Logistics growth driven by smart systems

As artificial intelligence moves from being an experimental tool to an essential component of everyday infrastructure across much of the global economy, in 2025, China's parcel delivery industry offered one of the clearest examples of how profoundly the technology can reshape a mature, labor-intensive sector.

The shift has been most visible in the physical architecture of logistics. Large sorting centers have become largely automated, unmanned warehouses have expanded steadily, and pilot programs involving driverless vehicles and drones have moved into regular operation in parts of the country. Cloud computing and large AI models have been embedded in demand forecasting, warehouse management, dispatching and route planning — changes that, taken together, have pushed delivery efficiency and reliability to levels rarely matched.

"The postal and parcel delivery sector has become increasingly technology-intensive during the 14th Five-Year Plan period (2021-2025)," said Zhao Chongjiu, head of the State Post Bureau of China. Electronic waybills and recyclable transit packaging are now standard, he noted, while the industry's combined transport efficiency, digital coordination and service coverage rank among the world's most advanced.

Last year, China processed nearly 199 billion parcels, a 13.7 percent increase from the year before, generating 1.5 trillion yuan ($216 billion) in revenue. On the peak day, more than 777 million packages moved through the network — more than 6,000 every second — placing extraordinary demands on a system that has increasingly turned to algorithms to keep pace.

These numbers have been enabled through the use of artificial intelligence, which has moved from pilot projects to the operational core of China's logistics network, influencing how parcels are sorted, routed, transported and delivered — and, increasingly, how human labor is deployed.

That shift was symbolized in December in Shenzhen, Guangdong province, when a local resident, Li Xiaojun, received an online order — an AI-enabled learning device — delivered to his neighborhood by an unmanned vehicle before being handed to a courier for the final steps. The package was China's 180 billionth parcel of the year. Its journey, largely invisible to its recipient, traced the contours of a system being steadily rewired by algorithms.

Algorithmic advantage

The delivery network's adoption of AI has come out of necessity.

The industry operates under conditions that strain conventional logistics models: enormous volume, thin margins, rising labor costs and a mandate to serve both dense cities and remote rural areas. Manual dispatching, human-dependent sorting and fixed delivery routes prove increasingly unsustainable at such an incredible scale.

AI has offered a way to absorb growth rather than be overwhelmed by it, according to Liu Jiang, director of strategic planning research at the bureau's development and research center. He added that the sector has been fueled by a mix of supportive macroeconomic policies and a steady unified national market.

As scale continues to expand, the courier industry is no longer just responding to consumption, he said, but increasingly shaping it, emerging as a key driver of domestic demand and economic stability. Technology, he added, has become a central engine sustaining that growth.

In China, the presence of a unified national market and sustained growth in parcel volumes has provided a broad testing ground for new technologies. Large-scale real-world data allows intelligent systems to be trained and adjusted more efficiently, supporting improvements in areas such as dispatching, warehouse management and route planning. These technologies are increasingly being integrated into daily operations, contributing to higher efficiency and more consistent service performance.

Automation to intelligence

Over the past year, major courier companies, including SF Express, ZTO Express and J&T Express, have integrated large language and industry-specific AI models into their operations, marking a transition from basic automation to more adaptive, system-wide intelligence.

At J&T, AI-driven training and internal support systems have reduced manual customer-service workloads by about 50 percent and shortened onboarding time for new employees. At SF and ZTO, large models are being used to optimize resource allocation, predict demand surges and streamline service workflows, helping lower operating costs while improving reliability.

AI has been embedded in nearly every major link of the delivery chain. Vision systems scan parcels in milliseconds, reducing sorting errors. Algorithms adjust routes in real time in response to weather, traffic and volume fluctuations. Predictive models help companies anticipate peak demand during shopping festivals and holiday travel seasons.

By the end of China's 14th Five-Year Plan (2021-25), most large sorting centers had achieved near-total automation. Cloud computing and large models were being deployed for demand forecasting, warehouse management and dispatch planning, while electronic waybills and reusable transit packaging became standard across the industry, Zhao said.

Inside the warehouse

At JD Logistics' Pingshan grid warehouse in Shenzhen, the transformation is visible on the floor.

The site processes roughly 15,000 parcels a day, with five unmanned vehicles shuttling goods on site, reducing repetitive trips by human staff.

"They ease the workload and let couriers spend more time in communities, focusing on customer service," said An Jixing, the station's head. "The improvement in efficiency is very clear."

Nearby, JD's "smart warehouse" that opened in October, uses nearly 200 mobile robots and vertical transport systems to move standardized bins through a dense, three-dimensional storage environment. It can handle more than 35,000 outbound orders a day.

According to Li Jinyuan, an operation and maintenance engineer at JD Logistics' smart warehousing facilities, parcels can move from order confirmation to outbound sorting in as little as 15 minutes. Storage efficiency is more than four times that of traditional warehouses, while picking accuracy has reached 99.99 percent, he said.

As machines have taken over repetitive tasks, new roles have emerged to manage, maintain and optimize intelligent systems.

Last mile, reconfigured

The most visible changes, however, are unfolding on the streets.

Zhang Fan, the courier who delivered China's 180 billionth parcel last year, serves more than 2,000 households in a Shenzhen neighborhood. Before unmanned vehicles were introduced, he traveled nearly six kilometers each way, four times a day, just to collect parcels.

"Now, the vehicles bring packages to a transfer point a few hundred meters away," Zhang said. "I can focus more on deliveries, talk to customers and collect outgoing parcels."

At ZTO's sorting hub in Tonglu, Zhejiang province, eight autonomous vehicles supplied by Neolix have been put into regular operation. According to Tang Rong, the facility's manager, the vehicles have increased overall site efficiency by about 70 percent while significantly reducing labor costs.

Each vehicle can handle the workload of roughly three drivers and operate around the clock. A typical 60-kilometer run costs about 15 yuan in electricity, compared with at least 50 yuan in fuel for a conventional vehicle.

"The technology allows people to focus on more value-added tasks, especially last-mile delivery," Tang said.

The hub plans to expand its autonomous fleet this year.

Even though the technology is ready, one major bottleneck is policy and regulation, and large-scale deployment depends on regulatory clarity, particularly access to public roads.

"Temporary obstacles are technical problems that can be solved," said He Jianfang, a product manager for JD's unmanned delivery vehicles. "The bigger challenge is policy — who gets the right to operate, and where."

Shenzhen testing ground

Shenzhen has emerged as a testing ground for what an even more automated delivery ecosystem might look like.

The city has deployed 180 unmanned vehicles in the postal and parcel sector, capable of handling more than 100,000 parcels a day, according to Liu Xiaoqing, deputy head of the office of the Shenzhen Postal Administration.

Over the past year, companies have invested more than 150 million yuan to upgrade sorting equipment and security systems. Drone delivery has expanded rapidly, with eight operational bases and more than 500 routes in service.

In parts of the Guangdong-Hong Kong-Macao Greater Bay Area, same-city deliveries within two hours — and intercity deliveries within three — have become routine.

Nationally, drones are used in hundreds of pilot applications, particularly in rural and mountainous regions where traditional delivery is costly and slow. More than 450 drones transport close to four million parcels annually, according to official data.

Rather than prescribing specific technologies, regulators have focused on creating room for experimentation, allowing companies to test new delivery models while gradually addressing concerns around safety, airspace and road access.

Beyond speed

China has led the world in annual parcel volume for the past 12 years. During the past five years alone, the industry's annual parcel count rose from just over 80 billion to nearly 200 billion, accounting for more than 60 percent of global courier growth. Per-capita parcel usage has climbed from 59 in 2020 to 141 in 2025.

This year, the sector is expected to handle about 214 billion parcels, maintaining steady growth even as broader economic growth is expected to slow.

For policymakers, the integration of AI into logistics has become a way to sustain that momentum without relying solely on labor or expansion. For companies, it has become a matter of survival in an industry where margins are thin and expectations are relentless.

The record-setting parcel delivered in Shenzhen attracted little notice from its recipient. But its route — planned, adjusted and executed largely by intelligent systems — offers a glimpse of how China's parcel network is evolving, quietly and at scale.