Each year, we present the logistics trends that we believe will impact the industry in the coming year. An important aspect in 2025 is the increasing predictive quality of IT systems, which will improve planning and scalability. However, more digitization also makes companies more vulnerable: this turns cybersecurity into an important trend – especially for a critical industry like logistics.
Current Trends in Logistics: What Will Drive Developments in 2025 and the Near Future?
The technological trends in logistics may not have changed fundamentally in recent years, but they have changed significantly in one respect. In addition to digitization in general, the megatrend of recent years has been artificial intelligence (AI). Today, we can say that AI is no longer a separate trend, but an indispensable component of almost all logistics trends. Apart from sustainable fuels, no other trend in our overview is independent of digitization and AI. This also means that AI has long since arrived in the day-to-day operations of many players in the logistics industry.
Given the ongoing geopolitical crises, another key issue that has not diminished in importance is the resilience of supply chains. This is where we come full circle, as AI in particular is an effective lever for strengthening resilience.
Climate change and sustainability have somewhat taken a back seat in the public debate, but this does not change the fact that sustainable management is a prerequisite for a future-proof (economic) world. Many of our trends also contribute to sustainability by increasing efficiency. Ultimately, this benefits everyone: the environment, people, and businesses.
Sustainable Fuels and Electromobility
Sustainable drive solutions will remain a trend until the transition to low-emission road freight is complete. This is especially true for companies in the EU, where the European Parliament and member states have set clear emission reduction targets in early 2024. Commercial vehicles over 7.5 tons delivered from 2030 onwards must reduce their carbon emissions by 45% between 2030 and 2034 compared to 2019. Further tightening is planned for 2035 (65%) and 2040 (90%).
Low-emission fuels such as (bio)LNG, (bio)CNG, and HVO provide a promising interim solution because these alternative fuels can reduce emissions in the short term. This makes them valuable as a bridging technology – although they do cause direct emissions (albeit lower).
The situation is different for electric mobility, which produces no direct emissions, making it particularly attractive in urban traffic. Battery-electric vehicles are commonplace in last-mile and distribution logistics. In long-haul transportation, they are still a rarity in most countries.
This could change, as the offer of high-performance vehicle models with ranges beyond the 500-kilometer mark is growing. This means that electric mobility can already be an option for medium- and even long-distance road freight in the short term. What logistics companies cannot achieve on their own, though, is a sufficient European network of fast-charging stations. Only then will the trend toward electric mobility in logistics gain momentum.
Artificial Intelligence for Route Planning
Humas are good at planning routes. But in the age of e-commerce, with ever-smaller but ever-more transport units, this is becoming more and more challenging – which destinations should be reached in which order may be easy to answer for full loads, but for combined shipments the answer is a complex decision-making process. This makes the use of AI in route planning a key trend.
AI-based route planning uses data on resources (such as personnel, vehicles, transport capacity) or on traffic and weather as a basis for calculation. It can accelerate and optimize route planning and adjust the choice of the appropriate mode of transportation accordingly. In addition to the predictive capabilities of machine learning, AI can quickly process real-time information. This allows for greater route flexibility. Networked AI systems integrate control centers, vehicles and routes, and have access to all relevant traffic information in real time. They can respond to problems and suggest route changes.
AI-optimized route planning is a major driver of greater efficiency and sustainability in transport logistics by making the best possible use of vehicles, fuel, and personnel.
Forecast for Logistics Planning with AI
Not just route planning, but the planning of all logistics processes is being improved by the predictive capabilities of AI. Machine learning models that can analyze complex data sets and recognize patterns beyond human capabilities have significantly improved the accuracy and timeliness of forecasts. Forecasting is critical to logistics and supply chain management when it comes to operational efficiency, customer satisfaction, sustainability, and strategic planning.
Financial forecasts as well as models predicting consumer behavior and demand peaks enable logistics companies to anticipate market trends, dynamically adjust prices, and efficiently allocate resources. Forecasting also increases the resilience of the supply chain; for instance, by anticipating weather patterns, the effects of climate change, or natural disasters. Logistics strategies can then be adjusted, shipments rerouted, or alternative sources of supply secured.
AI-powered analytics also include geopolitical and social factors, such as the likelihood of strikes or political instability. Predictive models can also analyze social media sentiment and political news to foresee disruptions and facilitate proactive measures.
Logistics depends on external factors that are beyond the control of logistics companies, but can be anticipated. The trend is that AI predictions will increasingly support demand and process planning in logistics.
Autonomous Robots for Warehouse Work
Advances in AI and the Internet of Things (IoT) have greatly expanded the use of robots in warehouse logistics. Robotic solutions play a critical role in warehouse automation. Machine learning is empowering robots to navigate more autonomously and communicate with shelves and cartons via IoT. In order fulfillment, robots, in conjunction with AI, are helping to provide real-time information for inventory management to accurately estimate delivery times.
The variety of warehouse robots includes robotic picking assistants, pick and place robots, sorting robots, packing robots, autonomous transport vehicles, and drones. The move to warehouse robotics and automation is particularly important in markets with high labor costs. In addition, rising customer expectations for faster order fulfillment are leading to increased use of robotics.
Multimodal Solutions for Greater Resilience
Road, rail, and sea and inland waterway transport constitute the backbone of the logistics industry. Multimodal transport refers to the change of means of transport during the movement of goods. Multiple modes of transport are used to cover all stages of a shipment, from the first mile to the last mile.
Multimodal transport concepts represent one of the four dimensions of supply chain diversification. Volatility and disruption threaten supply chains. Dependence on a single source of supply, a single trade route, or a single mode of transport increases risk. Changing the mode of transport is sometimes trivial: if goods are transferred to trucks at (air) ports, train stations, or logistics centers, this is considered multimodal. Ideally, however, a multimodal transport solution combines the advantages of each mode to provide the most efficient and sustainable logistics chain. This diversifies transport routes and reduces the risk of breakdowns.
New technological perspectives are turning multimodality into a trend: with the help of modern analysis tools, the efficiency of multimodal transport can be individually determined for companies. This includes analyses of cost savings, energy consumption, or carbon emissions. It is important to integrate the flow of information and goods and to increase the flexibility of the shipping process. For freight traffic, this means less predefined but increasingly flexible supply chains that can be modified during the transport (see above, Artificial Intelligence for Route Planning). This will be achieved by using integrated software tools and new business and collaboration models in logistics.
Intelligent Packaging
Packaging technology also accelerates logistics processes such as automated shipment entry, monitoring, and tracking. Smart packaging transmits location and progress data, enabling seamless monitoring of the delivery process. To this end, smart packaging integrates hardware components such as time-temperature indicators (TTI), freshness and ripeness sensors, and radio frequency identification (RFID) and other tags.
This trend is particularly focused on the interface between content and packaging. Progress is expected in this area, especially in terms of quality control and protection of the transported goods.
Digital Freight Documentation
Electronic waybills, bills of lading, and customs documents are as much a necessity in logistics as electronic health records are in healthcare. The manual creation of documents is prone to errors and a waste of resources such as time, personnel, and materials. Electronic documents help logistics companies work more efficiently, reduce errors, promote connectivity among supply chain participants, and increase transparency. Shippers, carriers, and warehouse personnel can all access documents in real time. This accelerates process handling and permits immediate adjustments in the event of disruptions at any link in the supply chain.
Cloud-Based Document Management
Speaking of networking, transparency, and electronic documents: the trend toward digitization in document management extends beyond freight documentation. Real-time access to all relevant documents for all stakeholders is best achieved through cloud-based document management systems that automatically adjust for status changes.
The cloud is the central storage location and shared access point for all documents and information. Complex and/or international supply chains with many participants benefit especially from cloud solutions. It is important to have sophisticated security protocols, continuous updates, and advanced encryption technologies (see below, Cybersecurity). Cloud solutions also offer financial savings for logistics companies by allowing storage capacity to be scaled on demand and local server infrastructures to be downsized.
Process Mining
Process mining is a data analysis technique used to visualize and exploit process data that is automatically collected in existing IT systems. Special algorithms are applied to event log data to identify patterns, trends, and details in the process flow. Typical examples of this type of data, which is collected anyway in logistics, are order processes, delivery times, storage and transportation costs, profit margins, or human and vehicle resources.
Process mining reconstructs and visualizes real process flows based on this data to uncover opportunities for improvement. Since process optimization is the core of many logistics goals – be it efficiency, cost reduction, or sustainability – process mining is an important part of the overall trend towards digitization.
Cybersecurity
Cybersecurity is a highly relevant trend. Due to their critical role, logistics networks are a prime target for cyber attacks. The integration of new digital technologies comes with new risks. Throughout the supply chain, technological advances in generative AI, quantum computing, etc. are posing serious challenges to traditional protection and encryption methods. The increase in huge data sets through the implementation of IoT offers intruders large amounts of data to sell or exploit. In addition, the expanding use of digital infrastructure and its interconnectivity makes previously isolated assets vulnerable to attack.
Just as AI and automation are allowing logistics companies to operate more efficiently, cybercriminals are using these capabilities to launch attacks that are harder and harder to detect and defend against. The next generation of smart applications thus requires a new generation of security solutions, a Cybersecurity 2.0 – including protection, detection, and response tools that not only prevent attacks, but also deploy AI and other advanced technologies and methodologies to actively predict, autonomously detect, and respond to attacks.
Cyberattacks typically target the weakest link in the supply chain and can cause a chain reaction. Therefore, not only cybersecurity teams, but everyone involved in logistics needs to be vigilant. Key risks include ransomware, AI attacks, malware, denial of service, manipulation and disruption of information, and attempts to manipulate employees into disclosing confidential information (known as social engineering).
Future Logistics Trends
Let‘s be honest: For some of the following points, many people (we’re not excluding ourselves) might have thought they would have been implemented faster. Sometimes technical issues are the main obstacles, sometimes approval problems also contribute.
Nevertheless, these trends could help mitigate the effects of a worsening labor shortage in the future or make processes more flexible.
The following trends are important for the future of logistics, but will probably not be implemented in the short term:
- autonomous vehicles for delivery in public space
- autonomous delivery drones in public airspace
- blockchain technology along the entire supply chain
- broad application of 3D printing technology: for example, for decentralized production in consumption centers to shorten delivery routes
AI Is Driving Innovation
Forecasting, planning, scaling, resilience, efficiency, sustainability: AI can help in each of these areas. Hardly any trend in logistics is independent of AI, which underscores its importance. However, increasing digitization also brings the importance of cybersecurity into focus. Sustainable drive solutions also remain on the trend radar. Here, the latest technical developments on the manufacturer side could prove to be a driving force, but only if the charging infrastructure follows suit.
