Convenient travel, and smooth logistics, embracing a digital, intelligent future together

Artificial Intelligence (AI) is sweeping the globe, becoming a driving force behind the new round of technological revolution and industrial transformation. It is poised to have a profound impact on global economic and social development as well as human civilization, fundamentally reshaping traditional modes of daily life, including how people work and study, while accelerating the digital and intelligent evolution of countless industries.

In the midst of profound restructuring of global supply and industrial chains, digital technologies—including 5G, cloud computing, big data, the Internet of Things (IoT), and especially AI—are being applied more rapidly across various industries, significantly enhancing productivity. The digital economy has emerged as the primary engine of global economic growth, with digital strategies being formulated and implemented in many countries.

Yet challenges remain: how to stimulate demand, build the right infrastructure, and measure effectiveness? As global digitalization and intelligent transformation accelerate, how to leverage ICT infrastructure to build a high-quality and sustainable digital economic system has become a strategic issue of shared concern for governments worldwide.

Data + AI: driving the transportation industry toward a diversified, highly integrated new era

The transportation industry is a fundamental, pioneering, strategic, and critical service sector. The deep application of digital and intelligent technologies will further integrate physical and digital transportation and logistics activities, thereby accelerating comprehensive transformation and upgrading within the industry.

Hub nodes such as ports, airports, railway stations, and border are evolving from single-purpose points into integrated platforms, like port-industry-city complexes, airport-city integrations, sea port-city free zones, and station-city complex. Highways, railways, metros, and urban road networks are rapidly converging, enabling collaboration in planning, transportation, services, management, and information across different modes of transport. The development of the road-network economy, corridor economy, and low-altitude economy has become a widespread aspiration, which, if realized, will promote the sustainable growth of the transportation industry.

Transportation networks connect hubs, facilitating passenger and freight flows. Advancing the reform of comprehensive transportation systems, establishing modern logistics enterprises, hub systems, and next-generation service networks has become crucial to reducing overall costs. Promoting combined rail-water, road-rail, and air-rail transport, realizing "one-order" and "one-container " intermodal transport, and improving the digitalization and intelligence of logistics and warehousing will further contribute to cost savings.

Four key aspects of digital transformation in transportation

The digital shift in transportation is not only reshaping business flow and improving service experience, but also optimizing TCO and creating new business models. Four aspects of this shift merit particular scrutiny: strategy, data, intelligence, and talent.

Strategy: the foundation. The adoption of AI in transport should be driven by strategy, not just by technology. Digital transformation is about using new ways of thinking to restructure systems and reengineer processes. By embedding digitalization into long-term strategy, transport operators can achieve sustainable high-quality growth.

Data: the bedrock. Without data, AI cannot exist. Transport systems need comprehensive connections and real-time feedback loops to make infrastructure and operations visible and measurable. Only then can management decisions be data-driven. Creating high-quality datasets specific to transportation ensures that AI can deliver reliable, repeatable value at scale.

Intelligence: the direction. AI represents both a contemporary challenge and a revolutionary opportunity in transportation. AI’s integration into transportation can already be seen in ports, airports, railways, and roads, which are using AI-driven models to optimize operations. Generative AI, in particular, is prompting organizations to rethink entire processes.

Talent: the core. None of the above is possible without skilled people. Cross-domain talent is essential: individuals who understand both transport operations and digital technologies. These professionals can design, implement, and refine solutions that bridge engineering, business, and technology, ensuring continuous innovation.

The “Four-in-One” approach

In transportation, adopting AI is no longer optional—it is a necessity for growth, sustainability, and resilience. The real question is not “Should we use AI?” but rather, “How can AI reshape the foundation of safety, efficiency and green development?” This marks a leap in industry cognition, evolving from technical mindset to strategic mindset that reshapes industrial logic systematically.

To address this, Huawei has developed a “Four-in-One” philosophy that integrates scenarios, computing power, algorithms, and data. We emphasize starting from business scenarios, adhering to a problem-oriented and goal-oriented approach, and driving AI into business scenarios and production systems.

——Scenarios are the starting point. Beginning with high-value scenarios such as port scheduling, airport operation, urban congestion governance, and giving high priority to massive, repetitive and complex operations like ship berthing, equipment maintenance, and signal control. From these points, AI can expand to broader systems, multiplying its benefits.

——Computing power underpins everything. A unified, secure, and reliable AI infrastructure is needed to ensure real-time, mission-critical operations such as port IGV dispatching, runway inspections. By providing digital infrastructure, computing power, AI development platform and toolchains, it can ensure to issue ship detention warning within 3 seconds, 0 interruption of road pavement inspection, etc. Architectures must also be resilient enough to adapt to rapid technological shifts.

——Algorithms turn expertise into practice. Transport challenges—like traffic signal optimization or railway fault detection—require the fusion of traditional engineering knowledge with AI’s predictive capabilities. By leveraging domain-specific models enhanced with AI agents, the industry can coordinate decision-making across intersections, vehicles, railways, and even airspace.

——Data sets the limits. High-quality data, standardized and secure, is essential to unlocking the full value of AI. Multimodal inputs such as radar, GPS, and sensor data must be consolidated into unified data lakes, where they can be curated for trustworthy AI training and deployment.

AI in action: building the digital foundation for comprehensive transportation infrastructure and logistics services

Huawei has begun implementing this “Four-in-One” philosophy across sectors, developing a full-stack AI capability architecture. This includes computing resources, frameworks, platforms, and both large and specialized models. The system is designed not only for today’s needs but also for future adaptability, avoiding redundant investment while maintaining compatibility with existing infrastructure. Importantly, the framework is open and collaborative, developed alongside industry partners.

The most compelling proof of AI’s transformative potential lies not in theory, but in practice. Across highways, ports, railways, airports, and logistics, Huawei is driving real-world digital transformation at scale—redefining how critical infrastructure is built, managed, and optimized.

On highways, AI computing power is driving the integration of construction, management, and operations. Traditional large-scale infrastructure is evolving toward large-scale operation and maintenance. Huawei’s highway large model, trained on full-scenario datasets, achieves more than 95% accuracy in predicting traffic flow, speed, and congestion. This supports corridor economies, reduces congestion, and makes networks safer and more efficient.

In ports, AI models are transforming hub operations. Huawei’s port large model, built from millions of samples across 80 subcategories, delivers major efficiency gains: a 15% increase in small-sample accuracy, an 80% reduction in labeling workload, and the ability to reuse models across different terminals. The result is safer, faster, and more reliable port operations.

For railways, AI is reshaping safety and maintenance. Huawei’s TFDS (Trouble of Moving Freight Car Detection System) uses a large-scale railway model to detect more than 430 types of faults across 70 vehicle types with over 99.3% accuracy. Critical issues are identified without missed reports, and image review efficiency has increased by 200%. During intelligent scheduling, maintenance efficiency is increased by 30%, manual workload for Level-1 maintenance is reduced by 50%. While perimeter protection achieves 0 omissions and errors, and inspection efficiency is improved by 50%. Huawei reshapes the closed loop of perception, decision-making, and execution through AI, providing a digital foundation to improve passenger and cargo transport safety and efficiency.

At Airports, AI drive the refinement of flight operations. In the case of the global surge in air passenger and cargo traffic, Huawei has applied AI algorithms to automate 26 manual data collection nodes, achieving 98% accuracy, a time error of less than 30 seconds and 100% process visualization. In return, the abnormal rate has dropped by 80%, and the daily abnormal aircraft handling has decreased from 10 to 2.

In logistics, documentation remains a critical pain point. Customs forms, packing lists, and shipping documents come in many formats and languages, often degraded by stamps or handwriting. Leveraging advanced AI-driven recognition technology, the company has pushed document recognition accuracy above 90%, reducing manual entry by 90% and cutting processing time to just a few minutes. This leap has a direct impact on supply chain efficiency and customer service.

The road ahead: scaling smart infrastructure globally

The scale of Huawei’s deployment speaks volumes. Its intelligent transportation and logistics technologies now power more than 100 ports, 200 logistics companies, 300 urban rail systems, 180,000 kilometers of railway, 200,000 kilometers of highways, and 210 airports worldwide.

From local city transit systems to the arteries of global trade, AI is no longer an emerging trend—it’s the foundation of modern infrastructure. It’s enabling safer, more efficient, and more sustainable transportation journeys.

Looking forward, Huawei is doubling down on its commitment to both real-world business needs and cutting-edge technological innovation. By deepening collaboration with industry partners and clients, the company is focused on building a robust digital foundation for safe and efficient supply chains and industrial networks. The long-term vision is tangible: Convenient Travel, and Smooth Logistics, Embracing a Digital, Intelligent Future Together.