Artificial Intelligence (AI) provides a unique opportunity to enhance and augment Model-Based / Systems Engineering (SE and MBSE). Through a systematic literature review, this paper explores current and potential uses of AI in SE across the V-model and analyses barriers of AI adoption in SE/MBSE. The results show that despite a significant potential of AI to enhance SE, several barriers exist, such as unavailability of data, trust and explainability issues, and technical limitations of AI systems. Based on the findings, this paper suggests future research directions, focussing on increasing the availability of high-quality datasets, integrating explainable AI techniques into SE, investigating Human-AI team dynamics, exploring MBSE roles for facilitating AI and how to address technical limitations of current AI models.
