Artificial intelligence (AI) has become a revolutionary tool in the automotive sector, specifically in quality management and issue identification. This article presents a systematic review of AI implementations whose target is to enhance production processes within Industry 4.0 and 5.0. The main methods analyzed are deep learning, artificial neural networks, and principal component analysis, which improve defect detection, process automation, and predictive maintenance. The manuscript emphasizes AI’s role in live auto part tracking, decreasing dependance on manual inspections, and boosting zero-defect manufacturing strategies. The findings indicate that AI quality control tools, like convolutional neural networks for computer vision inspections, considerably strengthen fault identification precision while reducing material scrap. Furthermore, AI allows proactive maintenance by predicting machine defects before they happen. The study points out the importance of incorporating AI solutions in actual manufacturing methods to ensure consistent adaptation to Industry 5.0 requirements. Future investigations should prioritize transparent AI approaches, cyber-physical system consolidation, and AI material enhancement for sustainable production. In general terms, AI is changing quality assurance in the automotive industry, improving efficiency, consistency, and long-term results.

The automotive industry is a key driver of global economic growth. However, traditional management approaches, relying on statistical tools and continuous improvement methodologies from the 1990s, lack the agility needed to address today’s complex challenges. This study proposes the Agile Viable Model (AVM), which integrates Viable System Model (VSM), Soft Systems Methodology (SSM), and Agile Methodologies to enhance responsiveness, resilience, and strategic decision-making in quality management. Applied to the Problem Resolution Process in Quality Control, the study identified low network connectivity, confirming that the system operates under a Supercritical Regime, limiting efficiency. Analyst involved and his leader emerged as critical nodes, with 68% of interactions being conflictual, revealing the need for improved communication and collaboration. To address these challenges, agile tools such as virtual boards, product logs, and daily meetings were integrated, optimizing process flexibility. CATWOE analysis facilitated the development of conceptual models aligned with organizational objectives. The Problem Resolution Process is vital both pre- and post-sale, influencing customer satisfaction and warranty costs. Strengthening connectivity and collaboration will lead to faster problem resolution, reduced costs, and enhanced reputation. The AVM offers a structured yet adaptive solution, improving operational efficiency and decision-making in automotive quality management.

Hoy en día México es considerado un líder en inversión automotriz a nivel mundial; sin embargo, a pesar de haber vivido años de éxito, se encuentra atravesando una rápida transformación. El futuro del país se presenta incierto, derivado de conflictos políticos (Thomson Reuters Mexico, 2024), de la presión de mantener los estándares de calidad que requieren sus produtos y la necesidad de reducir la complejidad de sus procesos, por lo que México se ve obligado a buscar respuestas eficientes que le permitan adaptarse a los cambios que se presentan. El presente artículo contiene una revisión de literatura acerca de lo puntos clave necesarios para la conformación de un modelo ágil, bajo la perspectiva del pensamiento sistémico. Este estudio presenta una revisión de la literatura que explora cómo el pensamiento sistémico y las metodologías ágiles han impactado a las empresas automotrices, demostrando sus bondades y hallazgos significativos, que demuestren que, al integrar estas herramientas, es posible mejorar los procesos, fomentar la innovación, adaptarse a un entorno cambiante, gestionar la complejidad organizacional y mejorar la toma de decisiones. Los resultados muestran que tanto el pensamiento sistémico y las metodologías ágiles ofrecen herramientas, enfoques y estrategias que abordan la complejidad existente dentro de la industria automotriz. Se halló que al complementar las metodologías del pensamiento sistémico con otras metodologías, es posible potencializar la sostenibilidad y la innovación, lo que permite a las empresas mantenerse competitivas en un entorno dinámico y tecnológicamente disruptivo.