@Logistics Professionals, a “storm” is brewing in the supply chain amid the AI wave.

■   The logistics sector is currently undergoing a transformation from “ At the cusp of a generational shift driven by disruptive technologies. ”。

■   Supply chain management ranks among the top three industries that stand to gain the most from AI applications.

■   A threat to the transportation industry comes from within the industry itself. “ High-tech digital entrant ”。

Future artificial intelligence may not only “Disrupt” the existing logistics industry, and even transform supply-chain management, while reducing the number of jobs people perform.

According to industry executives, the following technologies will be deployed in the future. — including sidewalk‑walking robots, self‑driving trucks, customer‑service chatbots, and even generative AI that can predict disruptions or explain why sales‑forecasting models were “completely off the mark.”

▍ Logistics upgrading and transformation Truck driver substitution?

Just this year In May, a research report by Morgan Stanley stated that artificial intelligence could potentially eliminate all human involvement in supply chains—either entirely or nearly so—including “back-office” tasks that do not require direct interaction with frontline workers.

Of course, although AI‑driven innovations already number in the tens of thousands, this report remains cautiously optimistic about the pace of AI adoption.

According to the report, although the current technological applications of artificial intelligence remain quite limited, the transition from research and development to practical implementation is not a linear process: historically, it has typically taken about… for a new technology to progress from inception to commercial deployment. Over a decade, this implies that productivity gains have lagged behind. However, as the adoption of new technologies accelerates, the pace of AI—this cutting-edge technology—could outstrip that of the personal computer (PC) revolution.

Over time, technology adoption has been accelerating. Image source: Morgan Stanley

According to the report, the logistics sector is currently undergoing a transformation driven by… “At the cusp of a generational shift driven by disruptive technologies,” the technologies already in widespread use include autonomous driving, electric vehicles, blockchain, and drones. Meanwhile, artificial intelligence is the newest among these potentially transformative technologies—and perhaps the most powerful to date.

For example, the report states that it is expected In 2024, hundreds of self-driving trucks will begin operating in the United States, reducing per-mile costs by 25% to 30% and eventually eliminating the need for human drivers altogether—though the timeline for this is “more than three years.” In other words, could the job of truck driver soon become obsolete?

To answer this question, we must first examine the pace of development in autonomous trucks. On this point, it is worth considering… Take TuSimple, the “first autonomous truck stock,” as an example.

According to reports, TuSimple has successfully completed China’s first fully driverless test of an autonomous heavy-duty truck on public roads, with no safety driver on board and no human intervention throughout the entire journey. The fully driverless testing area encompassed Shanghai’s Deepwater Port Logistics Park, the Donghai Bridge, and other public test routes for autonomous vehicles, covering a total distance of approximately… 62 kilometers. The scenarios covered include traffic signal recognition, on- and off-ramp driving, lane changes, yielding to vehicles in the emergency lane, handling partial lane closures, and navigating heavy fog and crosswinds.

The advantages of autonomous driving are clear: prolonged manual driving can lead to driver fatigue, necessitating rest breaks and inevitably reducing transport efficiency. Once autonomous technology matures, it will be able to operate continuously without interruption, significantly boosting operational productivity. Moreover, autonomous systems eliminate the risk of fatigue and other human‑related hazards, enabling faster and safer delivery to destinations.

Of course, autonomous trucking still has a long way to go, but one thing is certain: once this path is successfully paved, it will fundamentally transform the operating model of the entire logistics industry. The table below outlines the strengths and weaknesses of the world’s leading players in autonomous driving; it is provided for reference only.

Comparison of the Strengths and Weaknesses of Autonomous Trucking Companies   Image source: GF Securities

▍ Out of stock Gone for good?

Of course, artificial intelligence is transforming not just logistics but the entire supply chain.

The kind that’s always on one’s lips “Supply chain transformation and upgrading” involves leveraging technology to optimize every stage of the product journey, from production to the point of consumption. Each of these stages relies on the enabling power of artificial intelligence, and supply‑chain processes that were once heavily reliant on manual operations are now accelerating their shift toward intelligent automation.

As is well known, supply chains are not only lengthy but also involve multiple stakeholders: a company may source raw materials from manufacturers in different regions around the world, transport components to a central assembly plant for processing, and ultimately deliver finished products to end consumers via logistics.

Producing and shipping goods has always been inherently complex, but the three-year global COVID‑19 pandemic, coupled with frequent geopolitical conflicts, has further compounded this complexity. As a result, shortages of critical components—such as computer chips—have emerged, and companies have been forced to adjust their supply chains. This heightened uncertainty means that businesses often lack visibility into what exactly happens to their products as they move through the production and logistics process.

Morgan Stanley’s report explains that this is precisely where artificial intelligence and machine learning come into play. By forecasting potential disruptions in the transportation network, AI and machine learning can even proactively implement measures before issues arise, thereby preventing complete breakdowns in the logistics system.

Here’s a simple example: Adverse weather is a major challenge for freight transportation. By leveraging an AI‑driven data‑centric freight network, real-time shipment information can be provided, enabling timely adjustments and optimization of transport routes in response to unexpected events such as severe weather—thereby boosting operational efficiency.

The aforementioned theme also applies to investment firms. Jefferies has been closely monitoring the topic and has made several forecasts regarding “the impact of generative AI on transportation and logistics,” including demand forecasting, predicting truck maintenance schedules, optimizing transport routes, and tracking shipments in real time.

According to the agency in According to a research report dated June 6, as generative AI is adopted in sectors such as trucking and logistics, labor shortages among truck drivers, blizzards triggered by polar vortices that disrupt trade, and shortages of infant formula on store shelves will all become distant memories.

The points above directly address the pain points of the transportation industry. Take the shortage of truck drivers, for example—it has long been a persistent challenge for the U.S. transportation sector. According to projections by the American Trucking Associations, By 2027, the U.S. transportation industry could reach a market size of one trillion dollars, yet it faces a severe supply-demand imbalance, primarily driven by a shortage of truck drivers: in 2019, the shortfall stood at 66,000 workers, and it is projected to grow to 160,000 by 2026. The adoption of artificial intelligence may help bridge this gap.

“Science and technology are the primary productive forces.” Advancing the transformation and upgrading of supply chains is inseparable from robust technological support, particularly the continuous innovation in key technologies such as machine vision, deep learning, big data, and cloud computing, which have opened up vast possibilities for supply-chain disruption and evolution.

Specifically in practical applications, the supply chain encompasses numerous processes that are well-suited for AI, such as autonomous warehouse carts and inspection robots. From the production floor all the way to the final point of consumption, AI technologies can be seamlessly integrated. According to a McKinsey survey, supply chain management ranks among the top three industries that stand to gain the most from AI applications.

▍ Traditional industry giants Embrace Artificial Intelligence

Since artificial intelligence is capable of “Disrupting” the entire logistics industry, shipping giant Maersk is also actively embracing artificial intelligence. Navneet Kapoor, the company’s Chief Technology and Information Officer, stated that generative AI will become a key component of its operations.

Kapoor further pointed out that artificial intelligence and machine learning have been around for a long time, and have evolved from merely… From “fun” prototype projects to more “real-world” initiatives within the company, the landscape is now poised for a pivotal shift: with the advent of generative AI, artificial intelligence has finally seized a transformative opportunity to take center stage in mainstream business.

Kapoor said that Maersk has been leveraging artificial intelligence for several years and is now… “Proactively seeking” ways to integrate artificial intelligence more broadly into its business processes and functions. One approach already in use is helping customers plan more effectively.

Kapoor explained that Maersk is using artificial intelligence to build what is known as A “predictive” cargo‑arrival model enhances forecast reliability for customers. Even after the COVID‑19 pandemic, ensuring reliability remains critical, and the model enables customers to better plan their supply chains and manage inventory, thereby reducing costs. Maersk also aims to leverage artificial intelligence to recommend solutions when shipping routes become congested—for instance, by advising whether cargo should be transported by air or stored.

Moreover, Kapoor said the company aims to leverage a large language model to learn how to identify, summarize, and generate text and other types of content from vast amounts of data, thereby gaining deeper insights into the sales process. “You can gain a comprehensive understanding of all the transactions your customers conducted with you last year, and pinpoint the underlying reasons why you may have lost orders in a particular business segment.”

▍ Double-edged sword AI Will it exacerbate unemployment?

Like The widespread adoption of consumer‑facing AI systems like ChatGPT has left many white‑collar workers, once enjoying seemingly secure careers, worrying that their jobs may soon be at risk. As generative AI continues to penetrate supply chains, will even more people find themselves out of work as a result?

On this, Kapoor said: “In my view, generative AI represents a once-in-a-lifetime disruption. As such, it will lead to job losses in traditional contexts, but I also believe it will create new roles—just as every technological upheaval before it has done. For example, the role of prompt engineers—those who train AI to generate better responses—may become increasingly in demand.”

Morgan Stanley’s report notes that one threat to the transportation sector comes from within the industry itself. “High-tech digital entrants,” as described in the report, Artificial intelligence is a double-edged sword for the logistics industry: it can help make the sector more efficient, but it may also reduce demand for third-party logistics providers’ services in packaging, warehousing, and transportation.

Maersk has already invested in AI startups through its Growth Ventures division, including an autonomous electric truck manufacturer. Einride; the company Pactum, which automates sales negotiations; and the AI platform 7bridges, which helps companies gain visibility into their inventory and forecast delays.

Kapoor explained, “We view data startups as enablers and accelerators of transformation, but we remain vigilant: we don’t want to be complacent on this front... Data startups can serve as intermediaries between us and our customers, and we need to ensure that we stay ahead while also learning from these startups.”

▍ Knowledge Assistant Show one's full capabilities

Based on artificial intelligence and already proven effective across multiple fields, “Knowledge Assistant” also holds vast potential and can make significant contributions in the supply chain domain.

A software company dedicated to helping businesses centralize and analyze data. Igor Rikalo, President and Chief Operating Officer of o9 Solutions, stated that knowledge assistants can help address another challenge: product overstocking and stockouts, which often stem from poor communication among internal teams—specifically, discrepancies between the sales department and the supply chain management team regarding transactions.

According to him, choosing a knowledge assistant is also a… A “suboptimal” outcome, as products that the sales team has heavily invested in promoting may face supply-chain constraints, which inevitably leads to a waste of resources.

He added that he hopes everyone will have this kind of AI- and large language model–powered… “Knowledge Assistant” can provide in-depth insights into a range of sales issues, such as why a supplier’s delivery quantity falls short of the ordered amount.

Answering these questions typically requires input from the sales, marketing, supply chain, and procurement teams, but generative AI may be able to analyze big data to provide insights. This could also mean that integrated business planning teams will require fewer personnel; these teams are responsible for overseeing the achievement of long-term objectives and for forecasting revenue and demand for specific products.

Ricardo said, “Today’s planning team of 1,000 people could shrink to 100 or fewer.”

▍ Written at the end

While artificial intelligence can drive the transformation and upgrading of supply chains, the greatest challenge still lies with people. The notion of relying solely on AI to completely replace human labor is unrealistic. After all, no matter how advanced AI becomes, it ultimately requires human operators and controllers—and the very quality that makes us human: empathy—may be precisely what AI lacks most.