4. Interoperability and open standards
MCP and A2A are two ways AI agent orchestration platforms support open standards and enable connecting to an ecosystem of agents. Many platforms also allow developers to select and replace the underlying AI models and to choose from a range of AI code-generation tools. These flexibilities ensure teams can optimize around performance, accuracy, compliance, costs, and other future considerations.
“When evaluating an AI orchestration platform, we look first at composability and interoperability,” says Rajesh Arora, chief data and analytics officer at Principal. “The real test is not how many features it offers today, but whether it can connect models, data sources, agentic solutions, and workflows in a way that adapts to our AI strategy, tech stack, and changing business needs.”
Other interoperability criteria to review include the platform’s AI agent cataloging capabilities, how permissions are configured dynamically, and whether prebuilt connectors are available for the required integrations.
