Ad Context Protocol (AdCP) is often portrayed as a simple solution, but most initial projects using it are likely to fail. The issue isn’t the protocol itself but the misconception that AdCP is merely an API upgrade. In reality, it represents a complex, asynchronous, stateful, multi-tenant engineering challenge that requires much more than a simple integration.
Unlike a typical API call, AdCP operations involve multiple stages and delays. For example, a media buy request enters a pending approval state and can take hours or days to complete, requiring the system to manage asynchronous workflows and handle webhooks from external servers.
Engineering teams must build an orchestration engine with several critical capabilities:
- Persistent state management to track tasks over extended periods
- Durable processes that handle restarts, webhook ingestion, and workflow resumption
- Robust failure management including retries with exponential backoff, idempotency to avoid duplicate actions, and circuit breakers for partner outages
Moreover, running AdCP effectively means implementing a central “hub” to manage multiple partnerships, enabling shared budget control and unified analytics. This hub acts as the orchestration brain, coordinating data harmonization, budget allocation, and error handling.
Despite the complexity, adopting AdCP is preferable to continuing with fragmented and static data exchanges. Its shared ontology allows data to flow seamlessly, while its action protocol enables automation across independent systems. This facilitates strategic, repeatable campaigns without the need for numerous bespoke vendor integrations.
AdCP complements existing protocols like OpenRTB:
- OpenRTB: Handles high-frequency, sub-second auction transactions
- AdCP/MCP: Manages low-frequency workflows such as planning, setup, and reporting, which can take hours or days
This combination shifts the focus from fragile integrations to intelligent orchestration strategies.
To implement AdCP pragmatically, follow these steps:
- Launch a read-only pilot with one or two partners to validate data integration and schema consistency.
- Run a small-scale write pilot to test asynchronous loops and webhook processing, prioritizing technical validation over ROI.
- Establish governance with human-in-the-loop approval workflows and immutable audit trails before scaling.
- Develop the core hub architecture featuring state machines and canonical data models to streamline adding new AdCP-compliant partners.
In conclusion, AdCP demands considerable engineering effort but offers a controlled, auditable orchestration layer that replaces the chaos of brittle scripts. Organizations should adjust budgets and expectations accordingly, investing in the hub rather than underestimating the scope as just an API update.