The IAB Tech Lab released a new specification Tuesday that creates a standard, machine-readable format for the Request for Proposal (RFP) process in digital advertising. The move targets a stubbornly manual workflow that sits between media planning and actual purchases, a gap that becomes critical as AI agents take over more of the discovery and evaluation work.
"As agents take on more of the work in media planning and buying, the industry needs a common framework for the RFP and proposal process," said Anthony Katsur, CEO of IAB Tech Lab.
The specification, called OpenProposal, is part of the broader Agentic Advertising Management Protocols (AAMP) 3.0 framework. It will remain open for public comments until October 22.
Why the RFP-to-buy gap matters now
Digital media buying already relies on technical standards for most stages of a transaction. But the handoff from an RFP to an actual purchase has stayed manual and human-driven. As AI agents begin handling media discovery, evaluation, and planning, that manual handoff creates a bottleneck. Without a common language, buyer agents and seller agents cannot exchange and evaluate proposals before executing a deal.
OpenProposal defines how sellers represent advertising products and respond to buyer briefs in an agent-readable format. It lets buying agents discover and compare opportunities against a brief while giving sellers control over how their inventory and ad products appear. Once approved, the specification will be built into the Buyer and Seller Agent SDK reference implementations.
How it connects to existing infrastructure
OpenProposal does not replace existing standards. It connects to IAB Tech Lab protocols already in use across AdCOM, OpenDirect, and the Deals API. Together, these standards create a foundation for agentic workflows that move from discovery and planning through negotiation, buying, execution, and reporting.
AAMP 3.0 itself provides a seven-stage framework that automates the full digital advertising lifecycle. Sellers can publish inventory. Buyers can discover, compare, and qualify matching audience opportunities. The framework also supports negotiation, campaign execution, and performance reporting using current industry infrastructure.
What publishers and buyers get
For publishers, OpenProposal makes ad products readable by agentic agents and provides a standard way to create proposals in response to buyer briefs. Proposals can include information that helps buyers understand how products can be bought, executed, measured, and evaluated. That gives media teams a way to assess a broader selection of potential media without manual back-and-forth.
The agent software development kits will continue to support deterministic guardrails around pricing, ad packages, orders, and media buying details. The IAB Tech Lab said these guardrails help ensure consistent responses and data integrity as agents operate at greater speed and scale, and as trust in agents increases and identity is strengthened across transactions.
Why this matters for creatives, marketers, and sales teams
For marketing and sales professionals, the shift to agentic advertising changes where human judgment gets applied. Instead of spending time on manual RFP formatting and proposal comparison, teams can focus on brief strategy, creative direction, and relationship-building with publisher partners. Writers and creatives should pay attention because the proposals these agents exchange will still need to represent ad products clearly and persuasively - the format is becoming standardized, but the positioning and product narrative remain human work. Understanding how agents read and evaluate proposals will become a practical skill for anyone building or selling ad packages.
For teams exploring how AI agents fit into advertising workflows, structured training can help bridge the gap between technical standards and day-to-day practice. Resources like AI agent courses cover the automation frameworks that underpin agentic systems, giving marketers and sales leads a clearer picture of how these tools make decisions.
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