You may not be able to see it, but artificial intelligence (AI) is probably installed on systems and equipment throughout your warehouse. Here’s how to judge its quality, effectiveness, and impact.
Ben Ames has spent 20 years as a journalist since starting out as a daily newspaper reporter in Pennsylvania in 1995. From 1999 forward, he has focused on business and technology reporting for a number of trade journals, beginning when he joined Design News and Modern Materials Handling magazines. Ames is author of the trail guide "Hiking Massachusetts" and is a graduate of the Columbia School of Journalism.
Step inside one of today’s high-tech warehouses, and you might marvel at the high-speed conveyors, voice-operated picking headsets, or fleets of autonomous mobile robots (AMRs) bustling about. But you’d be hard-pressed to point out any concrete examples of one of the most advanced technologies in the facility: artificial intelligence (AI).
Although it’s fast becoming an industry buzzword, AI is little understood outside of engineering circles, and its impact on logistics operations is hard to trace. But the truth is, the technology is already widely used, powering everything from the conversational interface on the smartphone in your pocket to the warehouse management system (WMS) that controls the flow of goods through the DC.
So if you can’t see the AI in your warehouse, how can you get a handle on it? That is, how do you select a good system, judge its effectiveness, and measure its impact on your business over time? To get answers to these and other questions, we asked some experts to share their thoughts about AI and the warehouse.
LEARN THE ABCs OF AI
To begin with, organizations that want to be successful at adopting AI have to change their basic approach to buying warehouse technology, says Peter Chen, co-founder and CEO of Covariant, which develops AI for commercial devices like robotic picking arms.
That’s because AI operates in a fundamentally different way from previous generations of logistics and material handling tools. Twenty years ago, logistics managers chose hardware—such as forklifts or conveyors—based on quantifiable attributes like speed, strength, and durability. As technology progressed and they began to select software—like a warehouse control system (WCS) or a WMS—they added criteria like cybersecurity, tech support, and ease of upgrades to the list. And now to buy AI systems, they need to adopt a new set of strategies, he says.
There are a couple of reasons for that. For one thing, AI differs from other technologies in that it becomes more, rather than less, effective over time—in direct contrast to, say, hardware that slowly breaks down with use or software that eventually becomes obsolete. What sets AI apart is that it doesn’t rely on “programmed intelligence,” Chen says. “With AI, you have intelligence that is not preprogrammed; instead, it learns from data and learns from experience. As opposed to static behavior, it learns from its own trial and error, and improves over time.”
In Covariant’s case, that learning curve enables machines like robotic arms to handle an ever-evolving and expanding range of items without requiring software upgrades or engineering studies, Chen says. Instead, the arm experiments with a wide array of stock-keeping units (SKUs) and slowly refines its ability to grasp items of various types, whether it’s apparel, grocery items, pharmaceuticals, or cosmetics.
Another factor that differentiates AI from other technologies is that companies get the best results when they start as soon as possible. Just as financial advisers tell clients to start investing early in life so their savings can grow through compound interest, AI works best when it has time to learn and develop. That contrasts with the typical hardware-buying strategy of waiting to refresh or replace equipment until the vendor rolls out the latest version. “The best way to buy AI is to get going as early as possible, because it can start learning ASAP,” Chen says. “Roll out your first site as quickly as possible so [the system] can collect data and start learning. The goal is to gather vast amounts of data, then develop analytics and actionable insights, so it compounds the results of AI adoption.”
SO YOU HAVE A NEW AI; NOW WHAT?
Measuring the results is a critical step in justifying any warehouse purchase, but it comes with an added challenge for AI because artificial intelligence typically operates “behind the scenes,” says John Black, senior vice president for product engineering at Brain Corp. The San Diego-based firm develops AI software and analytics to run AMRs from third-party manufacturers, with a focus on the automated floor-cleaning robots found in factories, DCs, retail stores, and office buildings.
Just as most people don’t know what type of microchip is powering their personal computer, most users of AI-powered devices can’t pinpoint exactly which functions rely on artificial intelligence. That makes it tough to gauge how well the technology is working, particularly because AI is typically held to a pass/fail standard—if a machine’s logic makes a single mistake, the entire device is seen as defective. For example, as an AMR cruises through a DC, it executes dozens of AI-enabled steps along the way, from localization and navigation to data gathering and analytics. If it fails at any one of those steps, then the AMR is basically useless. “You have to get all the way there,” Black says. “You can get most of the way there, and that is interesting, but it’s not enough to get a [return on investment]” for the company that bought the AMR.
“[AI] has to be nearly perfect. The measure is, how much time can this robot go without an intervention? You can send an employee over to fix a problem on an AMR, but every touch [diminishes the system’s return]. The goal is no-touch autonomy,” he says. “What you’re paying for with automation is accuracy and repeatability. If you have to have a person babysitting it, essentially you’ve just changed their job to overseeing the task and haven’t truly repurposed that employee from a labor standpoint.”
By that measure, AI works best when people forget they’re even using it, agrees Mike Myers, director of solutions at Third Wave Automation. The company incorporates its AI into reach trucks built by partner companies, allowing those forklifts to become autonomous vehicles.
Myers points to AI that has run for years as a basic “rules engine” in the accounting software many people use to file their personal tax returns. More recently, some developers of tier-one warehouse management systems have applied AI to the complex puzzle of managing fulfillment operations in a busy e-commerce DC. “And in a WMS, the AI is invisible in how it works. That’s how you know things are effective—when people don’t have to go into the WMS; they can just go to the end points” and follow the software’s guidance, he says.
WHAT EXACTLY IS YOUR AI THINKING ABOUT?
Striking a balance between automated decision making and human oversight is key to generating a solid ROI (return on investment) from an AI system, Myers says. But to measure how independently the AI in your warehouse is performing, you need to know exactly what it’s doing. And that can be a challenge.
A common misconception about AI is that it acts as “general intelligence,” functioning like a sentient robot in a Hollywood movie, Myers observes. But the truth is that most AI performs a series of small jobs, as opposed to pondering big questions like the meaning of life. “AI is in the vehicle navigation, the high-level route planning, and the sequencing of tasks in a facility, and it’s also in Siri on your iPhone,” Myers says. But as impressive as a tool like Siri is, it works through a series of machine learning and language processing steps, not through an umbrella of overall awareness, he explains. “So ‘general intelligence’ AI is not necessary for practical use cases; you can break up all those cases to achieve each step.”
In the end, the best way to measure an AI system’s impact on your logistics operations is to go back to the classic supply chain yardstick—the key performance indicator (KPI). “KPIs don’t change, whether you’re looking at cost per unit, SLA [service level agreement] adherence, or whatever,” Myers says. “Consistency in meeting those numbers is a measure of effectiveness. The AI is just a component, one machine in the entire system. But because AI is self-improving, [the fact that you’re] making progress toward those KPIs is how you know it’s working.”
Warehouse automation orders declined by 3% in 2024, according to a February report from market research firm Interact Analysis. The company said the decline was due to economic, political, and market-specific challenges, including persistently high interest rates in many regions and the residual effects of an oversupply of warehouses built during the Covid-19 pandemic.
The research also found that increasing competition from Chinese vendors is expected to drive down prices and slow revenue growth over the report’s forecast period to 2030.
Global macro-economic factors such as high interest rates, political uncertainty around elections, and the Chinese real estate crisis have “significantly impacted sales cycles, slowing the pace of orders,” according to the report.
Despite the decline, analysts said growth is expected to pick up from 2025, which they said they anticipate will mark a year of slow recovery for the sector. Pre-pandemic growth levels are expected to return in 2026, with long-term expansion projected at a compound annual growth rate (CAGR) of 8% between 2024 and 2030.
The analysis also found two market segments that are bucking the trend: durable manufacturing and food & beverage industries continued to spend on automation during the downturn. Warehouse automation revenues in food & beverage, in particular, were bolstered by cold-chain automation, as well as by large-scale projects from consumer-packaged goods (CPG) manufacturers. The sectors registered the highest growth in warehouse automation revenues between 2022 and 2024, with increases of 11% (durable manufacturing) and 10% (food & beverage), according to the research.
The Swedish supply chain software company Kodiak Hub is expanding into the U.S. market, backed by a $6 million venture capital boost for its supplier relationship management (SRM) platform.
The Stockholm-based company says its move could help U.S. companies build resilient, sustainable supply chains amid growing pressure from regulatory changes, emerging tariffs, and increasing demands for supply chain transparency.
According to the company, its platform gives procurement teams a 360-degree view of supplier risk, resiliency, and performance, helping them to make smarter decisions faster. Kodiak Hub says its artificial intelligence (AI) based tech has helped users to reduce supplier onboarding times by 80%, improve supplier engagement by 90%, achieve 7-10% cost savings on total spend, and save approximately 10 hours per week by automating certain SRM tasks.
The Swedish venture capital firm Oxx had a similar message when it announced in November that it would back Kodiak Hub with new funding. Oxx says that Kodiak Hub is a better tool for chief procurement officers (CPOs) and strategic sourcing managers than existing software platforms like Excel sheets, enterprise resource planning (ERP) systems, or Procure-to-Pay suites.
“As demand for transparency and fair-trade practices grows, organizations must strengthen their supply chains to protect their reputation, profitability, and long-term trust,” Malin Schmidt, founder & CEO of Kodiak Hub, said in a release. “By embedding AI-driven insights directly into procurement workflows, our platform helps procurement teams anticipate these risks and unlock major opportunities for growth.”
Here's our monthly roundup of some of the charitable works and donations by companies in the material handling and logistics space.
For the sixth consecutive year, dedicated contract carriage and freight management services provider Transervice Logistics Inc. collected books, CDs, DVDs, and magazines for Book Fairies, a nonprofit book donation organization in the New York Tri-State area. Transervice employees broke their own in-house record last year by donating 13 boxes of print and video assets to children in under-resourced communities on Long Island and the five boroughs of New York City.
Logistics real estate investment and development firm Dermody Properties has recognized eight community organizations in markets where it operates with its 2024 Annual Thanksgiving Capstone awards. The organizations, which included food banks and disaster relief agencies, received a combined $85,000 in awards ranging from $5,000 to $25,000.
Prime Inc. truck driver Dee Sova has donated $5,000 to Harmony House, an organization that provides shelter and support services to domestic violence survivors in Springfield, Missouri. The donation follows Sova's selection as the 2024 recipient of the Trucking Cares Foundation's John Lex Premier Achievement Award, which was accompanied by a $5,000 check to be given in her name to a charity of her choice.
Employees of dedicated contract carrier Lily Transportation donated dog food and supplies to a local animal shelter at a holiday event held at the company's Fort Worth, Texas, location. The event, which benefited City of Saginaw (Texas) Animal Services, was coordinated by "Lily Paws," a dedicated committee within Lily Transportation that focuses on improving the lives of shelter dogs nationwide.
Freight transportation conglomerate Averitt has continued its support of military service members by participating in the "10,000 for the Troops" card collection program organized by radio station New Country 96.3 KSCS in Dallas/Fort Worth. In 2024, Averitt associates collected and shipped more than 18,000 holiday cards to troops overseas. Contributions included cards from 17 different Averitt facilities, primarily in Texas, along with 4,000 cards from the company's corporate office in Cookeville, Tennessee.
Electric vehicle (EV) sales have seen slow and steady growth, as the vehicles continue to gain converts among consumers and delivery fleet operators alike. But a consistent frustration for drivers has been pulling up to a charging station only to find that the charger has been intentionally broken or disabled.
To address that threat, the EV charging solution provider ChargePoint has launched two products to combat charger vandalism.
The first is a cut-resistant charging cable that's designed to deter theft. The cable, which incorporates what the manufacturer calls "novel cut-resistant materials," is substantially more difficult for would-be vandals to cut but is still flexible enough for drivers to maneuver comfortably, the California firm said. ChargePoint intends to make its cut-resistant cables available for all of its commercial and fleet charging stations, and, starting in the middle of the year, will license the cable design to other charging station manufacturers as part of an industrywide effort to combat cable theft and vandalism.
The second product, ChargePoint Protect, is an alarm system that detects charging cable tampering in real time and literally sounds the alarm using the charger's existing speakers, screens, and lighting system. It also sends SMS or email messages to ChargePoint customers notifying them that the system's alarm has been triggered.
ChargePoint says it expects these two new solutions, when combined, will benefit charging station owners by reducing station repair costs associated with vandalism and EV drivers by ensuring they can trust charging stations to work when and where they need them.
New Jersey is home to the most congested freight bottleneck in the country for the seventh straight year, according to research from the American Transportation Research Institute (ATRI), released today.
ATRI’s annual list of the Top 100 Truck Bottlenecks aims to highlight the nation’s most congested highways and help local, state, and federal governments target funding to areas most in need of relief. The data show ways to reduce chokepoints, lower emissions, and drive economic growth, according to the researchers.
The 2025 Top Truck Bottleneck List measures the level of truck-involved congestion at more than 325 locations on the national highway system. The analysis is based on an extensive database of freight truck GPS data and uses several customized software applications and analysis methods, along with terabytes of data from trucking operations, to produce a congestion impact ranking for each location. The bottleneck locations detailed in the latest ATRI list represent the top 100 congested locations, although ATRI continuously monitors more than 325 freight-critical locations, the group said.
For the seventh straight year, the intersection of I-95 and State Route 4 near the George Washington Bridge in Fort Lee, New Jersey, is the top freight bottleneck in the country. The remaining top 10 bottlenecks include: Chicago, I-294 at I-290/I-88; Houston, I-45 at I-69/US 59; Atlanta, I-285 at I-85 (North); Nashville: I-24/I-40 at I-440 (East); Atlanta: I-75 at I-285 (North); Los Angeles, SR 60 at SR 57; Cincinnati, I-71 at I-75; Houston, I-10 at I-45; and Atlanta, I-20 at I-285 (West).
ATRI’s analysis, which utilized data from 2024, found that traffic conditions continue to deteriorate from recent years, partly due to work zones resulting from increased infrastructure investment. Average rush hour truck speeds were 34.2 miles per hour (MPH), down 3% from the previous year. Among the top 10 locations, average rush hour truck speeds were 29.7 MPH.
In addition to squandering time and money, these delays also waste fuel—with trucks burning an estimated 6.4 billion gallons of diesel fuel and producing more than 65 million metric tons of additional carbon emissions while stuck in traffic jams, according to ATRI.
On a positive note, ATRI said its analysis helps quantify the value of infrastructure investment, pointing to improvements at Chicago’s Jane Byrne Interchange as an example. Once the number one truck bottleneck in the country for three years in a row, the recently constructed interchange saw rush hour truck speeds improve by nearly 25% after construction was completed, according to the report.
“Delays inflicted on truckers by congestion are the equivalent of 436,000 drivers sitting idle for an entire year,” ATRI President and COO Rebecca Brewster said in a statement announcing the findings. “These metrics are getting worse, but the good news is that states do not need to accept the status quo. Illinois was once home to the top bottleneck in the country, but following a sustained effort to expand capacity, the Jane Byrne Interchange in Chicago no longer ranks in the top 10. This data gives policymakers a road map to reduce chokepoints, lower emissions, and drive economic growth.”