SAN PEDRO GARZA GARCÍA, NL – Artificial intelligence (AI), automation, and real-time visibility are beginning to change how logistics companies manage their operations. However, the challenge lies not only in incorporating technology, but also in identifying where it can generate value and connect the systems of the various participants in the supply chain , agreed industry specialists at the panel “AI, Automation, and Total Visibility: The Technological Future of Logistics ,” held at ETYL MTY 2026 by Grupo T21 .
Francisco Fabila, CEO of Ferrovalle , explained that capital investments are not focused solely on tracks, cranes, locomotives, or yards, but also on optimization software and AI . He said that the combination of infrastructure and continuous process improvement allows for increased capacity and a higher level of service.
However, he cautioned that automating one aspect of the operation can simply shift the bottleneck to another process. During his presentation, he cited as an example how the implementation of archways reduced truck entry time to their intermodal terminal from eight to ten minutes at the gate to just seven seconds.
According to Fabila, the terminal processes between 1,500 and 1,800 trucks daily, so the reduction in access times represented a relevant operational improvement without the need to physically expand the infrastructure .
“It’s an explosion of benefits for the user, for the operator, for the terminal, even for society; I mean, not having a single line outside the terminal affecting traffic again is crazy,” he asserted.
According to the expert, the first step is to understand the processes and identify inefficiencies, because otherwise, the investment in technology can result in an expensive solution that doesn’t generate proportional benefits for the client. “You’ll likely end up with a white elephant that cost a fortune,” he emphasized.
Visibility to anticipate risks
Another topic addressed in the panel, moderated by Karolina Pulido, CEO of GIEicom , was the availability of real-time information and its usefulness for decision-making.
Fabila explained that Ferrovalle has enabled visibility tools for its main intermodal clients, allowing them to access information about their containers, dwell times, and the duration of entry and exit processes. This data enables them to evaluate the service, manage inventory, and detect delays.
For his part, Sergio Islas, CEO of SIEM Business , pointed out that one of the main obstacles is the lack of interoperability between suppliers, carriers, customs agents, clients and authorities .
He explained that SIEM Business has used artificial intelligence to collect, recognize, and sort documents in one location, with the purpose of facilitating the work of the teams responsible for the operation.
Furthermore, he considered it necessary to improve the quality and standardization of the data , as well as to update the customs risk analysis mechanisms to make reviews more efficient and avoid unnecessary delays.
Training was another key topic of discussion. Participants agreed that resistance to change can hinder technological projects , especially when modifying processes that have been carried out the same way for years.
Luis Parra, Regional Sales Manager at Motive , highlighted the importance of bringing new tools closer to everyday activities and supporting their implementation to facilitate the adoption of technology , which should solve specific problems and not become an isolated tool from the operation.
“I have this, with this information that is mine, real, and what is coming in the future according to my projections, I can make decisions,” he stated.
According to Gartner data , cited by Karolina Pulido, 60% of digital adoption efforts in supply chains will not deliver the promised value by 2028 due to insufficient investment in training and skills development. This data reinforces the importance of incorporating staff training from the outset of projects.
The panelists also noted that AI needs structured and consistent information to function properly. Before deploying more complex models, companies should review where their data resides, unify and standardize it , and assess the recurring costs of infrastructure, storage, and technology maintenance.
The evolution toward more autonomous operations will also depend on the ability to connect systems and equipment. The panel discussed how an intermodal platform must be able to exchange information with rail systems, port terminals, shipping companies, and other members of the supply chain.
Warehouse automation will be part of this transformation. Pulido indicated, according to a Gartner study, that by 2030, 50% of new warehouses in developed markets will be designed with a robot-centric approach, requiring platforms capable of coordinating different types of automated equipment .
“A platform will be needed that can orchestrate all those robots so that they can obviously be autonomous,” he stated.
These cases show the potential of the technology, although its application in Mexico must respond to the conditions of each operation and a measurable return on investment.
The panel emphasized that artificial intelligence should not be adopted simply because it’s trendy. The starting point is to identify an operational problem, assess the quality of available information, and determine which tool can solve it. With clear processes, trained personnel, and interoperable systems, technology can contribute to more efficient, transparent logistics that are better equipped to anticipate risks .
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