Beyond the Observability Mesh: Why The Next Enterprise Platform Will Govern Intelligence

Enterprise AI stopped being a model-selection conversation the moment autonomous agents began interacting with enterprise systems. Governance has evolved from a compliance discussion into an architectural necessity, with Microsoft and IBM both shipping control planes for agent fleets this year. The architectural question underneath remains open.

Sai Krishna Cheemakurthi is Vice President and Lead Infrastructure Architect for Enterprise Observability at U.S. Bank. A Senior IEEE Member and Forbes Technology Council member, he has spent over a decade building petabyte-scale observability and resiliency platforms for global financial institutions. Last year, he introduced the Observability Mesh as a way to turn signal volume into meaning. This time, he described what sits on top of it.

"The Observability Mesh tells the enterprise what's happening. The Enterprise AI Control Plane determines what should happen next, securely, intelligently, and with human accountability," said Cheemakurthi. "Organizations today don't have an AI model problem. They have an AI coordination problem," he said. Cloud introduced distributed computing. AI is introducing distributed intelligence. Just as distributed computing required orchestration, distributed intelligence requires coordination. Most enterprises won't run one AI, but will operate an entire AI estate consisting of models, agents, workflows, knowledge systems, and business tools. Coordinating that estate becomes the real challenge.

• What uncoordinated looks like: A single customer request to raise a credit limit can touch identity verification, fraud analysis, credit risk, spending behavior, and pricing, each running different AI capabilities. "One AI says approve it. Another says decline it. Another uses outdated customer data while another uses a different policy," Cheemakurthi said. The challenge isn't intelligence, but enterprise coordination across intelligent systems.

• No tower, no traffic: "Imagine an airport without an air traffic controller. Every pilot flies well, yet the airport becomes unsafe," he said. Duplicate agents, overlapping use cases, and inconsistent security controls produce the same result at enterprise scale, which is why multi-agent governance keeps landing on CIO agendas.

The fix he proposed separates awareness from authority. Observability collects and correlates. The control plane decides what an approved system is allowed to do with that correlation, a split that mirrors the ledger discipline banks already run.

• Two layers, one loop: "The Observability Mesh is the enterprise's sensory system. The Enterprise AI Control Plane is its decision-making system. AI agents and automation become the execution layer," Cheemakurthi said. Outcomes feed back into the mesh, which is where governance stops being a document and starts living in the pipeline.

• More than models: The layer has to manage identity, routing, evaluation, observability, lifecycle, cost controls, and runtime enforcement. An AI gateway handles entry, authorization, prompt and response inspection, rate limits, and tokenization. "Optimizing token consumption and intelligently routing requests reduces cost without sacrificing quality," he said.

• Autonomy has a clock: "The question is not whether an agent is autonomous, but autonomous within what boundaries, and for how long, and what the rollback policy is," Cheemakurthi said. In his framing, identity becomes the boundary of autonomy, which is the same position the Cloud Security Alliance has taken on non-human actors.

He rejected the idea that any of this slows delivery. "Poor governance slows innovation, because every team must reinvent the security evaluation and the compliance," he said. A well-designed control plane offers approved models, reusable patterns, and automated guardrails, so teams move without repeating risk reviews.

That produces a split ownership model, shared across platform, security, risk, data, and business teams. "Governance should be logically centralized, but execution can remain federated," Cheemakurthi said, describing an arrangement close to the governed platform with federated execution pattern now spreading through banking. The central team owns the paved road. Teams own their destinations.

What that leaves CIOs is a build order rather than a procurement decision. You cannot govern what you cannot see. Observability must come before autonomy. "A policy document tells teams what should happen. A control plane makes those policies operational," he said.

"The next enterprise platform will not simply manage infrastructure. It will govern intelligence. The winners of the AI era won't have the smartest model. They will have the smartest operating model for AI."