Space AI Readiness as a Proto-Institution: Governing, Operating, and Exiting AI in Physical Spaces

DOI: https://doi.org/10.62517/jike.202604133

Author(s)

Yingdong Zhu1, Wen, Xu2, Xue, Wang1, Xin, Wang1,*

Affiliation(s)

1School of Marxism, Zhejiang Shuren University, Hangzhou, China 2OPENVIBE Ltd, Singapore *Corresponding Author

Abstract

As AI migrates from screen-based applications into buildings, campuses, and commercial venues, a consistent failure mode emerges: spaces become “AI-enabled” as a display layer (dashboards, assistants, smart panels) while remaining operationally fragile. Under model drift, vendor turnover, or contested accountability, AI shifts from a productivity promise to a new source of friction and downtime. This paper introduces Space AI Readiness, defined as the durable socio-technical preconditions that allow AI to participate in everyday production, coordination, and operations within a physical space without eroding governance, responsibility, or service continuity. Building on Science and Technology Studies (STS) and Umberto Eco’s limits of interpretation, we conceptualize readiness along two coupled dimensions: (1) governance/interpretation, where AI outputs must be contestable, traceable, and ultimately subordinated to accountable human judgment; and (2) operational infrastructure, where AI must be substitutable and exitable so the space remains runnable under human takeover and across vendor or model changes. We formalize this dual-axis construct as an evaluative framework and operationalize it through an L0–L5 readiness ladder adapted from autonomy discourse, clarifying progression from conventional operations to adaptive, semi-autonomous regimes. We further theorize Space AI Readiness as a proto-institution—a shared rule-set and evidence regime that coordinates owners, operators, tenants, service providers, and visitors by reducing interpretive disputes and decision costs. Finally, we translate the framework into audit-ready deliverables (task-based operating blueprints, RACI/WBS packages, evidence chains, data-and-licensing matrices, and exit tests) that enable contracts to bind renovation, operation, and AI governance into a verifiable loop. the paper offers a rigorous vocabulary and an implementation grammar that shifts debate from “AI adoption” to governable operation in the built environment.

Keywords

Space AI Readiness; Built Environment; Socio-Technical Governance; Auditability; Contestability; Operational Continuity; Vendor Exit; Proto-Institutions

References

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