Design is a complex cognitive activity that can introduce distinct forms of stress. Despite growing attention to stress in design contexts, existing research remains fragmented and lacks a unified conceptual framework. This study conducts a scoping review, using an interpretive metasynthesis approach, to integrate existing knowledge and conceptualize design stress as a distinct, process-embedded phenomenon. Unlike occupational stress or cognitive load, design stress emerges within iterative, ill-structured and cognitively demanding design activities. Following PRISMA-ScR guidelines, relevant studies were identified in major academic databases. The study combines scientometric analysis using VOSviewer with qualitative approaches, including grounded theory and content analysis, to map and interpret the field’s structure. Findings identify “mental stress” as the dominant keyword, with studies clustering into three areas: design-related harm, stress in design and their bidirectional relationship. Consequently, the novel topic of “design stress” is identified and introduced. Design stress manifests in multiple forms and across levels, with significant and diverse impacts. To identify, analyze and manage stress while enhancing productivity, a multifaceted approach is required. These findings offer valuable insights for professionals addressing stress in design environments. By establishing a structured framework for future research, the study provides strategies to improve performance, optimize creativity and reduce cognitive burdens throughout the design process.

As AI continues to evolve and demonstrate new design capabilities, there is an opportunity to explore its integration with design at a process level. While recent studies have examined the creative potential of AI-based design tools and their use in enhancing individual tasks, there remains an opportunity to understand how the design process might evolve at the end-to-end design workflow macro scale through study of practice-based design. We follow a revised design process workflow, alongside an exemplar implementation using interactive digital workspaces, establishing an applied approach for viewing the design process as a dialogue between humans and AI. Data were collected from three-day continuing education workshops with industry professionals, providing an empirical dataset that offers longitudinal insights into how the proposed workflow performs in real-world contexts. The approach is evaluated through method-level comparisons and a longitudinal study providing process-level evaluation between human-only and AI-augmented workshop flows, comprising four workshops and 20 teams. Two methods, affinity clustering and mind mapping, were sampled for direct comparison. Participants preferred the AI-augmented workflow, and method-level comparisons indicate comparable quality. The primary contribution is a practice-based, longitudinal account of integrating AI across an end-to-end professional design workflow.