Enterprise Agent Planner - The Missing System of Record for AI Agents
Every major enterprise function has its system of record. ERP for resources. CRM for customers. HRIS for employees. ServiceNow for IT workflows.
These systems didn’t emerge overnight. They became essential because without them, enterprises had duplication, fragmentation, and chaos. Finance ran on inconsistent spreadsheets. Customer data was scattered across teams. IT relied on ad hoc ticketing. Systems of record brought order, governance, and scale.
Now, as enterprises experiment with AI agents, we’re watching history repeat itself.
Next Moca’s EAP provides a System of Record for Enterprises to manage agent chaos
The Current State: AI Agent Chaos
Right now, AI agents live in silos:
A marketing team builds a campaign bot.
HR experiments with resume screening.
Ops prototypes process automation.
Each is built in isolation, often with different tools or frameworks. They’re fragile, duplicative, and almost impossible to govern. One department doesn’t know what another is running. Security teams scramble to audit. Compliance can’t enforce policies. The result: agent chaos.
We saw this same movie before SaaS platforms matured. Without a system of record, progress stalls at pilots and proofs of concept.
The False Tradeoff: Innovation vs. Control
Some leaders believe you need to choose between moving fast and staying in control. In reality, the opposite is true. Without governance, reuse, and consistency, speed collapses. Every team reinvents the wheel. Compliance bottlenecks slow projects to a crawl.
The truth: control enables speed. Guardrails allow more teams to innovate with confidence.
Why a System of Record Is Needed
Just as ERP standardized financial processes and ServiceNow centralized IT workflows, AI agents need their own system of record. The Enterprise Agent Planner fills this gap by providing:
A Catalog of reusable agents, tools, and knowledge — so teams don’t rebuild from scratch.
Governance and Compliance built in — so policies are enforced and risk is reduced.
Orchestration — connecting agents into broader workflows, rather than isolated experiments.
Declarative Spec — ensuring agents are predictable, auditable, and shareable across the enterprise.
This transforms agents from scattered prototypes into an enterprise-wide capability.
A Look Ahead: From Pilots to Scale
History shows every platform shift reaches this tipping point. Before CRM, customer data was chaos. Before ERP, finance was chaos. Before ServiceNow, IT workflows were chaos. AI agents are at the same moment.
The companies that adopt a system of record early will move faster, scale further, and pull ahead. Those that don’t will remain stuck in endless pilots.
At Next Moca, we call this the Enterprise Agent Planner — the missing layer that makes AI agents production-ready.
The pattern is clear: demos → adoption → system of record. And with AI agents, that time is now.
📅 Want to see it in action? Book a walkthrough
🌐 Learn more: https://www.nextmoca.com
