Bridging the gap: Legacy tools gain enterprise AI support

Broadcom marshals workload acquisitions

Broadcom's Automic is structured around Jobs, software components which execute commands across different environments, such as operating systems, databases, enterprise applications such as SAP and Oracle's E-Business Suite, file transfers and web services. Version 26 adds an AI Agent Job type that orchestrates AI agents and integrates them into existing workflows. The new Job type also wraps Automic's role-based access control, logging and audit protocols around AI agents' activities for governance. Version 26 further adds a natural language-driven workload execution interface to a Python-based Code Assist tool for building data pipelines.

Rajeev Kumar

"Users can type a simple prompt and whatever LLM they have plugged into Automic, with the configurations and grounding rules that are part of the product, will generate a workflow plan," said Rajeev Kumar, head of products for workload automation at Broadcom.

For example, a business analyst might want to get data from Salesforce every day at 6 a.m., move that data to BigQuery for analysis then to Looker to produce a report, generate an AI summary of that report and email it to their CEO. Automic can now generate a workflow plan for that, Kumar said, identifying the Jobs and elements of the workflow that should be created to achieve that result, present it to the user for review, and then deploy it with the user's approval.

"AI is helping software engineers," Kumar said. "We are focused on non-software engineers, the business analysts who have been building these workflows in the past but have been relying on ad hoc tools."

Broadcom has amassed a broad set of hardware and software businesses over the last decade, positioning it among the most important AI infrastructure vendors for enterprises to consider, said Stephen Elliot, an analyst at IDC.

"People don't realize how much of the internet's traffic goes over Broadcom hardware," Elliot said. "VMware is just part of that massive infrastructure software group, and you can't forget about the CA piece, the Symantec piece, network software pieces and chip software."

BMC takes cautious, strategic view

BMC's Control-M added support for AI agents from partners such as CrewAI, LangGraph and Snowflake Cortex in its March update, along with a Jett AI advisor and workflow creator. Its support for multi-AI agent orchestration remains a work in progress, said BMC CTO Ram Chakravarti. 

"We are approaching it in two tranches: in the core product, you can now call individual agents based on prebuilt integrations and infuse them into workflows," Chakravarti said. "In parallel, we are co-innovating with some of our flagship customers for meaningful use cases where bespoke agents are being orchestrated with Control-M core, or even add-on features such as Managed File Transfer for federated data exchange with AI."

Unless your AI use cases are aligned to your overall digital business strategy, your AI pilots are going to languish as science experiments.

Federated data exchange is a process by which querying instruments access potentially sensitive data within partners' infrastructure, or vice versa, without exporting the information outside a company's network. It can be an important part of beginning work with a new partner. One pilot Control-M customer has shortened the federated data exchange process using AI agents from 30 days to fewer than 12 hours, Chakravarti said. He declined to name the customer or specify the company size, except to say that it is an "extremely large" company.

"We already built a lot of the puzzle pieces, and we're continuing to do so, but for us, it's about how we can provide predictable outcomes with Control-M, with dependency management, reliable handoffs, SLA adherence and a whole bunch of complexity management, as we do traditionally," Chakravarti said. "Unless your AI use cases are aligned to your overall digital business strategy, your AI pilots are going to languish as science experiments."

Dan Twing

BMC has also undergone extensive portfolio rationalization over the years, most notably by splitting its IT service management and operations management business, and its workload and mainframe automation business, into separate companies last year.

"Broadcom still has to extend [agentic AI support] to some of its other products, but created the foundation based on years of work, architecturally, to rationalize these things," Twing said. "BMC didn't have that challenge -- it had different challenges, like going through SaaS modernization, while Broadcom added SaaS two years ago."

AI expands mainframe modernization opportunities

Broadcom has begun integrating generative and agentic AI into mainframe management by adding MCP servers to its Rally Agile development and Endevor change management software that support mainframes alongside distributed systems. Broadcom also supports the open source Zowe framework for hybrid cloud mainframe integration, including  Zowe MCP server. Finally, IBM's WatchTower observability tool includes AIOps features for mainframes.

Updates to BMC's AMI tool in April included enterprise application analysis reporting for its AI-driven zAdviser development productivity monitoring tool. The existing AMI AI assistant added integrations with the mainframe Knowledge Hub and a Knowledge Expert chat to pull in information from sources such as runbooks, tickets, log files and prior incident resolutions.

BMC's statement of direction for AMI will move it beyond explanation and recommendations to autonomous AI agent-driven workflows for system and performance diagnostics, development workflows, security validation and operational recovery, learning from past incidents.

With this statement of direction, BMC is taking a more holistic and thoughtful approach to AI for mainframe modernization than Broadcom, said Steven Dickens, CEO at HyperFrame Research.

Steven Dickens

"Broadcom put an MCP server on the mainframe and then connected it to a bunch of legacy apps, so you can sort of interrogate them via an MCP server, which seems to me like table stakes, rather than a holistic deployment of AI," Dickens said. "BMC is looking at, 'How do we ingest support data? How do we ingest Redbooks and support databases and knowledge bases? How do we then do code explanation and automate ops with a broader radius of thinking?'""

IBM, Arm and history repeating?

In Dickens' view, BMC has the most ambitious mainframe strategy, but IBM also has its Concert AIOps software that supports System Z automation, along with control over mainframe hardware, which it brought to bear in its recent agreement to support Arm chips.

IBM undertook a similar effort to integrate x86 chips into its zBX systems more than a decade ago, which can now support most major enterprise workloads but has a few known issues in areas such as storage resource management and, in some cases, third-party application support, Dickens said.

Opening the platform further to Arm chips could offer another avenue for third-party app compatibility, and there are strong incentives on both sides to make the Arm integration work, Dickens said.

"Whatever anybody says about the mainframe, it's highly available, highly resilient, highly performant -- it's the fastest commercially available processor," he said. "Arm is getting access to that instruction set collaboration with hundreds of chip developers and architects -- IBM has got some chops in this space."

However, Dickens said he doesn't expect to see any shippable results from the collaboration until the launch of the next-generation System Z, likely in 2028, according to IBM's typical three-year System Z release cadence. The latest z17 systems were launched in April 2025.

On the workload automation side, an October 2025 EMA Radar Report for Workload Automation and Orchestration placed IBM's Workload Automation in the "strong value" category. This ranked below Control-M and Automic, which were among the tools in EMA's top "Value Leader" category, alongside Stonebranch, HCLSoftware, Beta Systems and Redwood.

But overall, IBM and Red Hat have a strong set of hybrid cloud agentic AI tools to compete with, Dickens said, for enterprise buyers.

"When you look at Red Hat, you look at the OpenShift integration that they've done on the mainframe -- IBM is not just having a mainframe tools conversation, it's having a more holistic hybrid IT kind of conversation," Dickens said.

Beth Pariseau, senior news writer for Informa TechTarget, is an award-winning veteran of IT journalism. Have a tip? Email her or connect on LinkedIn.