Construction
As we enter 2026, major public procurement agencies in Korea are shifting their approach to AI adoption. Moving beyond simple pilot projects or declarative roadmaps, this trend is taking concrete form through organizational restructuring, the allocation of dedicated personnel, and on-site implementation.
The Korea Land and Housing Corporation (LH) established an AI Innovation Center (TFT) in August of last year. A dedicated team of nine members is tasked with monitoring the status of internal AI initiatives and overseeing and managing key projects.
Recently, the company has launched a full-scale “LH AI Transformation (AX) Roadmap Development Project,” analyzing all business processes—including project planning, design, construction, maintenance, housing welfare, and management—to identify potential applications for generative AI. This systematic approach includes designing a KPI framework and establishing a portfolio of short-term and mid-to-long-term tasks.
The Korea Expressway Corporation uses vehicle-mounted video analysis systems to detect road surface damage in real time while driving and employs tunnel scanners to inspect the exteriors of highway tunnels without closing the route. From automatically identifying improperly loaded trucks to detecting hazards at construction sites using AI-powered CCTV, the corporation is deploying AI across all field operations.
The Korea National Railroad Corporation is upgrading the Railway Facility Integrated Information System (RAFIS), established in 2024, with AI. It is building a system that analyzes facility maintenance history data using AI to determine the optimal timing for repairs, while simultaneously pursuing integration with GIS databases and mobile systems.
The Korea Water Resources Corporation is expanding its AI water treatment plant model nationwide to utilize water resource data—amounting to approximately 7.4 billion records per day—as an AI resource. Following its initial application at the Hwaseong Water Treatment Plant in 2022, the corporation recently partnered with the city of Busan to launch a pilot project expanding the AI water management model to local water supply systems.
There is a notable commonality in these trends. All four organizations are focusing on the task of converting unstructured data generated in the field into structured information.
Road surface conditions, tunnel exterior scan results, railway facility maintenance histories, and water treatment process data—all of these are collected on-site but have been left unused because they could not be organized and analyzed in a timely manner using conventional methods.
What AI is changing is not mere automation, but the speed at which field data is transformed into actionable information. And the starting point for that transformation is 'field documentation.'
Digitalpresso is developing technology that automatically converts unstructured data (photos, audio, and video) from construction sites into structured documents. We are aligned with the AX (AI-driven) initiatives of public procurement agencies.
