Three-moment lifecycle
AI provenance flows through three distinct moments, each handled by existing AdCP tasks.
Each moment is independent. A buyer can declare provenance without any verification having occurred. A seller can verify without requiring a declaration. Enforcement can happen with or without both.
AI detection via get_creative_features
AI detection is a creative governance feature, evaluated by specialist agents throughget_creative_features — the same task used for security scanning, creative quality, and content categorization. AI detection does not require a separate protocol or workflow.
Agent declares AI detection capabilities
An AI detection agent advertises its features viaget_adcp_capabilities:
Seller evaluates a creative
The seller sends the creative manifest to the AI detection agent:Agent returns detection results
Seller applies enforcement logic
The seller compares the detection result against the buyer’s provenance claim:Multi-agent evaluation
AI detection fits naturally into the multi-agent creative governance pattern. A seller evaluating a creative can call multiple specialist agents in parallel:
The orchestrator calls all agents via
get_creative_features, aggregates results, and applies its requirements across all of them. AI detection is one column in the evaluation matrix, not a separate workflow.
Content standards integration
For publisher content (artifacts), provenance verification uses the content standards infrastructure:calibrate_content for alignment and validate_content_delivery for auditing.
Artifact provenance
Publishers declare provenance on artifacts the same way buyers declare it on creatives:Calibration for AI provenance
Duringcalibrate_content, the verification agent can evaluate whether artifact provenance claims are accurate. This uses the same calibration dialogue as brand suitability — the verification agent returns verdicts with explanations:
Post-delivery validation
Buyers can audit AI provenance in delivered content throughvalidate_content_delivery, the same task used for brand suitability auditing:
Compliance profiles
Different regulatory environments require different levels of provenance enforcement. Here are example configurations.These profiles are illustrative configurations, not schema-defined objects. Each seller implements enforcement logic suited to their regulatory requirements. The AdCP schemas provide the data model; the enforcement rules are implementation decisions.
For regulators
AdCP provides a machine-readable, protocol-level mechanism for AI disclosure in programmatic advertising. Every creative and content artifact in the supply chain can carry structured provenance metadata that declares the digital source type, the AI tools used, the level of human oversight, and the applicable disclosure requirements by jurisdiction — including specific regulation identifiers such aseu_ai_act_article_50, ca_sb_942, and cn_deep_synthesis.
This metadata uses the IPTC digital source type vocabulary, the same classification system adopted by C2PA Content Credentials, Meta, and Google for AI content labeling. AdCP does not invent a new taxonomy. It carries an existing, widely adopted one through the advertising supply chain where it has not previously been available in structured form.
Verification is independent, not self-reported
Provenance in AdCP is explicitly a claim, not a certification. The declaring party — typically the advertiser or their agency — attaches provenance when submitting a creative. The enforcing party — typically the publisher or their supply-side platform — verifies that claim independently using AI detection services, C2PA manifest validation, or both. This verification happens through existing AdCP governance mechanisms (get_creative_features for creatives, calibrate_content for publisher content) and does not require new infrastructure.
This architecture addresses a structural problem in advertising compliance: the party submitting the creative has an incentive to understate AI involvement (to avoid placement restrictions or disclosure requirements), while the party publishing the creative bears the regulatory liability for non-disclosure. By treating provenance as a verifiable claim rather than a trusted assertion, the protocol ensures that compliance does not depend on the good faith of any single participant.
Mapping to regulatory requirements
EU AI Act Article 50: Requires that AI-generated content be labeled in a machine-readable way. AdCP’sdigital_source_type field provides this classification at the asset level. The disclosure.jurisdictions array allows creatives to carry jurisdiction-specific label text. Enforcement points can filter or flag creatives based on digital_source_type values that indicate AI generation (trained_algorithmic_media, composite_with_trained_algorithmic_media).
California SB 942: Requires disclosure when content is generated or substantially modified by AI. The digital_source_type and human_oversight fields together provide the information needed to determine whether a creative meets the disclosure threshold. The disclosure.required flag provides a direct signal for enforcement.
Platform mandates (Meta, Google, TikTok): Major platforms already require AI content labeling using IPTC-aligned metadata. AdCP’s provenance structure is directly compatible with these requirements because it uses the same underlying vocabulary.
AdCP does not determine which regulations apply to a given creative. It provides the structured metadata that allows each enforcement point to apply its own jurisdictional rules. The protocol carries the data; the enforcing party makes the compliance decision.
Verification flow
Implementation checklist
Buyers (brands and agencies)
Sellers (publishers and platforms)
Creative agents
Governance agents (AI detection)
Related
- AI provenance and disclosure — The provenance schema reference, digital source type enum, and inheritance model
- Creative Governance — Feature-based creative evaluation via
get_creative_features get_creative_features— Task reference for creative feature evaluation- Content Standards — Privacy-preserving brand suitability for publisher content
calibrate_content— Calibration task for content standards alignmentvalidate_content_delivery— Post-delivery content validation