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Abstract Model‐based systems engineering (MBSE) is rapidly gaining popularity among U.S. industries. Though industry practitioners and academic researchers have identified several advantages in transitioning to MBSE, several adoption challenges of MBSE in industries, such as insufficient tool knowledge, lack of skilled personnel, and resistance in organizations toward a shift to MBSE, are observed. Attesting to the challenges in industry adoption of MBSE, a previous research study by the authors characterized the adoption challenges as tools‐based, knowledge‐based, cultural, political, and cost‐related, and customer understanding and acceptance of MBSE practices. This study is motivated to explore further and address the challenge of low MBSE tool knowledge and lack of skilled personnel with MBSE knowledge for industry adoption. This paper presents a two‐phased research approach framed by an overarching question of the extent to which the MBSE academic curriculum is aligned with industry workforce requirements. In Phase 1 of the study, we survey industry professionals from Defense, Aerospace, Automotive, and other industry clusters to identify MBSE tools, languages, and concepts preferred by industry professionals in a candidate for hire. This is followed by Phase 2 of the survey targeted at academic institutions with Systems and MBSE programs to analyze the extent to which MBSE curricula reflect industry workforce hiring requirements. Further, we also identify the challenges reported in academic institutions in training the Workforce on MBSE. The contributions of this paper are two‐fold: providing a pathway for academic institutions to align their curricula to MBSE industry workforce requirements and triggering discussion in the broader MBSE community to identify strategies for addressing MBSE adoption challenges and training future model‐based systems engineers. 

Model-Based Systems Engineering (MBSE) supports the development of complex systems through capturing, communicating, and managing system specifications with an emphasis on the use of modeling languages, tools, and methods. It is a well-known fact that varying levels of effort are required to implement MBSE in industries based on the complexity of the systems a given industry is associated with. This paper shares the results of a survey to industry professionals from Defense, Aerospace, Automotive, Consultancy, Software, and IT industry clusters. The research goal is to understand the current state of perception on what MBSE is and the use of MBSE among different industry clusters. The survey analysis includes a comparison of how MBSE is defined, advantages on the use of MBSE, project types, specific life cycle stage when MBSE is applied, and adoption challenges, as reported by the survey participants. The researchers also aim to trigger discussions in the MBSE community for identifying strategies to address MBSE related challenges tailored to a specific industry type.