  High availability of data is responsible for the current trends in Artificial
Intelligence (AI) and Machine Learning (ML). However, high-grade datasets are
reluctantly shared between actors because of lacking trust and fear of losing
control. Provenance tracing systems are a possible measure to build trust by
improving transparency. Especially the tracing of AI assets along complete AI
value chains bears various challenges such as trust, privacy, confidentiality,
traceability, and fair remuneration. In this paper we design a graph-based
provenance model for AI assets and their relations within an AI value chain.
Moreover, we propose a protocol to exchange AI assets securely to selected
parties. The provenance model and exchange protocol are then combined and
implemented as a smart contract on a permission-less blockchain. We show how
the smart contract enables the tracing of AI assets in an existing industry use
case while solving all challenges. Consequently, our smart contract helps to
increase traceability and transparency, encourages trust between actors and
thus fosters collaboration between them.
