mainframe operations

Predict, investigate, and respond to mainframe issues

Use analytics, machine learning, AI, GenAI, and specialized agents to detect anomalies, investigate operational conditions, explain probable causes, recommend next steps, and support informed responses. BMC AMI Ops Insight provides proactive detection, root cause analysis, GenAI-powered explanations, and actionable guidance, while BMC AMI Agentics for Ops adds purpose-built agentic experiences that use supported live operational context to investigate defined problems and guide operators while they remain in control.

 

Explore BMC AMI Ops

Database management and optimization

Investigate Db2 and IMS conditions with specialized AI

BMC AMI Agentics for Data uses specialized Advisor experiences for Db2 reorganization, SQL workload optimization, IMS deadlock analysis, and IMS database exceptions to assemble evidence, explain findings, evaluate options, and guide next steps while database professionals remain in control. 

 

Explore BMC AMI Data

Mainframe data for enterprise AI

Make mainframe data accessible and ready for AI and analytics

Z platform data to secure, immutable object storage, scale extraction with zIIP, and transform proprietary mainframe data into open formats off platform. BMC AMI Cloud makes trusted mainframe data accessible to AI, ML, and analytics applications while maintaining Z platform reliability.

 

BMC AMI Cloud Analytics

Governed agentic AI for the mainframe

Governance is a core part of an agentic mainframe. Identity, authorization, policies, task scope, approvals, observability, and human oversight define what AI agents can access, recommend, or perform. BMC AMI Agentics includes built-in runtime governance for

Agent performance

Monitor how supported agents perform defined work

Resource utilization

Maintain visibility into resources used by agentic activity.

Policy compliance

Apply established policies to supported agentic workflows.

Auditable activity

Maintain records of agent activity for visibility and accountability.

Agentic Mainframe FAQs







Put agentic AI to work on your mainframe

Explore how BMC AMI combines AI, specialized mainframe expertise, operational context, and governed capabilities to help organizations build toward an agentic mainframe.