20.500.12556/RUL-178027 The role of AI agents in construction project management The integration of Large Language Models (LLMs) into Artificial Intelligence (AI) agents presents new opportunities for enhancing construction project management through improved collaboration, reasoning, and workflow automation. This paper investigates how LLM-powered AI agents can support complex construction tasks such as scheduling, resource allocation, risk assessment, and information coordination. We conduct a structured review of recent literature across construction informatics, AI-driven project management, and agent-based systems to identify trends, capabilities, and limitations. Our findings show that while AI agents offer strong potential to assist project teams with dynamic decision-making and routine task automation, their effectiveness is limited by data quality, domain adaptation, and the stochastic nature of LLMs. These insights are significant for researchers and practitioners aiming to introduce AI agents into real-world construction workflows, where reliability, explainability, and human oversight are essential. The paper highlights the need for further exploration of Human-in-the-Loop (HITL) designs and calls for standardisation of agent capabilities to ensure safe, transparent, and practical deployment in the construction industry. Vključitev velikih jezikovnih modelov (VJM) v agente umetne inteligence (UI) ponuja nove priložnosti za izboljšanje upravljanja gradbenih projektov z izboljšanim sodelovanjem, razumevanjem in avtomatizacijo delovnih tokov. Ta prispevek preučuje, kako lahko agenti UI, ki jih poganja VJM, podpirajo kompleksne gradbene naloge, kot so načrtovanje, dodeljevanje virov, ocena tveganj in usklajevanje informacij. Izvedli smo strukturiran pregled najnovejše literature s področja gradbene informatike, upravljanja projektov na podlagi UI in sistemov na podlagi agentov, da bi identificirali trende, zmogljivosti in omejitve. Naše ugotovitve kažejo, da agenti UI sicer ponujajo velik potencial za pomoč projektnim delovnim skupinam pri dinamičnem sprejemanju odločitev in avtomatizaciji rutinskih nalog, vendar je njihova učinkovitost omejena zaradi kakovosti podatkov, prilagajanja domen in stohastične narave VJM. Ti vpogledi so pomembni za raziskovalce in st rokovnjake, ki želijo agente UI uvesti v realne gradbene delovne tokove, kjer so zanesljivost, razložljivost in človeški nadzor bistvenega pomena. Članek poudarja potrebo po nadaljnjem raziskovanju zasnov načela človek v zanki (angl. Human-in-the-Loop, HITL) in poziva k standardizaciji zmogljivosti agentov, da se zagotovi varna, pregledna in praktična uporaba v gradbeni industriji. AI agents LLM project management construction workflows construction informatics agenti UI veliki jezikovni modeli upravljanje projektov gradbeni delovni tokovi gradbena informatika true false true Angleški jezik Slovenski jezik Članek v reviji 2026-01-16 10:59:44 2026-01-16 10:59:51 2026-01-17 04:38:20 0000-00-00 00:00:00 2025 0 0 Str. 147-154 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.8:624 10.18154/RWTH-CONV-254903 262894083 262884355 Brelih...-The_role_of_AI_agents_in_construction_project_management.pdf Brelih...-The_role_of_AI_agents_in_construction_project_management.pdf 1 1BEFACFD33FCF5D42D7527BA5C449E3D a9dd4c7b2b6a519396d1db39bb4d9a05f1561f4a35764ffebfce5b2f13f3f030 9f85576a-f2c2-11f0-bf92-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=225533 https://publications.rwth-aachen.de/record/1014054/files/1014054.pdf 1 12651e02-f2c2-11f0-bf92-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=225532 Fakulteta za gradbeništvo in geodezijo 0 0 0