ABSTRACTA growing concern about the shrinking size of the U.S. Navy budget and the pool from which selections will be made to “man” U. S. Navy shipboard systems has led to investigations on achieving improvements in affordability and operational effectiveness. One such investigation has resulted in the development of the Standard Monitoring and Control System (SMCS), a modular, open architecture control system which includes the control system components for propulsion, electric plant, auxiliaries, and damage control. The first major technology upgrade to SMCS will entail the insertion of Artificial Intelligence (AI) technologies into HM&E monitoring and control applications. The Intelligent Machinery Control Integration Task (IMCI) was established to provide a structural approach for this major technology upgrade. As part of the first phase of IMCI, an identification of intelligent control requirements, an assessment of AI technologies, and a survey of intelligent control applications were performed. This paper lists those HM&E‐related shipboard operational requirements from which intelligent machinery control requirements will be identified. Also, there is an initial assessment of AI‐related reasoning and the following AI technologies, knowledge‐based systems, fuzzy logic, neural nets, and genetic algorithms. The survey provided some insight into applying AI technologies to SMCS shipboard operational requirements.