INTELLIGENT AGENTS AND LEAN LOGISTICS FOR THE IMPROVEMENT OF MANAGEMENT PROCESSES IN TRANSPORTATION COMPANIES

Transportation companies face significant operational challenges including delivery delays, prolonged waiting times, inefficient resource utilization, and low process standardization, which negatively impact service quality and competitiveness. This research proposes the integration of intelligent agents with Lean Logistics principles to improve management processes in transportation firms, with a focus on small and medium-sized enterprises in Hidalgo, Mexico. A mixed-methods approach was employed, combining a systematic literature review following the PRISMA 2020 protocol (20 key articles from 2016-2026), a diagnostic survey of 100 users using a 5-point Likert scale, Value Stream Mapping (VSM), and the design of an intelligent operational management agent implemented in n8n with OpenAI language models. Survey results revealed that 26% of users identified delays as the main problem and 20% highlighted high waiting times, with only 42% reporting satisfaction or high satisfaction. The proposed agent automates data validation, Lean waste detection (waiting, unnecessary transport, overprocessing, etc.), resource optimization, route analysis, risk monitoring, KPI calculation, and automatic generation of actionable recommendations and HTML reports. Complementary standardized control formats (F-01 to F-08) support process standardization under the PDCA cycle. Expected outcomes include reduced planning times, lower operational waste, optimized resource allocation, and improved service consistency. The study provides a practical, scalable methodological framework for digital transformation in regional transportation companies.