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Artificial intelligence (AI) research and market have grown rapidly in the last few years and this trend is expected to continue with many potential advancements and innovations in this field. One of the emerging AI research directions is Distributed Artificial Intelligence (DAI). It has been motivated by the technological advancements in communication, networking, and hardware together with the nature of data being generated from connected, distributed, and diverse objects. DAI is expected to create a fertile environment for innovative, advanced, robust, and scalable approaches for AI supporting the vision of smart societies. In this paper, we explore state of the art on DAI and identify the opportunities and challenges of provisioning of Distributed AI as a Service (DAI-aaS). We provide taxonomy and comprehensive review that covers various aspects of DAI including AI workflow, distribution paradigms, supporting infrastructure, management techniques, and applications. Based on the gained insights from the conducted review, we propose Imtidad, a framework for the provisioning of DAIaaS over the cloud, fog, and edge layers. We refine this framework and propose the Imtidad software Reference Architecture (RA) for designing and deploying DAI services. In addition, we extend the framework and developed a future networking infrastructure transformation framework as it is one of the main enablers for DAI. This framework and RA can be used as guidance facilitating the transition to the future DAI where DAI is decoupled from the design and development of smart applications. This paper, including the proposed framework, RA, taxonomy, and …