We recently performed a meta-analysis of AI use cases in Mexico’s manufacturing and logistics industries. As is the case globally, mature AI adoption is spreading faster in sectors like finance, e-commerce and entertainment media compared to in the supply chain industries. However, in Mexico’s case, there is a confluence of factors that highlight manufacturing and logistics as particularly fertile ground for industrial transformation.
As everywhere, Mexico’s manufacturing and logistics companies are heavy on highly-customized capital assets. These industries are inherently slower to adopt transformative technologies like artificial intelligence because they are reliant on OT– operational technology– even moreso than they are on pure-play IT, software, which is comparatively easy to edit and update, and on networked communications technologies, which are commodities when compared to manufacturing assembly lines and vehicles and warehousing equipment.
Indeed, if it is slower and more expensive to update the supply chain industries, there is also relatively more risk riding on the updates. Supply chains by nature require interoperability of technologies used by several distinct players. In Mexico’s case, further complexities are at play:
- highway security and other logistics continuity factors
- greater need to ensure water and electrical supply/resilience
- the multinational nature of the supply and distribution networks– the inputs, outputs, and their transit and financing are governable by multiple legal jurisdictions
The company Advanced Logistics Solutions in a recent blog post describes in detail 2025 as a period of accelerated U.S.-Mexico supply-chain integration driven by nearshoring, with opportunities centered on cost optimization, shorter transit times, and improved cross-border responsiveness. They highlight gains from digitalized logistics, automation of customs processes by both the US and Mexico, and expanding regional workforce capacity supporting advanced manufacturing and real-time supply-chain visibility. From our view at the NC office in Mexico, we see ongoing trade and security negotiations between Mexico and the US as ultimately a dance that will result in more consolidated bilateral, precision control of supply chain tracking and other data.
What does this mean in terms of advanced operational technology implementation? The rest of this blog post highlights 5 of the AI use cases we looked at in Mexico manufacturing and logistics. The goal is to provide some signposts in terms of technology systems that other adopters in Mexico will be looking to. The 5 companies are major players not just in Mexico but regionally and globally, including in the US. Their progress establishes performance baselines for Tier 1, Tier 2 and partnering and competing supplier in Mexico’s, which is also North America’s, supply chain ecosystem.
Cemex – global cement company
Cemex uses AI for predictive maintenance, kiln process optimization, energy-efficiency analytics, and digital-twin simulations across cement production lines. These systems operate in major plants in Monterrey, Hidalgo, and Puebla, with continuous data collection from thousands of sensors and multi-site integration of remote monitoring via the MARIA platform. Technology partners include Microsoft Azure Machine Learning, IoT Edge, EPAM NEORIS, and internal R&D teams. For further reading: CEMEX, “Improving Cement Production Through Artificial Intelligence.” (2021)
Grupo Bimbo – global baked goods company
Grupo Bimbo applies AI for demand forecasting, dynamic route optimization, shelf analytics using computer vision, equipment maintenance prediction, and digital-twin modeling of distribution centers. Its deployment spans nationwide production and distribution networks, with over 200 automated processes and more than 1,000 trained citizen developers supported through its analytics hubs in Mexico City and Monterrey. Technology partners include the integrator Nubity, AWS Bedrock, SageMaker, Microsoft Power Platform, Oracle Fusion Cloud, SAP S/4HANA, IBP, Blue Yonder, and Manhattan TMS/WMS. For further reading in English, from Oracle, “Grupo Bimbo kneads Oracle Fusion Cloud apps into its growth strategy” (2025)
Nemak – global metals manufacturing
Nemak integrates machine learning into its casting and machining operations to optimize parameters, reduce defects, schedule predictive maintenance, and simulate processes with digital twins. These capabilities are active across 15 plants, supported by a global rollout from its Monterrey R&D center and a 400-person citizen-developer program. Technology partners include Microsoft Azure IoT and ML, Siemens, Dassault Systèmes DELMIA, Emilabs, Nemak NORIS, Your IT Consulting, iAlestra-NXT, and Tec de Monterrey. See this video in English hosted by Nemak on their NORIS platform (2025).
Volkswagen de México – global automotive manufacturing
Volkswagen de México employs AI in predictive maintenance, production analytics, robot-driven assembly, and real-time quality inspection via cobot systems. Its Puebla and Silao plants are integrated into the global Volkswagen Industrial Cloud, managing over 200 robots and 20 PLCs under VASS standards and supporting vehicle production volumes exceeding 400,000 units per year. Technology partners include AWS, Microsoft Cloud for Manufacturing, Dassault Systèmes, Dominion Global, and Diro Automation. See Dominion Global, the integrator’s, case study for VW Mexico’s automated welding described in English.
FEMSA / Solistica (Traxión Group) – world’s largest Coca-Cola bottler and affiliated LATAM-wide distribution operations
Solistica uses AI to optimize transport planning, forecast delivery disruptions, detect operational threats, and simulate logistics flows in multimodal freight networks. The system covers 6,200 vehicles, 25,000 employees, and more than 9,000 connected devices across Mexico, Colombia, and Brazil, with centralized control-tower oversight in Mexico City and Monterrey. Technology partners include Oracle Transportation Management, Microsoft Sentinel and Defender, Bendix ADAS sensors, internal Distribución Digital 1.0 platform, SAP S/4HANA (ERP integration), Databricks, Solistica, Servinformación, FEMSA Digital, and Traxión Group.
Estafeta – national logistics carrier and forwarder
Estafeta has developed an AI-driven digital twin of its parcel-distribution network to improve fleet utilization, hub planning, and investment decisions. The system integrates predictive-demand forecasting, dynamic route optimization, anomaly detection, and real-time visibility dashboards across more than 130 logistics facilities nationwide. The model uses agent-based and discrete-event simulation to balance mode, cost, and service-level priorities for both air and ground operations. Technology partners include AnyLogic, Microsoft Azure, and Estafeta’s internal analytics and operations teams. For an English case study, see Anylogic, “Developing a Logistics Digital Twin for a Parcel Distribution Network in Mexico.” (2022)