Agentic Advertising Management Protocols (AAMP)

What is Agentic Advertising Management Protocols | AXD Observatory?

The IAB Tech Lab.

What is 01 - The Machine That Buys the Ad?

What is 02 - Three Pillars of AAMP?

What is Pillar One: ARTF - The Agentic Real-Time Framework?

What is Pillar Two: Agentic Protocols - The Management Layer?

Key concepts in Agentic Advertising Management Protocols | AXD Observatory

How do agentic advertising management protocols relate to agentic commerce?

  1. Agency requires intentional delegation — every agentic system begins with a designed act of delegation
  2. Trust is the primary material — AXD works in trust rather than attention
  3. Absence is the primary use state — the most consequential experiences happen when no one is watching
  4. Relationships have temporality — agentic experiences accumulate history over time
  5. Outcomes replace outputs — AXD designers specify results, not interfaces
DimensionTraditional UXAgentic Experience Design (AXD)
Primary materialAttention and affordanceTrust and delegation
User statePresent, navigatingAbsent, delegating
Design outputScreens and interfacesOutcomes and constraints
Temporal modelSession-basedRelationship-based
Success metricTask completionTrust calibration

Frequently Asked Questions

What is AAMP (Agentic Advertising Management Protocols)?

AAMP is the IAB Tech Lab's umbrella initiative for governing how autonomous AI agents operate within the advertising ecosystem. Announced in February 2026 and fully unveiled at the Beet Retreat, AAMP comprises three pillars: (1) ARTF - the Agentic Real-Time Framework, a high-performance execution control plane that cuts real-time bidding latency by 90% through containerised agent co-location; (2) Agentic Protocols - schemas, SDKs, and reference implementations built on AdCOM and OpenDirect that

What is the Agent Registry and why does it matter for agentic commerce?

The Agent Registry, launched on 1 March 2026 by the IAB Tech Lab as part of AAMP, is the first operational trust infrastructure for non-human economic actors in any industry. It provides agent identity verification, capability disclosure, and accountability records - enabling buyer and seller agents to verify each other before transacting. From an AXD perspective, the Agent Registry is the advertising industry's implementation of Know Your Agent (KYA) principles, and it represents the first real

What is AdCP and how does it differ from AAMP?

The Ad Context Protocol (AdCP) is a competing initiative founded by Yahoo, Optable, PubMatic, Scope3, Swivel, and Triton Digital. Unlike AAMP, which builds on the IAB Tech Lab's existing advertising standards (OpenRTB, AdCOM, OpenDirect), AdCP is built directly on top of Anthropic's Model Context Protocol (MCP). Now at version 3.0 as of March 2026, AdCP provides advertising-specific workflows for campaign setup, bidding, and media buying. The AAMP-vs-AdCP dynamic mirrors the A2A-vs-MCP fragmenta

Why is advertising the first industry to build comprehensive agent-to-agent trading infrastructure?

Advertising was structurally pre-adapted for agentic commerce because its core transaction - the real-time bid - was already machine-to-machine. Programmatic advertising has operated as automated agent-to-agent trading since the early 2010s, with demand-side platforms (DSPs) and supply-side platforms (SSPs) executing billions of transactions per day without human involvement. The shift to agentic AI does not introduce machine-to-machine trading to advertising; it introduces autonomy, judgment, a

What is AAMP (Agentic Advertising Management Protocols)?

AAMP is the IAB Tech Lab's umbrella initiative for governing how autonomous AI agents operate within the advertising ecosystem. Announced in February 2026 and fully unveiled at the Beet Retreat, AAMP comprises three pillars: (1) ARTF - the Agentic Real-Time Framework, a high-performance execution control plane that cuts real-time bidding latency by 90% through containerised agent co-location; (2) Agentic Protocols - schemas, SDKs, and reference implementations built on AdCOM and OpenDirect that

Key Takeaways

On a Tuesday in March 2026, a brand's autonomous media buying agent submits a bid for a premium video placement on a publisher's inventory. The bid is not a number. It is a structured mandate: a set of audience parameters, brand safety constraints, attention thresholds, frequency caps, and a maximum cost-per-outcome that the brand's human marketing director specified three weeks ago and has not revisited since. The publisher's selling agent receives the mandate, evaluates it against fourteen other bids from fourteen other buying agents, and accepts the one that best satisfies its own mandate - a set of yield targets, advertiser quality thresholds, and audience composition requirements specified by the publisher's revenue team. The transaction completes in eleven milliseconds. No human on either side was consulted. No human on either side was aware it happened. The brand's agent reports the placement in a weekly summary. The publisher's agent adjusts its yield model and moves to the next bid. Somewhere between the two, a trust verification occurred: each agent confirmed the other's identity, capability scope, and authorisation chain before the transaction was permitted to execute. This is not a future scenario. This is the operational reality that the IAB Tech Lab's Agentic Advertising Management Protocols (AAMP) Advertising is not the industry most people associate with the frontier of Programmatic advertising - the automated buying and selling of digital media inventory through real-time bidding (RTB) - has operated as machine-to-machine trading since the early 2010s. Demand-side platforms (DSPs) submit bids on behalf of advertisers. Supply-side platforms (SSPs) evaluate and accept bids on behalf of publishers. The transaction volume is staggering: billions of bid requests per day, each resolved in milliseconds, each executed without human involvement at the point of transaction. The infrastructure for machine-to-machine trading in advertising is not emerging. It i

References and Citations

Gartner: Machine Customers as Strategic Technology Trend Stanford HAI: Human-Centered AI Research NIST AI Risk Management Framework About the AXD Institute Contact Us Email the AXD Institute Tony Wood on LinkedIn Tony Wood on X (Twitter)