As AI rapidly moves from experimentation to execution, one question is becoming unavoidable for enterprise leaders: how do you let AI act on real business processes without losing control?
For Anshu and Kevin, the answer lies in Enterprise MCP. Not as a buzzword, but as a fundamental shift in how systems, processes, and AI interact across the organization.
“Two years from now, people might not even use the term MCP,” explained Anshu Mishra, Director of Employee Experience at F5. “But it will have fundamentally changed the way business gets done.”
From Automation to True Business Orchestration
Traditional automation has helped teams move faster, but it still operates within defined lanes. Enterprise MCP pushes beyond that by creating a seamless, intuitive bridge between AI and enterprise systems.
“It gives you the ability to do wonders and magic,” Anshu said. “You can think beyond the way we’re developing automation today.”
At its core, MCP acts like a universal plug. Standard input, standard output, no matter where you are in the enterprise stack. That consistency allows AI to interact naturally with business processes, instead of being bolted on as an afterthought
Why Governance Can’t Be an Afterthought
While the promise of AI-driven processes is powerful, it also introduces real risk. Uncontrolled access, unclear permissions, and compliance gaps can quickly turn innovation into liability.
“One of the big challenges with raw MCP is governance,” noted Kevin Wolf, Senior Director of Information Technology at Swanson Health. “Ensuring rights and permissions becomes really hard and really scary.”
Enterprise MCP changes that equation by embedding governance directly into the architecture. Every interaction is monitored, audited, and controlled through enterprise-grade software.
“Everything that goes in and comes out is governed,” Kevin said. “You can audit it, report on it, and remain compliant as a public company without creating a whole new set of compliance problems.”
That balance, innovation with discipline, is what makes Enterprise MCP viable at scale
Guardrails That Let AI Work Safely
Handing business processes over to AI requires trust, and trust comes from accuracy and rules.
“What Enterprise MCP provides is guardrails,” Kevin explained. “It allows AI to fulfill a business process within a defined set of rules.”
Instead of AI operating freely across systems, it works within clearly defined boundaries. The result is faster execution without sacrificing reliability or accountability, addressing one of the biggest concerns enterprises have about AI adoption.
“The real value of Enterprise MCP is that it lets AI operate with discipline. You’re not just handing over business processes, you’re defining the rules, the permissions, and the guardrails so AI can execute safely within them,” said Anshu.
Faster Time to Value with Pre-Built Connectivity
Another advantage of Enterprise MCP is how quickly teams can move from idea to execution.
“With pre-built connectors, you get an out-of-the-box client library that already speaks MCP,” Kevin said. “You don’t have to focus on infrastructure, you focus on the core business logic.”
That shift mirrors what many IT teams are striving for today: spending less time wiring systems together and more time solving meaningful business problems.
A Change Leaders Will Feel, Even If They Don’t Name It
Perhaps the most telling insight from the conversation is how invisible MCP may become to executives over time.
“Most leaders won’t talk about MCP by name, but it’s going to reshape how their business runs,” Anshu said. “It will quietly become part of how work gets done, and the impact will be bigger than almost any initiative we’re driving this year.”
In that sense, Enterprise MCP isn’t just a technical evolution, it’s a platform shift. Kevin summed it up simply: “It’s a new iPad for the agents.”
As enterprises move from AI experimentation to real operational impact, Enterprise MCP is emerging as the connective tissue that makes it all possible — securely, compliantly, and at scale.