A Roadmap for Model-Based Reviews

Despite widespread adoption of Model-Based Systems Engineering (MBSE), technical reviews remain largely document-centric and fail to exploit the full potential of models and computational support. This report presents a capability-based roadmap for Model-Based Reviews (MBR), ranging from traditional paper-based reviews (Pre-MB), through model-informed but artifact-driven practices (MBR 1.0), to in-model yet largely manual reviews (MBR 2.0), which dominate current practice. The limitations of these approaches are discussed, particularly their reliance on manual effort and unverified traceability. The report then articulates a forward-looking vision for computer-aided and AI-assisted reviews (MBR 3.0 and MBR 4.0), where validation rules, formal queries, ontologies, and collaborative intelligence allow review tasks to be partially delegated to machines, fundamentally changing the role of the human reviewer. Ultimately, the report argues for a transition from reviewing static artifacts to trusting validated review processes and infrastructures, enabling more scalable, consistent, and trustworthy reviews aligned with digital engineering principles.