"But this transformation won't happen instantly and without effort. Agentic AI needs schemas and standards to work. They provide invaluable, referenceable context, so the agents get trained to execute exactly what you asked them in natural language with repeatable accuracy. Which means ripping out battle-tested infrastructure and starting from scratch - as some emerging agentic protocols propose - is the slowest and most painful path you can possibly imagine."
"Why ditch existing schemas? The open standards that have emerged for allowing AI agents to communicate with each other - Model Context Protocol (MCP) and Agent-to-Agent (A2A) - are fundamentally schema-driven. The schemas they rely on are the shared protocol that enables automation. The industry can take two different paths regarding the protocols that underpin agent-to-agent communication:"
Agentic AI will reshape media discovery, planning, buying and measurement but requires time and effort to implement. Schemas and standards provide referenceable context that train agents to execute natural-language instructions with repeatable accuracy. Abandoning existing, battle-tested infrastructure in favor of starting from scratch would be slow and painful. Open standards for agent communication, such as Model Context Protocol (MCP) and Agent-to-Agent (A2A), are fundamentally schema-driven and depend on shared protocols to enable automation. Without shared schemas, agent-to-agent programmatic negotiation is impossible. The industry faces two paths: invent entirely new schemas unlikely to achieve rapid universal adoption, or adopt existing schemas and taxonomies like OpenDirect, AdCOM and OpenRTB to enable interoperability.
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