Fahad Husain Azad
Gigamapping is a central method in systems oriented design (SOD) for engaging with complexity through multi-layered visual representations (Sevaldson, 2011, 2022). Despite its demonstrated value across public, private, and academic contexts, the method remains constrained by a significant facilitation bottleneck: effective gigamapping sessions typically require the presence of a practitioner trained in SOD methodology. Aguirre, Agudelo, and Romm (2017) have analysed design facilitation as an emerging practice, identifying a demanding repertoire of moves that few practitioners fully command. This paper proposes a conceptual framework for an AI agent that acts as a conversational facilitator, guiding participants who have no prior experience with gigamapping through the process and translating their inputs onto a collaborative digital canvas such as Miro. The agent is grounded in the academic literature of SOD, drawing on published works concerning gigamapping methodology, facilitation practice, systems thinking, and systemic communication (Romm et al., 2014; Sevaldson, 2018, 2022). Beyond general methodological knowledge, the agent can be tuned to reflect the praxeology of a particular systemic thinker, shaping how the facilitation unfolds in terms of language, priorities, and lines of inquiry. Through dialogue rather than instruction, the agent scaffolds the methodology: scoping the system boundary, identifying entities and actors, surfacing relationships, and prompting for layering and analysis. We position AI-mediated facilitation as a contribution to systemic design pluralism (RSD15 Call for Contributions, 2026). By decoupling the method from the requirement of a trained human facilitator, gigamapping becomes accessible to new disciplines, communities, and organisational contexts. The paper draws on recent RSD contributions addressing pedagogical entry points to systemic thinking (Fenlon, 2026; Maiorana, 2026), pluriversal systems practice (Udoewa & Dudani, 2026a), and AI applications within systemic design (Sund & Tarp, 2026), situating the proposed framework within the current trajectory of the field. An interaction model describing the agent’s behaviour across five facilitation phases is presented, alongside design considerations addressing the tension between structured scaffolding and emergent sensemaking, spatial reasoning limitations, the relational dimensions of facilitation, methodological fidelity, and reflexivity, together with a path towards empirical validation. The contribution is exploratory: the paper asks what an AI agent for gigamapping could be and what its introduction would mean for systems oriented design as a methodology, rather than reporting an implemented system.
Keywords: gigamapping, AI facilitation, systems oriented design, non-expert participation, collaborative canvas, praxeology