The edge AI reference architecture requires a technical system overview that provides a generic approach applicable to multiple industrial sectors, rather than one developed for a single industry (industrial-sector agnostic). A layered architecture that aligns with the edge AI technology stack should be considered. The layers should include hardware, hardware accelerators, interfaces, edge AI frameworks, software, edge AI models, algorithms, data, and applications. It can be connected to an IoT architecture, which includes layers such as sensors, connectivity, edge processing, communication, memory, storage, and edge computing. The three-dimensional architecture should consist of, in the second dimension, edge AI system quality properties (related to dependability, security, reliability, maintainability, and trustworthiness), and, in the third dimension, performance properties describing the edge AI system. The edge AI architecture can then be unfolded for each use case, and all three sides of the architecture can be mapped to the elements or components of edge AI systems, including hardware, edge AI frameworks, and edge AI models.