What is AIGC detection?

AIGC detection is the attempt to determine whether a piece of content was generated by an AI model, using either statistical analysis of the artefact itself or provenance metadata attached at creation. The two approaches have very different reliability.

Statistical detectors infer generation from patterns — token predictability in text, frequency-domain artefacts or anatomical inconsistencies in images — and are unreliable enough that most serious deployments have been withdrawn or heavily caveated. OpenAI retired its own text classifier for low accuracy, and academic evaluations consistently find high false-positive rates, particularly against non-native English writing. Provenance approaches invert the problem: rather than detecting generation after the fact, C2PA Content Credentials attach a signed manifest at creation recording what tool produced an asset and what was done to it. This is cryptographically verifiable where it survives, though metadata is routinely stripped by social platforms and image pipelines. The practical position for a marketing team is that detection cannot be relied on either to prove or to disprove AI involvement, so compliance should rest on your own disclosure practice rather than on an expectation of being detected.