Dijital Tuğla - Bölüm 21: Hak Talebi Yönetiminde ve İhtilafların Giderilmesinde Yapay Zekanın Rolü

26 Aug 2025 · 32 min
31:44

In this episode of the Dijital Tuğla podcast, hosts Cem Kafadar and Haluk Eginat discuss how artificial intelligence is transforming claim management and dispute resolution in the construction industry. They start by describing AI’s ability to detect potential claims early – monitoring daily site data, weather feeds, and schedule deviations to issue instant notifications and avoid missed claim deadlines. The conversation then moves to AI‑driven evidence aggregation, where machine‑learning tools automatically extract, tag, and cross‑reference emails, RFIs, photos, videos, and sensor data to build comprehensive claim dossiers. They discuss the use of large language models (LLMs) to read and map contract clauses (e.g., FIDIC, NEC, bespoke agreements) such as “reasonable efforts,” highlighting how AI can surface ambiguous terms and suggest draft language or risk mitigations. The hosts explain how AI quantifies delay and acceleration costs by applying industry models like measured‑mile, MCA, and IBEW, pulling from cost databases and invoices. They present proactive risk dashboards that combine weather, supply‑chain, and historical claim data to generate risk scores and supplier performance rankings, turning AI from a reactive tool into a preventive one. A catalog of concrete tools – Alice, Doxel, OpenSpace, Buildats, Procore AI dashboards, SmartVit, Lex Machina, Ross Intelligence – is provided, illustrating the current ecosystem. Ethical and legal challenges are examined, including bias, manipulation, hallucination, transparency of training data, and the open question of liability when AI makes erroneous claim decisions. Throughout, the hosts stress that AI cannot assess human intent, goodwill, or nuanced contractual interpretation, so human judgment remains essential. They cite Oliver Wyman’s estimate that generative AI could save 20‑40 % of claim‑related effort, but note methodological debates and the need for regulatory frameworks. The episode concludes that AI will continue to act as a powerful assistant, accelerating data‑driven insights while humans retain the final decision‑making authority.

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