The Ad Context Protocol (AdCP) is often touted as a simple solution for ad tech integration, but first-time projects usually face failure. This is not due to flaws in the protocol itself, but because organizations underestimate the complexity involved, expecting a straightforward API upgrade when they actually need to build a distributed system.
AdCP operates as an agentic automation tool, which introduces a significant engineering challenge. Unlike typical API calls, AdCP workflows are asynchronous, stateful, and multi-tenant. For example, a media buy request returns a “status: submitted” response, placing the buy in a pending approval state that can last hours or days until manual approval triggers a webhook response.
This means engineering teams must develop a robust orchestration engine capable of:
- Persisting state with durable job queues and state machines to track tasks over extended periods.
- Handling asynchrony with reliable server-side processes that manage restarts, webhook ingestion, and workflow resumption.
- Managing failures via retry mechanisms, idempotency safeguards, and circuit breakers to handle partner downtime.
Additionally, the use of a central AdCP “hub” is essential for scaling beyond pilot projects with single partners. This hub acts as the core coordinator, enabling unified analytics, budget control, and managing numerous servers and partners.
Despite its complexity, AdCP represents progress beyond the current state of static, fragmented integrations, offering a shared ontology for data and a protocol that allows work to move efficiently across sovereign systems. It complements rather than replaces OpenRTB, functioning as the low-frequency workflow layer for planning, setup, and reporting, while OpenRTB handles real-time bidding.
To implement AdCP effectively, experts recommend a staged approach:
- Begin with a read-only pilot connecting a few partners to validate data plumbing.
- Proceed with a small-scale write pilot to test asynchronous workflows and webhook handling.
- Develop governance mechanisms, including human-in-the-loop approvals and immutable audit trails.
- Build a core hub architecture with state machines and canonical data models for scalable partner integration.
AdCP demands significant engineering investment but replaces fragile, bespoke scripts with a strategic, auditable orchestration layer. Rather than budgeting for a simple API, organizations should prepare for building and maintaining a comprehensive hub.