BMC Aims to Be the "Orchestrator of Orchestrators" in the Age of Agentic AI

BMC Aims to Be the "Orchestrator of Orchestrators" in the Age of Agentic AI

Generative AI may be one of the fastest-adopted technologies in history, but for many businesses, the question remains: where’s the value? A recent McKinsey study shows nearly 80% of companies are already experimenting with generative AI, yet relatively few are seeing measurable impact on the bottom line.

One answer, experts suggest, lies in orchestration. Rather than deploying AI tools in isolation, orchestration provides a way to connect and manage them effectively—what some call the point when “agents become agentic.”

AI agent orchestration: The CIO’s crucial next step
As companies deploy dozens of AI agents and LLMs, they will need to control and connect them all through an orchestration and integration platform, experts say.

That’s where BMC believes it can play a central role. The enterprise software company positions its Control-M platform as a hub for workflow automation, bringing together different systems and applications under one point of control. BMC’s approach has already earned recognition: last month, Gartner named the company a leader in its Magic Quadrant for service orchestration and automation platforms.

Control-M - BMC Software
Control‑M simplifies and automates diverse batch application workloads while reducing failure rates, improving SLAs, and accelerating application deployment.

According to Basil Faruqui, BMC’s director of solutions marketing, the company’s vision is clear: Control-M as the “orchestrator of orchestrators.” Today, that means coordinating applications and APIs. But within the next year or two, Faruqui predicts orchestration will extend to AI agents themselves.

Other players are moving in a similar direction. Salesforce recently introduced Agentforce, a platform designed to help enterprises scale and manage AI agents across business functions. For BMC, the trend is inevitable.

Salesforce Launches Agentforce 3 to Solve the Biggest Blockers to Scaling AI Agents: Visibility and Control
New Agentforce Command Center provides a complete observability solution for optimizing AI agents — enabling leaders to manage, track, and scale how AI agent activity enhances human productivity Agentforce 3 enables seamless agent interoperability with built-in support for open standards like Model Context Protocol (MCP). Through the expanded AgentExchange, customers will be able to access […]
“Whether it’s a data warehouse, whether it’s a CRM like Salesforce or SAP, all of these things will be automating their functions using agentic AI,” Faruqui explains. “That’s really where we see our future in this ‘agent economy’—automating and connecting agents across systems.”

The stakes are high. In a conversation with the CTO of a major healthcare organization processing over $10 billion in claims each month, Faruqui learned that early testing of generative AI had been “transformative,” cutting operational timelines dramatically. But he cautions that pilots don’t equal production. For AI to deliver sustainable value at enterprise scale, issues like governance, reliability, and integration need to be addressed—and orchestration is a key part of that equation.

Momentum behind AI adoption is also shifting higher up the corporate ladder. Faruqui notes that boards of directors—not just CIOs and CTOs—are increasingly sponsoring AI initiatives. Some companies are even reporting progress in shareholder letters, underscoring how central AI has become to corporate strategy.

With that level of investment and urgency, Faruqui says vendors must move quickly.

“This is going to move fast, which means that, from the vendor side, we have to be ready, not in three years, [but] six months,” he says. “We in BMC are working through a very bold vision where we see this agent economy really taking off—and orchestration is the vehicle for business outcomes.”

Read more