The IT industry faces challenges with multiple, competing standards aimed at addressing agent-to-agent communication in AI, risking the potential of agentic AI. This situation reflects historical issues with service-oriented architecture and messaging conflicts. Numerous technologies like OpenAI's Function Calling and Microsoft's Semantic Kernel Extensions aim to facilitate these interactions but contribute to the overwhelming number of protocols. The emergence of many standards driven by various agendas complicates achieving a straightforward solution for interoperability among intelligent agents, undermining their efficiency, security, and transparency in communication.
The IT industry develops many competing standards to solve a simple problem of agent-to-agent communication in AI, which may limit the potential of agentic AI.
Intelligent agents need to communicate efficiently, securely, and transparently; however, emerging standards are proliferating from various groups, complicating interoperability.
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