Mexico's busiest warehouses may not be the right first sites for mobile robots

Up to 33.57%. That's how much less time certain picking tasks took when workers and mobile robots split the job, according to a study that tracked more than two million visits to storage locations. The same study carries the catch: product weight, travel distance and picking density all changed how much of that gain actually showed up.

That caveat is the core of a November 5 analysis by Romina Miranda at Mexico Business News, which asks a question every Mexican logistics network faces once e-commerce growth, wider SKU ranges and tighter delivery windows put autonomous mobile robots (AMRs) on the table. Robots in every building are rarely the plan. The decision is which distribution center goes first, and how to prove the case there before the capital request reaches the CFO.

Walking distance sets the payback

AMRs earn their money in picking by cutting the distance workers cover to find and move product. They use sensors, autonomous navigation and fleet coordination software to carry goods and work alongside pickers. The value depends on how much walking a building has to give up.

Mexico Business News lays out the first screen: operations where picking takes a lot of time and travel. Many SKUs, long routes and frequent orders all point that way. Order size, pick density and the building's physical condition come next, and the analysis cites the research in The International Journal of Logistics Management to make the point that a higher order count doesn't guarantee the best return.

The analysis also points to a DHL technical guide on autonomous warehouse vehicles, which names the scenarios where assisted-picking robots are especially relevant: large facilities with numerous SKUs and high volumes of order lines processed. Mexico Business News treats those traits as selection criteria, not universal profitability thresholds. Note that the guide counts order lines rather than orders. The study's own unit was the visit to a storage location, and lines sit closer to that unit than raw order counts do, which suggests why the busiest building by orders may not be the busiest by picking work.

Robots earn their keep by removing walking, so the strongest first site is the building where pickers walk farthest per pick, and that can be a different building from the one shipping the most orders.

DHL Supply Chain offers a working version of that discipline. El Economista reported in December 2025 that the company was widening its robotics strategy in Mexico with systems from Robust.AI. Sally Miller, then DHL Supply Chain's chief digital technology officer, described assessing each facility on its own before adding robots, weighing workforce size, expected productivity and financial return. DHL also pointed to mobile systems as more flexible than some fixed automation when volumes or layouts change.

The same logic shows up in inventory planning. Writing in Logistics Management on November 2, St. Onge Co. senior project engineer Brian Streu argued that applying one policy across a mixed product portfolio tends to leave too much stock of low-value items and too little of critical SKUs. Applying one automation plan across a mixed network carries a similar risk of putting capital where it does the least.

Streu frames the underlying tension as three competing priorities: maintaining high service levels, minimizing inventory investment and controlling operating costs. A robot rollout faces its own version of that balance. Picking the first site by travel and density rather than by order volume is one way to keep capital spending from outrunning the service and cost gains it is supposed to buy.

Cuautitlán Izcalli as the reference site

Mexico already has a documented case. In March 2024, GEODIS announced it had deployed Locus Robotics' Locus Origin robots at a distribution center in Cuautitlán Izcalli, State of Mexico, handling e-commerce and retail fulfillment for an international apparel brand. It was GEODIS' first Latin American operation to use the technology, with robots working across a three-level mezzanine and the LocusOne platform assigning tasks and directing pick moves.

The mezzanine detail matters most to anyone with an older building. It shows AMRs can be fitted into an existing multi-level Mexican facility without a greenfield build. Implementation cost and payback period were not disclosed, so the site shows the deployment can be done in an existing building but can't serve as a financial benchmark.

Two kinds of mobile robot, two different jobs

Choosing a site and choosing a robot type are linked decisions. Swisslog, in an October 6 explainer by Lena Maria Priesner, separates shelf-to-person robots, which bring storage racks to fixed picking stations and usually run inside fenced zones, from transport AMRs, which move pallets and containers across open floors among people and forklifts. Shelf-to-person systems suit broad, fast-changing SKU mixes and buildings where height or layout rules out high-bay storage. Adding racks raises storage capacity and adding robots raises throughput, and each can be expanded independently.

Swisslog adds that bringing goods to ergonomically designed stations improves picking accuracy and makes the work more comfortable for staff, and it names omnichannel fulfillment, e-commerce distribution and spare parts warehousing as natural fits. For a Mexican operator whose pain point is pickers covering long routes through a wide SKU range, that is the category aimed squarely at the walking problem.

Transport AMRs handle a different flow: receiving to storage, storage to production or buffer, buffer to shipping. Swisslog notes they navigate with laser-based SLAM and digital maps rather than floor guides, so routes can be redrawn in software as layouts shift, which matches the flexibility argument DHL made. The company frames the two as complementary, able to automate the flow from inbound to shipping with little or no conveyor spend.

The comparison Swisslog draws with AGVs is the practical one. Because transport AMRs rely on onboard sensors rather than fixed guidance, the company says they can be deployed more rapidly and with minimal disruption. Their safety scanners, often backed by 3D cameras, slow or stop the vehicle when a person or obstacle appears. Typical jobs include production line supply, transport between warehouse zones, cross-docking and picking support, across sectors from 3PL logistics and FMCG to food and beverage, electronics and pharmaceuticals.

Swisslog's own headline answer to which robot belongs in a warehouse is that it might be both, with the right mix depending on where the material flow most needs flexibility. That maps neatly onto site selection: a building whose problem is picking travel points one way, while a building whose problem is moving pallets between docks and storage points the other.

KUKA's AMR guidance puts the weight on integration. Its argument is that robots show their value once fleets take transport orders directly from WMS and ERP systems, and that fleet management and open interfaces decide whether a pilot can scale.

KUKA describes the pressure behind the shift in terms Mexican operators will recognize: rising product variety, shorter product life cycles and fluctuating demand, with traditional material flows built on fixed transport routes increasingly reaching their limits. Those are close relatives of the e-commerce growth and SKU diversification Mexico Business News cites. In KUKA's framing, the question has moved from whether AMRs can be deployed to how companies integrate them, optimize material flows and scale over the long term.

Its case material shows the transport side of that story. GTS, part of the Krone Group, uses AMRs to automate material transport in welding production without the constraints of fixed conveyor technology, and a food manufacturer uses them to move and sort pallets. Neither is e-commerce picking, which is the point: these deployments answer a pallet-flow question, not the walking question that should decide a first picking site.

Buying robots versus renting them

The money question splits two ways in the Mexico Business News analysis. Buying outright is an upfront capital project. Robotics-as-a-service (RaaS) spreads some costs into recurring payments but can lock a company into long contractual commitments. A purchase can involve these cost lines:

• Robots and equipment
• Facility modifications
• Software licenses
• Connectivity
• System integration
• Workforce training

According to the analysis, the choice comes down to three variables: available liquidity, the expected duration of the project and demand variability. The first is a treasury question. The other two tie the financing decision back to the building itself, since a site's demand pattern and planned life shape how long the robots need to earn their keep.

Demand variability is where the two halves of the decision meet. DHL's case for mobile systems is operational flexibility when volumes or layouts change. A recurring-payment model could add financial flexibility on top, but only if the contract term doesn't outlast the project it is meant to serve, which is the risk the long commitments of RaaS can carry.

A pilot that sets the baseline

The analysis recommends a pilot with defined operating indicators before any multi-site rollout. Start with a facility that has a clear problem, such as long travel distances, low productivity or trouble handling peak demand. Record baseline performance before the robots arrive, then compare it with pilot results.

That baseline is what turns the 33.57% figure from a research ceiling into a number for a specific building. Product weight, travel and pick density all varied in the study, so the only gain worth putting in a budget is the one measured on site.

It is also the figure Cuautitlán Izcalli can't supply. A well-instrumented pilot gives an operator the financial benchmark the public case lacks, measured in its own building, and that is the number a multi-site capital request can stand on.