From Informatization to Intelligentization: Development Paths and Trends in Smart Logistics Systems

Taking the development of smart logistics as the central theme, this work provides an in-depth analysis of the distinctions and interconnections among informatization, digitalization, intelligentization, digital‑intelligence integration, and smartization, while also examining the evolutionary pathways and emerging trends of smart logistics systems across different stages.

01  Introduction

In today’s rapidly evolving era, the logistics industry is undergoing profound transformation. From its early days of manual operations and conventional transportation to the integration of cutting-edge technologies, the sector continues to advance. Concepts such as informationization, digitalization, intelligentization, data‑intelligence, and smart logistics have emerged in succession—each not only signifying technological upgrades but also driving innovation in operational models and management paradigms. Centered on the development of smart logistics, a thorough examination of the distinctions and interconnections among these concepts, along with an analysis of the evolutionary pathways and trends of smart logistics systems across different stages, is of great significance for the industry in shaping its future direction and enhancing its competitiveness. This approach not only helps logistics enterprises optimize operations, reduce costs, and improve service quality, but also propels the entire sector toward higher standards, enabling it to meet the emerging demands of economic and social development.

02  An Analysis of the Connotations of Informatization, Digitalization, Intelligentization, Digital Intelligence, and Wisdomization

(1) Informatization: The Foundational Building Blocks of Logistics Information
Informationization is the process of organizing, processing, transmitting, and utilizing various information resources through information technologies such as computers, communications, and networks. In the logistics sector, the core of informationization lies in establishing information systems to enable the recording, storage, transmission, and sharing of logistics information. It can be said that modern logistics emerged alongside the development of information technology. In ancient times, there was no concept of logistics; only fragmented functions such as warehousing and transportation existed. The integration of information has enabled end-to-end communication across the entire logistics chain, facilitating planning and control, and linking previously isolated operational activities into a cohesive system—thus giving rise to modern logistics. Moreover, modern logistics continues to evolve and transform in tandem with advances in information technology. For example, enterprises have developed logistics management information systems ( LMIS ), encompassing modules such as order management, inventory management, and transportation management. The order management module enables real-time tracking of order creation, modification, and shipment status; the inventory management module provides precise monitoring of stock levels and inbound/outbound records; and the transportation management module allows for tracking of cargo routes, estimated arrival times, and other relevant information. Through the coordinated operation of these modules, enterprises can maintain real-time visibility into every stage of the logistics process, facilitating the seamless flow of information across internal departments and with external partners, thereby enhancing the efficiency and accuracy of logistics operations. Informationization focuses on digitizing business processes, relying primarily on computer systems and network technologies, emphasizing data recording and computation, and seeking to accelerate and optimize workflows based on existing business logic.

(II) Digitalization: The Digital Twin of the Physical Logistics World

Digitalization is the process of converting analog signals or complex, dynamic information into digital form, representing an advanced stage of informatization. The fundamental distinction between informatization and digitalization lies in whether logistics‑automation systems can automatically collect and process information. With the widespread adoption of IoT technologies, when logistics‑system machines are capable of autonomously gathering and handling data, informatization advances to the digitalization phase. In the logistics sector, digitalization entails transforming various types of information—such as cargo attributes, the status of transport vehicles, and warehouse layouts—into digital formats for storage, processing, and transmission. For example, paper-based logistics documents can be converted into electronic formats, and sensors can transform physical parameters such as cargo location, temperature, and humidity into digital signals. Through digitization, logistics information can be processed and analyzed by computers more efficiently, enabling precise replication and widespread sharing of data. Digitization places greater emphasis on data analysis and mining; by leveraging advanced techniques like data mining and machine learning, it provides a robust data foundation for subsequent intelligent decision-making and business optimization.

(3) Intelligence: Autonomous Execution of Logistics Decisions

Intelligentization is the process by which advanced algorithms and artificial intelligence technologies are introduced, enabling machines or systems to autonomously learn, analyze, and make decisions—this is precisely what distinguishes digitalization from intelligentization. When a system reaches the digitalization stage but still requires human decision-making after digitizing its information, it remains at the digitalization level; only when the machine system can participate in decision-making does it signify that the system has entered the intelligentization phase. In logistics applications, intelligentization manifests across multiple dimensions. For example, in smart warehousing systems, automated guided vehicles (AGVs)… AGV ), it can autonomously plan its travel route and perform cargo-handling tasks based on pre‑set programs and real‑time environmental data; the intelligent sorting system leverages image‑recognition technology and robotic arms to sort and classify goods quickly and accurately; and the intelligent transportation‑dispatch system automatically optimizes delivery routes and vehicle‑allocation plans in response to real‑time traffic conditions, vehicle status, and order requirements. Intelligence endows machines or systems with perceptual capabilities, memory and reasoning abilities, learning and adaptive capacities, and decision‑making skills. By using intelligent technologies to optimize and restructure business models and service delivery, it embodies the self‑evolution of technology and represents a higher‑level application.

(4) Digital Intelligence: The Deep Integration of Data and Intelligence

Digital intelligence represents the deep integration of digitization, informationization, and intelligentization. Building on a digital foundation, it leverages advanced algorithms to conduct in-depth analysis, interpretation, and utilization of data, thereby achieving digital intelligence. At the same time, it digitizes human knowledge and expertise, embedding it into machine systems to support decision-making, ultimately realizing the seamless convergence of digital intelligence and intelligent digitization—this is what we call digital intelligence. In the logistics sector, digital intelligence emphasizes data-driven intelligent decision-making and business optimization. For example, e‑commerce logistics companies perform extensive mining and analysis on hundreds of millions of records—covering customer purchasing behavior, product sales, and logistics‑delivery data—and employ machine learning algorithms to forecast product demand across different regions and time periods. This enables them to proactively adjust inventory placement and optimize delivery routes. Digital intelligence goes beyond mere data transformation and organization; it places particular emphasis on in-depth data exploration and intelligent decision-making, turning raw data into valuable insights and knowledge, and using these insights to inform decisions and actions, thus driving operational processes that are both efficient and smart.

(5) Intelligentization: Comprehensive Coordination of the Logistics Ecosystem

Intelligentization represents the advanced stage of logistics industry development; it goes beyond the mere application of technology to encompass a new mindset and the creation of an integrated ecosystem. Smart logistics leverages intelligent technologies and tools—such as big data, cloud computing, and smart hardware—to comprehensively enhance the logistics system’s capabilities in systemic thinking, perception, learning, analytical decision-making, and intelligent execution. This drives a quantum leap in the system’s level of intelligence and automation, enabling it to engage in self‑learning and continuous improvement. Smart logistics is characterized by interconnectedness, data‑driven operations, deep collaboration, and efficient execution. All logistics components are interconnected and digitized, with… “Data” drives all insights, decisions, and actions; it enables deep collaboration across groups, enterprises, and organizations, leveraging globally optimized intelligent algorithms to orchestrate efficient division of labor and coordination among all stakeholders in the logistics system. For example, within a smart logistics ecosystem, suppliers, manufacturers, logistics providers, retailers, and consumers are tightly connected through a unified information platform, enabling real-time data sharing and coordinated operations. This allows each party to respond swiftly to shifts in market demand, jointly optimize supply-chain processes, and enhance overall performance.

03  The Evolutionary Path of Smart Logistics Systems Across Different Stages

(1) The Informationization Stage: Establishment and Widespread Adoption of Logistics Information Systems

During the logistics informatization phase, companies primarily focused on building logistics information systems. Early logistics information systems were relatively simple, with functions mainly centered on order processing and inventory management. As technology advanced, transportation management systems ( TMS ), Warehouse Management System ( WMS ) and others have gradually become widespread. These systems have digitized logistics business processes, enhancing the speed and accuracy of information transmission. For example, by… TMS With this system, enterprises can track the real-time status of shipments and promptly adjust their transportation schedules. WMS The system can effectively manage warehouse inventory storage and inbound/outbound operations, thereby improving the utilization of storage space. The informationization stage laid the data foundation for the logistics industry, enabling logistics enterprises to record and conduct preliminary analyses of business data, thus supporting subsequent development. However, at this stage, logistics systems primarily amounted to electronic replicas of traditional business processes, lacking in-depth data mining and intelligent applications.

(II) Digitalization Phase: In-depth Mining and Application of Logistics Data

As the logistics industry enters the digital era, companies are increasingly focusing on in-depth data mining and application. On one hand, a growing array of sensors and IoT devices has been deployed across logistics operations, enabling comprehensive data collection. For example, sensors are installed on transport vehicles… GPS Positioning devices, temperature sensors, humidity sensors, and other IoT-enabled equipment can collect real-time data on vehicle location and cargo‑transport conditions. In warehouses, smart shelving and electronic tags are deployed to enable precise inventory management. Meanwhile, enterprises leverage big data…

(3) The Intelligentization Stage: Automation of Logistics Operations and Autonomous Decision-Making

The intelligentization stage is a pivotal phase in the development of smart logistics, during which logistics operations achieve automation and autonomous decision-making. In the warehousing segment, automated sorting equipment, AGV Automation technologies, such as robotic arms, are now widely deployed, significantly enhancing the efficiency and accuracy of warehouse operations. In the transportation phase, intelligent dispatch systems automatically determine optimal routes based on real-time traffic conditions, vehicle status, and order information, enabling smart vehicle allocation. Some cutting-edge logistics companies are also exploring the application of autonomous driving technologies in freight transport, further improving safety and efficiency. Moreover, machine learning and artificial intelligence are extensively utilized for logistics forecasting and risk early warning. By leveraging machine-learning algorithms to analyze vast amounts of logistics data, predictive models can be developed to anticipate demand, detect equipment malfunctions, and other potential issues, thereby supporting informed decision-making. This stage of intelligentization allows logistics systems to autonomously sense, analyze, and make decisions, reducing reliance on human intervention and elevating the overall level of operational intelligence.

(4) The Digital Intelligence Phase: Intelligent Optimization and Coordination Across the Entire Logistics Process

The digital‑intelligence phase emphasizes intelligent optimization and coordination across the entire logistics process. In this stage, logistics enterprises build integrated smart logistics platforms that achieve comprehensive data integration and sharing. Leveraging big data, artificial intelligence, cloud computing, and other technologies, these platforms enable real-time monitoring and intelligent analysis of end-to-end logistics operations, thereby optimizing resource allocation and enabling smart collaboration throughout business processes. For example, in supply chain collaboration, a digital‑intelligent logistics platform can capture real‑time data on inventory levels, production schedules, and transportation status from suppliers, manufacturers, logistics providers, and retailers. By leveraging advanced algorithms for analysis and optimization, it enables seamless coordination across all supply chain stages, reducing inventory costs and enhancing overall operational efficiency. In customer service, natural language processing technologies and intelligent customer‑service systems facilitate rapid response to inquiries and complaints, thereby boosting customer satisfaction. The digital‑intelligent transformation stage empowers logistics enterprises to transition from traditional logistics to smart logistics, strengthening their core competitiveness.

(5) The Intelligentization Phase: Building a Smart Logistics Ecosystem

The intelligentization stage represents an advanced phase in the development of smart logistics, aiming to establish a fully integrated, collaboratively coordinated, and highly efficient smart logistics ecosystem. Within this ecosystem, logistics enterprises, suppliers, manufacturers, retailers, financial institutions, government agencies, and other stakeholders are tightly interconnected through digital platforms, enabling real-time information sharing and deep operational collaboration. For example, blockchain technology ensures the immutability and traceability of logistics information, thereby strengthening trust among all parties; smart contracts automate the execution of contractual terms in logistics transactions, enhancing both efficiency and security. The smart logistics ecosystem also prioritizes environmental sustainability, reducing the environmental footprint of logistics operations through the adoption of new‑energy technologies and optimized packaging solutions. Moreover, by adapting to evolving market demands and technological advancements, the smart logistics ecosystem continuously refines itself and drives innovation, fostering high‑quality development in the logistics sector.

04  Trends in the Development and Transformation of Smart Logistics Systems

(1) Trend of Technological Convergence: Multi‑technology Collaboration Drives Innovative Development in Smart Logistics

In the future, smart logistics systems will exhibit a development trend characterized by the convergence of multiple technologies. Big data, artificial intelligence, the Internet of Things, cloud computing, blockchain, and other technologies will work in synergy to drive innovative advancements in smart logistics. Big data provides AI with abundant data resources, enabling it to learn from and analyze diverse patterns and trends in logistics operations, thereby facilitating more accurate forecasting and decision-making; the Internet of Things enables comprehensive sensing and interconnectedness among logistics equipment and goods, laying the groundwork for big‑data collection and AI applications; cloud computing delivers robust computational power for storing and processing massive volumes of logistics data; and blockchain ensures the security and trustworthiness of logistics information, fostering collaborative cooperation among all stakeholders. For example, in smart warehousing, IoT technologies enable real-time sensing of goods and equipment; big data analytics optimize warehouse layout and storage strategies; AI facilitates intelligent scheduling and coordinated operations of automated systems; and blockchain ensures the secure sharing of warehouse information. This trend toward multi‑technology integration will make smart logistics systems even smarter, more efficient, and more secure.

(II) Green Development Trends: Sustainable Principles Integrated Throughout the Entire Smart Logistics Process

As global attention to environmental protection continues to grow, green development will become a key trend in the evolution of smart logistics systems. Smart logistics will integrate sustainable‑development principles across all stages—ranging from the selection of transport vehicles and the design of logistics packaging to the construction of logistics facilities—steering toward environmentally friendly practices. In the transportation sector, new‑energy vehicles—such as electric trucks and hydrogen fuel‑cell trucks—will see broader adoption to cut carbon emissions; meanwhile, intelligent dispatching and optimized routing will help reduce energy consumption. In logistics packaging, the use of biodegradable and recyclable eco‑friendly materials will be promoted to minimize environmental pollution from packaging waste; artificial intelligence will be leveraged to refine package designs, enabling material lightweighting and thereby lowering both packaging costs and resource consumption. In logistics infrastructure development, energy‑efficient equipment and technologies will be deployed to enhance energy‑use efficiency, while green logistics parks and warehouses will be built. This trend toward sustainability not only aligns with societal development needs but will also provide logistics companies with new competitive advantages.

(3) Trend toward Personalized Services: Meeting Customers’ Diverse Logistics Needs

The intensifying market competition and the growing diversification of customer needs have made personalized services an inevitable trend in the development of smart logistics systems. Leveraging big data analytics and artificial intelligence, smart logistics systems will gain deep insights into customers’ requirements and preferences, enabling them to deliver tailored logistics solutions. For example, for e‑commerce customers, personalized warehousing and delivery services—such as priority delivery, scheduled delivery, and in‑home installation—are offered based on sales data and customer reviews. For manufacturing enterprises, tailored logistics‑supply chain management solutions are provided, taking into account production schedules and supply‑chain characteristics, with optimizations across stages including raw‑material procurement, production logistics, and finished‑goods distribution. Moreover, smart logistics systems leverage intelligent customer service and feedback mechanisms to promptly capture evolving customer needs, enabling continuous adjustments and refinements to service offerings and enhancing overall customer satisfaction. This trend toward personalized services empowers logistics providers to better meet customer expectations, strengthen loyalty, and bolster their competitive edge in the market.

(4) Globalization Trend: Smart Logistics Facilitates the Coordinated Development of Global Supply Chains

As economic globalization continues to deepen, smart logistics systems will increasingly adopt a globalized development trajectory. Smart logistics will transcend geographical boundaries, enabling the integration of logistics resources and coordinated operations on a worldwide scale, thereby fostering the efficient and collaborative evolution of global supply chains. Logistics enterprises will establish global logistics networks and information platforms to facilitate cross-border transportation, warehousing, and last-mile delivery. By leveraging big data and artificial intelligence, they will optimize the layout and operations of global supply chains, enhancing responsiveness and flexibility. For instance, smart logistics platforms enable real-time monitoring of shipment statuses and inventory levels worldwide, allowing for timely adjustments to supply chain strategies based on market demand. Meanwhile, blockchain technology fosters transparency and trust by enabling secure sharing of supply-chain information, thereby streamlining international trade. The trend toward globalization will empower smart logistics firms to allocate resources globally, expand into new markets, and strengthen their international competitiveness, while also driving the integrated development of the global logistics industry.

(5) Talent Demand Trends: Cultivating Versatile, Smart Logistics Professionals

The development of smart logistics systems is creating new demands for talent, and cultivating multidisciplinary professionals in the field of smart logistics will become a key trend in the future. Smart logistics spans multiple domains, including logistics operations, information technology, artificial intelligence, and data analytics, requiring versatile experts who not only understand logistics processes but also possess relevant technical expertise. These professionals must not only be well-versed in logistics operations and management practices but also proficient in applying cutting-edge technologies such as big data analytics, artificial intelligence algorithms, and the Internet of Things, enabling them to leverage technological solutions to address real-world logistics challenges. To meet this demand, universities and vocational education institutions will strengthen the development of relevant programs and curricula, cultivating specialized talent capable of supporting the evolution of smart logistics. Meanwhile, logistics companies will intensify employee training to enhance both technical expertise and operational capabilities. In addition, firms will proactively recruit cross-disciplinary specialists, assembling diverse teams to drive innovation and advancement in smart logistics.

05  Conclusion

In the evolution of smart logistics systems, informatization, digitalization, intelligentization, digital‑intelligence integration, and wisdom‑driven transformation are both distinct and closely interconnected, advancing in a progressive, layered manner. Starting with the establishment of logistics information systems during the initial phase of informatization, moving on to the deep mining of logistics data in the digitalization stage, then to the automation of logistics operations and autonomous decision‑making in the intelligentization phase, followed by the digital‑intelligence integration stage that achieves intelligent optimization and seamless coordination across the entire logistics process, and finally culminating in the wisdom‑driven stage—where a fully coordinated, smart logistics ecosystem is established—each phase has ushered in a qualitative leap for the logistics industry.
Looking ahead, smart logistics systems will continue to advance along several key trends: technological integration, green development, personalized services, global expansion, and the cultivation of multidisciplinary talent. Technological convergence will drive innovation in smart logistics; the principle of green development will permeate every stage of the logistics process; personalized services will meet customers’ diverse needs; global collaboration will strengthen supply-chain coordination worldwide; and a pool of versatile professionals will provide the intellectual foundation for the sector’s growth. Logistics enterprises should stay attuned to these trends, proactively adopt cutting-edge technologies, streamline operational workflows, and invest in talent development—thus adapting to market shifts and competitive pressures, achieving sustainable growth in the new era of smart logistics, and making greater contributions to economic and social progress.