An operational layer, not a standalone product, shows how agentic AI reshapes facilities management in Gulf airports and ports

The agentic AI is no longer just an isolated software concept confined to research labs; it has begun to embed itself as an actual operational layer reshaping facilities and large-asset management across the Gulf region. This shift was the focus of discussion at the Clean Middle East conference in Dubai, where Danish Bukhari, project manager at High Tech AI, the technology arm of FARANK Group, explained that introducing agent models into the facilities-management sector does not arrive as a standalone product but as an integrated layer spanning daily operations. The argument rests on FARANK’s roughly half-century of operational experience in smart, sustainable facilities management within the UAE and Saudi Arabia, where its digital platforms serve aviation, healthcare, government and commercial facilities.

The field deployment of smart agents has moved beyond pre-programmed automation, heading toward moment-by-moment adaptation to live site requirements. At Dubai airports, specialized service robots operate alongside human staff at multiple locations, but their deployment is no longer tied to routine work schedules; it now follows passenger flow, instantaneous crowd density and aircraft movement timetables.Shifting from rigid shift rosters to automated and human resource allocation based on actual traffic density embodies the role of independent agents in reading the operational environment and making field decisions.

On the critical infrastructure front, agentic AI has expanded to include asset inspection and verification in ports and logistics facilities. In an operational trial with one of the port operators in the Gulf Cooperation Council (GCC) countries, the Kondtek solution analyzed visual evidence for more than 16,000 physical assets, and the system succeeded in detecting faults and gaps that had not been recorded in any prior paper or electronic log, including a live alarm active on a fire-suppression pump control panel. The agent-based system was also deployed for another Gulf client, covering 40 operational processes linked to quality and safety compliance, from receiving service requests and assigning them to maintenance providers, to continuously auditing service-level agreements and performance indicators.

The system rests on a clear operational equation: AI organizes and structures the evidence, qualified staff verify and approve, while operational and legal responsibility remains with the human element.This precise role delineation prevents leaving sensitive infrastructure to closed-algorithm decisions and confines the agent’s role to data collection, image analysis and anomaly filtering to enable technicians to intervene precisely.

What changes in practice for anyone managing a facility or utilities network in the Gulf, Egypt or the Levant is the shift from silent periodic inspections to asset management based on real-time evidence. In cost and decision terms, the detection of a fire-pump alarm at a port demonstrates that automated visual monitoring protects against large operational losses that traditional records cannot avert, tilting investment toward visual inference layers rather than legacy scheduling software. In terms of skills, the need for manual data entry and schedule tracking recedes in favor of engineering verification and auditing of the agent’s outputs, compelling operations managers to retrain their field teams to work in a shared environment that blends autonomous robots with human staff.