As a contract provider of warehousing, logistics, and supply chain solutions, Geodis often has to provide customized services for clients.
That was the case recently when one of its customers asked Geodis to up its inventory monitoring game—specifically, to begin conducting quarterly cycle counts of the goods it stored at a Geodis site. Trouble was, performing more frequent counts would be something of a burden for the facility, which still conducted inventory counts manually—a process that was tedious and, depending on what else the team needed to accomplish, sometimes required overtime.
So Levallois, France-based Geodis launched a search for a technology solution that would both meet the customer’s demand and make its inventory monitoring more efficient overall, hoping to save time, labor, and money in the process.
SCAN AND DELIVER
Geodis found a solution with Gather AI, a Pittsburgh-based firm that automates inventory monitoring by deploying small drones to fly through a warehouse autonomously scanning pallets and cases. The system’s machine learning (ML) algorithm analyzes the resulting inventory pictures to identify barcodes, lot codes, text, and expiration dates; count boxes; and estimate occupancy, gathering information that warehouse operators need and comparing it with what’s in the warehouse management system (WMS).
Among other benefits, this means employees no longer have to spend long hours doing manual inventory counts with order-picker forklifts. On top of that, the warehouse manager is able to view inventory data in real time from a web dashboard and identify and address inventory exceptions.
But perhaps the biggest benefit of all is the speed at which it all happens. Gather AI’s drones perform those scans up to 15 times faster than traditional methods, the company says. To that point, it notes that before the drones were deployed at the Geodis site, four manual counters could complete approximately 800 counts in a day. By contrast, the drones are able to scan 1,200 locations per day.
FLEXIBLE FLYERS
Although Geodis had a number of options when it came to tech vendors, there were a couple of factors that tipped the odds in Gather AI’s favor, the partners said. One was its close cultural fit with Geodis. “Probably most important during that vetting process was understanding the cultural fit between Geodis and that vendor. We truly wanted to form a relationship with the company we selected,” Geodis Senior Director of Innovation Andy Johnston said in a release.
Speaking to this cultural fit, Johnston added, “Gather AI understood our business, our challenges, and the course of business throughout our day. They trained our personnel to get them comfortable with the technology and provided them with a tool that would truly make their job easier. This is pretty advanced technology, but the Gather AI user interface allowed our staff to see inventory variances intuitively, and they picked it up quickly. This shows me that Gather AI understood what we needed.”
Another factor in Gather AI’s favor was the prospect of a quick and easy deployment: Because the drones can conduct their missions without GPS or Wi-Fi, the supplier would be able to get its solution up and running quickly. In the words of Geodis Industrial Engineer Trent McDermott, “The Gather AI implementation process was efficient. There were no IT infrastructure or layout changes needed, and Gather AI was flexible with the installation to not disrupt peak hours for the operations team.”
QUICK RESULTS
Once the drones were in the air, Geodis saw immediate improvements in cycle counting speed, according to Gather AI. But that wasn’t the only benefit: Geodis was also able to more easily find misplaced pallets.
“Previously, we would research the inventory’s systemic license plate number (LPN),” McDermott explained. “We could narrow it down to a portion or a section of the warehouse where we thought that LPN was, but there was still a lot of ambiguity. So we would send an operator out on a mission to go hunt and find that LPN,” a process that could take a day or two to complete. But the days of scouring the facility for lost pallets are over. With Gather AI, the team can simply search in the dashboard to find the last location where the pallet was scanned.
And about that customer who wanted more frequent inventory counts? Geodis reports that it completed its first quarterly count for the client in half the time it had previously taken, with no overtime needed. “It’s a huge win for us to trim that time down,” McDermott said. “Just two weeks into the new quarter, we were able to have 40% of the warehouse completed.”
Generative AI (GenAI) is being deployed by 72% of supply chain organizations, but most are experiencing just middling results for productivity and ROI, according to a survey by Gartner, Inc.
That’s because productivity gains from the use of GenAI for individual, desk-based workers are not translating to greater team-level productivity. Additionally, the deployment of GenAI tools is increasing anxiety among many employees, providing a dampening effect on their productivity, Gartner found.
To solve those problems, chief supply chain officers (CSCOs) deploying GenAI need to shift from a sole focus on efficiency to a strategy that incorporates full organizational productivity. This strategy must better incorporate frontline workers, assuage growing employee anxieties from the use of GenAI tools, and focus on use-cases that promote creativity and innovation, rather than only on saving time.
"Early GenAI deployments within supply chain reveal a productivity paradox," Sam Berndt, Senior Director in Gartner’s Supply Chain practice, said in the report. "While its use has enhanced individual productivity for desk-based roles, these gains are not cascading through the rest of the function and are actually making the overall working environment worse for many employees. CSCOs need to retool their deployment strategies to address these negative outcomes.”
As part of the research, Gartner surveyed 265 global respondents in August 2024 to assess the impact of GenAI in supply chain organizations. In addition to the survey, Gartner conducted 75 qualitative interviews with supply chain leaders to gain deeper insights into the deployment and impact of GenAI on productivity, ROI, and employee experience, focusing on both desk-based and frontline workers.
Gartner’s data showed an increase in productivity from GenAI for desk-based workers, with GenAI tools saving 4.11 hours of time weekly for these employees. The time saved also correlated to increased output and higher quality work. However, these gains decreased when assessing team-level productivity. The amount of time saved declined to 1.5 hours per team member weekly, and there was no correlation to either improved output or higher quality of work.
Additional negative organizational impacts of GenAI deployments include:
Frontline workers have failed to make similar productivity gains as their desk-based counterparts, despite recording a similar amount of time savings from the use of GenAI tools.
Employees report higher levels of anxiety as they are exposed to a growing number of GenAI tools at work, with the average supply chain employee now utilizing 3.6 GenAI tools on average.
Higher anxiety among employees correlates to lower levels of overall productivity.
“In their pursuit of efficiency and time savings, CSCOs may be inadvertently creating a productivity ‘doom loop,’ whereby they continuously pilot new GenAI tools, increasing employee anxiety, which leads to lower levels of productivity,” said Berndt. “Rather than introducing even more GenAI tools into the work environment, CSCOs need to reexamine their overall strategy.”
According to Gartner, three ways to better boost organizational productivity through GenAI are: find creativity-based GenAI use cases to unlock benefits beyond mere time savings; train employees how to make use of the time they are saving from the use GenAI tools; and shift the focus from measuring automation to measuring innovation.
The company’s Oracle Cloud SCM is part of its Oracle Fusion Cloud Applications Suite, and enables customers to connect supply chain processes and quickly respond to changing demand, supply, and market conditions. In addition, embedded AI now acts as an advisor to help analyze supply chain data, generate content, and augment or automate processes to help improve business operations and create a resilient supply network to outpace change, Oracle says.
The new tech comes in the form of role-based AI agents within Oracle Cloud SCM that are designed to automate routine tasks, deliver personalized insights and recommendations, and allow organizations to focus more time on strategic supply chain initiatives. While past versions of Oracle software already included AI assistants—that could formulate descriptions or write emails—the new AI agents can help users by answering natural language queries about complex rules such as a policy document on returns or claims.
“One of our goals is to not have AI be an esoteric thing that you need special training to use, but just to act as part of the tool, to help you accomplish each task according to the standards of your own particular company,” Srini Rajagopal, Oracle’s vice president of logistics product strategy, said in a briefing.
For example, once a company’s IT office has uploaded the firm’s unique policy documents—on issues such as packaging, deadlines, or transaction requirements—then all the company’s customer service representatives (CSRs) can use the new AI-based advisory agents to type natural-language queries into a text-based chat box to obtain quick answers to complicated questions.
In addition to providing quick business answers to current employees, that approach can also help to train new workers on company policies in a labor market with high turnover rates. Additional use cases could apply to workers in roles such as a shop floor operator or warehouse worker, Rajagopal said.
In another application of the new AI, the updates have added new capabilities to Oracle Transportation Management, Oracle Global Trade Management, and Oracle Order Management.
Applied to the transportation management system (TMS) product, the AI enables “better, faster, smarter” operations through new capabilities such as AI-powered order route predictions, transit time predictions, and a transportation emissions calculator. In the global trade management (GTM) took, the new AI supports a user-configurable platform that can provide trade incentive program processing relief and reporting. And in the order management software, the AI can provide a returns summary, pricing promotions summary, item availability check, and order fulfillment view.
“To successfully navigate an increasingly complex global landscape, supply chain leaders need agile and efficient processes that can help them diversify and strengthen supplier networks, adapt transportation and logistics strategies, and stay ahead of regulatory changes,” Rajagopal said in a release.
Oh, you work in logistics, too? Then you’ve probably met my friends Truedi, Lumi, and Roger.
No, you haven’t swapped business cards with those guys or eaten appetizers together at a trade-show social hour. But the chances are good that you’ve had conversations with them. That’s because they’re the online chatbots “employed” by three companies operating in the supply chain arena—TrueCommerce,Blue Yonder, and Truckstop. And there’s more where they came from. A number of other logistics-focused companies—like ChargePoint,Packsize,FedEx, and Inspectorio—have also jumped in the game.
While chatbots are actually highly technical applications, most of us know them as the small text boxes that pop up whenever you visit a company’s home page, eagerly asking questions like:
“I’m Truedi, the virtual assistant for TrueCommerce. Can I help you find what you need?”
“Hey! Want to connect with a rep from our team now?”
“Hi there. Can I ask you a quick question?”
Chatbots have proved particularly popular among retailers—an October survey by artificial intelligence (AI) specialist NLX found that a full 92% of U.S. merchants planned to have generative AI (GenAI) chatbots in place for the holiday shopping season. The companies said they planned to use those bots for both consumer-facing applications—like conversation-based product recommendations and customer service automation—and for employee-facing applications like automating business processes in buying and merchandising.
But how smart are these chatbots really? It varies. At the high end of the scale, there’s “Rufus,” Amazon’s GenAI-powered shopping assistant. Amazon says millions of consumers have used Rufus over the past year, asking it questions either by typing or speaking. The tool then searches Amazon’s product listings, customer reviews, and community Q&A forums to come up with answers. The bot can also compare different products, make product recommendations based on the weather where a consumer lives, and provide info on the latest fashion trends, according to the retailer.
Another top-shelf chatbot is “Manhattan Active Maven,” a GenAI-powered tool from supply chain software developer Manhattan Associates that was recently adopted by the Army and Air Force Exchange Service. The Exchange Service, which is the 54th-largest retailer in the U.S., is using Maven to answer inquiries from customers—largely U.S. soldiers, airmen, and their families—including requests for information related to order status, order changes, shipping, and returns.
However, not all chatbots are that sophisticated, and not all are equipped with AI, according to IBM. The earliest generation—known as “FAQ chatbots”—are only clever enough to recognize certain keywords in a list of known questions and then respond with preprogrammed answers. In contrast, modern chatbots increasingly use conversational AI techniques such as natural language processing to “understand” users’ questions, IBM said. It added that the next generation of chatbots with GenAI capabilities will be able to grasp and respond to increasingly complex queries and even adapt to a user’s style of conversation.
Given their wide range of capabilities, it’s not always easy to know just how “smart” the chatbot you’re talking to is. But come to think of it, maybe that’s also true of the live workers we come in contact with each day. Depending on who picks up the phone, you might find yourself speaking with an intern who’s still learning the ropes or a seasoned professional who can handle most any challenge. Either way, the best way to interact with our new chatbot colleagues is probably to take the same approach you would with their human counterparts: Start out simple, and be respectful; you never know what you’ll learn.
The 40-acre solar facility in Gentry, Arkansas, includes nearly 18,000 solar panels and 10,000-plus bi-facial solar modules to capture sunlight, which is then converted to electricity and transmitted to a nearby electric grid for Carroll County Electric. The facility will produce approximately 9.3M kWh annually and utilize net metering, which helps transfer surplus power onto the power grid.
Construction of the facility began in 2024. The project was managed by NextEra Energy and completed by Verogy. Both Trio (formerly Edison Energy) and Carroll Electric Cooperative Corporation provided ongoing consultation throughout planning and development.
“By commissioning this solar facility, J.B. Hunt is demonstrating our commitment to enhancing the communities we serve and to investing in economically viable practices aimed at creating a more sustainable supply chain,” Greer Woodruff, executive vice president of safety, sustainability and maintenance at J.B. Hunt, said in a release. “The annual amount of clean energy generated by the J.B. Hunt Solar Facility will be equivalent to that used by nearly 1,200 homes. And, by drawing power from the sun and not a carbon-based source, the carbon dioxide kept from entering the atmosphere will be equivalent to eliminating 1,400 passenger vehicles from the road each year.”
With the new Trump Administration continuing to threaten steep tariffs on Mexico, Canada, and China as early as February 1, supply chain organizations preparing for that economic shock must be prepared to make strategic responses that go beyond either absorbing new costs or passing them on to customers, according to Gartner Inc.
But even as they face what would be the most significant tariff changes proposed in the past 50 years, some enterprises could use the potential market volatility to drive a competitive advantage against their rivals, the analyst group said.
Gartner experts said the risks of acting too early to proposed tariffs—and anticipated countermeasures by trading partners—are as acute as acting too late. Chief supply chain officers (CSCOs) should be projecting ahead to potential countermeasures, escalations and de-escalations as part of their current scenario planning activities.
“CSCOs who anticipate that current tariff volatility will persist for years, rather than months, should also recognize that their business operations will not emerge successful by remaining static or purely on the defensive,” Brian Whitlock, Senior Research Director in Gartner’s supply chain practice, said in a release.
“The long-term winners will reinvent or reinvigorate their business strategies, developing new capabilities that drive competitive advantage. In almost all cases, this will require material business investment and should be a focal point of current scenario planning,” Whitlock said.
Gartner listed five possible pathways for CSCOs and other leaders to consider when faced with new tariff policy changes:
Retire certain products: Tariff volatility will stress some specific products, or even organizations, to a breaking point, so some enterprises may have to accept that worsening geopolitical conditions should force the retirement of that product.
Renovate products to adjust: New tariffs could prompt renovations (adjustments) to products that were overdue, as businesses will need to take a hard look at the viability of raising or absorbing costs in a still price-sensitive environment.
Rebalance: Additional volatility should be factored into future demand planning, as early winners and losers from initial tariff policies must both be prepared for potential countermeasures, policy escalations and de-escalations, and competitor responses.
Reinvent: As tariff volatility persists, some companies should consider investing in new projects in markets that are not impacted or that align with new geopolitical incentives. Others may pivot and repurpose existing facilities to serve local markets.
Reinvigorate: Early winners of announced tariffs should seek opportunities to extend competitive advantages. For example, they could look to expand existing US-based or domestic manufacturing capacity or reposition themselves within the market by lowering their prices to take market share and drive business growth.