Why interoperability is the foundation of productive enterprise AI

Across every industry, AI agents are multiplying and becoming more critical in daily operations. Yet as adoption accelerates, fragmentation has emerged as a new challenge. Business leaders are wrestling with disconnected agents that can’t communicate, coordinate or comply with shared governance, slowing time-to-value and creating inconsistent outcomes. The reality is that organizations rarely run on a single platform and agents need to reflect the state of these environments that were not designed to be uniform.

Modern enterprises operate across a patchwork of SaaS systems, existing applications, CRM platforms, cloud providers and custom-built tools. This ecosystem often includes technologies such as SAP, Salesforce, ServiceNow and a wide range of cloud applications and custom systems. And as AI adoption spreads across functions, that complexity compounds.

A single-suite agent platform does not reflect reality. However, the organizations that win the agent era will be the ones that can govern, orchestrate and scale an entire agent workforce across clouds, vendors and systems.

As organizations scale AI, many instinctively try to standardize tools across teams. But standardization slows innovation and rarely reflects how global, hybrid enterprises operate. The AI landscape evolves too quickly for one platform to meet every requirement or use case. Plus, requiring every part of your organization to adopt the same tools is often unrealistic and slow.

Interoperability flips the model. Instead of forcing teams to conform, it allows agents to operate across existing systems. Teams can use the tools what work best for their workloads while still connecting their agents. This approach gives enterprises flexibility, governance and faster time-to-value without disruptive migrations.

As an organization’s number of agents grows, line of business (LOB) and IT decision makers need a reliable way to manage them. This workforce shouldn’t be approached as isolated assistants, but as a workforce of virtual employees with roles, permissions and accountability. The agent catalog becomes the system of record for how agents operate, who manages them and how they interact. 

A catalog defines approved agents, their permissions, integrations and guardrails. It is the backbone for orchestrating reusable agents across departments, enabling scalable, governed automation. With an agent catalog, you’ll be balancing speed and trust in a high-demand environment.

Interoperability is both an IT decision and a business accelerator. As organizations adopt AI agents across departments, the value multiplies only when those agents can collaborate across systems, workflows and data sources. Leaders aren’t looking for “more tools”, they’re looking for unified outcomes: 

• Accelerated ROI with reusable, governed agents
  When agents can operate across systems, teams no longer reinvent automations from scratch, turning investments into productivity and enterprise-wide impact.

• Consistent customer and employee experiences
  Interoperability ensures that whether a customer is checking an order, requesting service or resolving an issue, each workflow feels unified and reliable.

• Reduced operational and compliance risk
  Organizations need AI that complies with security, access controls and audit requirements. Interoperability enables shared governance across environments, reducing the chance of “shadow agents” or automation drift.

• Streamlined end-to-end workflows
  Just like your employees, the biggest gains can come when multiple agents coordinate and execute their roles in tandem. Interoperability is what makes coordinated, multistep journeys possible.

• Adaptable AI ecosystems
  Technology, models and vendors change. An interoperable architecture gives organizations the flexibility to add, replace or upgrade AI capabilities without starting over.

Leaders can begin moving toward enterprise-wide interoperability by taking a series of focused, practical steps:

1. Evaluate your current “shadow agent landscape”
   Map which teams have already created agents, automations or custom integrations. Most organizations discover dozens of untracked or duplicative efforts across HR, finance, service operations, IT and development.
   
   
2. Establish governance teams, access controls and accountability
   Agent operations (AgentOps) enable teams to manage, monitor and improve agentic development. AgentOps helps you define who can create agents, what data they can access and how those agents are monitored. You can treat agents like digital employees with roles, permissions and performance expectations.
   
   
3. Adopt an interoperability layer that works across your systems
   Select platforms and orchestration layers that span all environments and applications. The goal is connection, not standardizing the entire enterprise on one vendor. An AI agent gateway provides a single point of connection and control to access AI services through APIs.
   
   
4. Build—or adopt—an agent catalog
   This process becomes the operational backbone for discovering approved agents, managing roles and permissions, applying governance and enabling reuse across teams. It replaces fragmentation with a single system of record.
   
   
5. Shift the mindset from deploying agents to orchestrating a workforce
   True enterprise AI happens when agents collaborate across steps, teams and business functions. Leaders should think in terms of a coordinated agent workforce, not a collection of isolated assistants.

Open, governed interoperability is becoming the foundation of enterprise AI and this moment is exactly where IBM watsonx Orchestrate® provides a clear path forward. As organizations adopt agents across functions and platforms, watsonx Orchestrate enables them to connect, govern and orchestrate a coordinated agent workforce. It brings together SAP, Salesforce, ServiceNow, custom systems and any environment they already rely on. 

The AI gateway feature adds a single point of connection and policy control for accessing AI services through APIs, ensuring every agent interaction is secured, observed and managed consistently. 

IBM watsonx Orchestrate gives enterprises what fragmented tools cannot: a unified interoperability layer.