AI agent protocols emerge to standardize enterprise communication

The landscape of artificial intelligence is shifting toward standardized communication protocols to manage the increasing complexity of agent-to-agent (A2A) and agent-to-tool interactions. Protocols such as the Model Context Protocol (MCP) allow agents to connect with enterprise tools, databases, and APIs, while A2A protocols enable independent agents to delegate tasks to one another.

Despite rapid adoption—with a PwC 2025 survey indicating that 79% of executives are already implementing AI agents—significant engineering challenges remain regarding security and accountability. Current agent-to-agent interactions often lack robust identity verification, authorization scopes, and audit trails. Without verifiable keys and signed receipts, agents face risks of impersonation, unauthorized data access, and a lack of recourse when tasks are disputed.

To address these gaps, developers are proposing structured frameworks including machine-readable manifests that define an agent's capabilities, costs, and required approvals, alongside signed call envelopes to ensure every interaction is authenticated and auditable.