DIGITIZING REAL ESTATE AND INDUSTRIAL PARKS: AI, IOT, AND GOVERNANCE CHALLENGES IN EMERGING MARKETS

Abstract

Digitizing real estate and multi-tenant industrial parks in emerging markets requires more than sensors and software; It demands interoperable architectures, enforceable data rights, and operational capacity. This systematic literature review maps the intersection of AI, IoT, and governance across buildings, shared utilities, and park operations. Following PRISMA, we searched scholarly databases (2010 to 2023), screened for deployment and estate-relevant evidence, and synthesized mixed findings. In total, 115 peer reviewed studies met the inclusion criteria. Evidence converges on five capabilities that predict success: sustained observability via sensing and tagging; actionable interoperability via open protocols and semantic models; effective controllability using edge-first, cloud-connected designs; governance readiness clarifying ownership, access, retention, and provenance; and organizational uptake through training and workflow integration. Across operational optimization studies, energy intensity commonly falls by low double digits while comfort is maintained; reliability work reports material reductions in unplanned downtime and faster leak or fault localization in shared utilities. Estates that implement semantic tagging and layered interoperability shorten time to analytics and close a larger share of detected issues; edge analytics and network segmentation improve data completeness and limit incident blast radius under weak power and backhaul. Financing and institutional choices matter: performance based and service models, together with outcome based procurement, help pilots scale into durable programs. We conclude with a maturity model, a governance checkpoint framework, and a KPI palette to link technical decisions to verifiable outcomes in real world estates. Implications for policymakers and operators are discussed, with emphasis on replicability and measurement and verification.