Companies in the logistics sector, which is one of the most important elements of the global economy, are at a moment of key technological transformations. Innovations, including the development of artificial intelligence (AI), are the response to current challenges.
Its application allows for improved decision-making, increased efficiency, and reduced operational costs. Besides AI, technologies such as the Internet of Things (IoT), blockchain, and the development of autonomous vehicles contribute to creating more integrated and efficient supply chains.
What is Artificial Intelligence (AI)?
Its application involves building computer systems that can perform tasks requiring thought processes very similar to human ones. Specifically, these include:
Learning, i.e., acquiring knowledge, understanding the principles of using data and information,
Reasoning, which involves using principles to draw approximate or definitive conclusions,
Self-correction, understood as validating the results of reasoning and drawing conclusions to make the reasoning more correct or of higher quality.
This mode of operation allows, among other things, for machines to understand natural (human) language, recognize patterns (e.g., in data), analyze images or voice, and make decisions based on data and make predictions.
The main advantage of artificial intelligence over existing solutions is the self-correction process. It is a mechanism that continuously improves the quality of results. Previous outcomes of a given AI tool simultaneously serve as material for further learning and reasoning.
Major challenges in the logistics industry
Supply chain disruptions stem from their complexity, involving many countries and stakeholders. Additionally, intense economic changes, increasingly frequent geopolitical tensions, and trade disputes are often sources of additional complications and constant changes.
Environmental pressure forces logistics companies to adopt more ecological (and thus more expensive) solutions to reduce their carbon footprint and meet the growing ecological awareness of their customers.
High operational costs, especially generated in the last mile of delivery but also by international and intercontinental transport, are most often due to rising fuel prices and labor costs.
Inventory management - variability in consumer demand, continuous development of e-commerce, and an unstable economic situation have led to unpredictable demand patterns. This complicates inventory management and can lead to excesses or shortages in warehouses and inefficiencies in transshipment centers.
City congestion and diverse delivery locations pose a significant logistical obstacle and have a significant impact on the speed and predictability of delivery and cost levels.
Customer expectations have significantly increased recently. The COVID-19 pandemic greatly popularized shopping and orders requiring delivery to individual customers. With this, they began to expect faster and more reliable deliveries with the possibility of real-time tracking.
AI in logistics
Many challenges can be addressed through innovations related to the application of artificial intelligence.
They can be used as follows:
Early warning systems
By analyzing huge amounts of historical and current data, AI algorithms can predict and recommend responses to potential disruptions. This data can come from many sources and concern situations in various product segments and geographical areas. For example, in the case of risks such as demand shocks or supply shortages, AI-supported software can suggest alternative supply sources or develop solutions to minimize losses (a compromise between many factors).
Route planning and scheduling
Based on identified patterns of shipment movements, delivery sizes, vehicle availability, containers, or shipload capacities, AI-supported systems can develop optimal schedules and routes in supply channels, thereby reducing energy consumption, pollution, and operational costs.
Route determination
Similarly, for last-mile delivery - based on information about traffic intensity, destination points, weather, or delivery windows, algorithms can recalculate a courier's route in real-time to minimize fuel consumption and delivery time. It is also possible to predict delivery times to specific recipients much more accurately than before.
Intelligent fleet servicing Using artificial intelligence and supporting devices such as the Internet of Things (IoT), it is possible to predict potential failures and wear and tear of equipment or vehicles. This allows for proactive planning of maintenance work well in advance, thus avoiding downtime and additional costs.
Demand forecasts (goods and services) Analyzing historical data and current market trends allows for extremely accurate predictions of consumer demand, enabling more efficient warehouse resource management and distribution planning.
Customer service AI-based chatbots, notification systems based on delivery time predictions, and mechanisms that include planning and real-time tracking significantly contribute to increasing customer satisfaction and relieving the helpdesk by automatically solving simpler customer inquiries.
Supporting technologies
Internet of Things (IoT), i.e., the application of network-connected devices, allowing for tracking goods at various stages of transport. IoT can also be used to monitor the technical condition of vehicles and other devices.
Blockchain, which offers secure tools for recording transactions and events in a decentralized and unmodifiable way, increasing the credibility and transparency of global trade.
Autonomous vehicles and drones, which are still in the testing phase at many major players, will optimize delivery processes in the last mile by accelerating them and reducing costs.
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What to Pay Attention To?
To fully harness the potential of AI, it's essential to consider key issues such as:
Investment costs,
The need for additional specialists for ongoing support,
Ensuring additional data security mechanisms,
Exploring the possibilities of integrating new solutions with existing systems and devices.
However, the biggest challenge is introducing technology in a way that is well received by the company team. This means, among other things, undertaking educational actions and ensuring that, contrary to popular belief, artificial intelligence will not take away jobs from people but rather facilitate them.
To overcome these obstacles, a strategic approach to implementing AI solutions is necessary. It should include clear communication of benefits, training for employees, and the gradual, iterative introduction of new elements to minimize potential risks and resistance.
When considering the introduction of AI mechanisms and processes, it's worth analyzing the following issues:
Return on Investment
Although estimating the total costs can be extremely challenging, it's essential to attempt it. Comparing costs with potential gains (in the long and short term) and forecasted strategic benefits seems to be a crucial factor influencing the decision to implement a solution based on artificial intelligence.
Regulations and Compliance
The transport sector is burdened with the need to comply with strict national and international regulations. These include data protection, environmental standards, and customs or road traffic regulations. A thorough legal analysis should be one of the first steps before starting actions aimed at implementing modern technological solutions based on artificial intelligence.
Data Security and Privacy
The use of artificial intelligence involves processing huge amounts of data, many of which may have a high degree of sensitivity. Therefore, actions identifying the company's needs in terms of cybersecurity and assessing the additional risk associated with potential data leaks or the consequences of cyber attacks should be undertaken.
Ethical Issues
The wider use of artificial intelligence is associated with many controversies regarding issues such as the loss of control over data or even the advent of an apocalypse (hehe 😀). It's worth analyzing how the implementation of AI could impact the brand's image and employees' attitudes towards the company.
Human Factor
Implementing any new solution is associated with so-called resistance to change. In the case of still controversial artificial intelligence, this resistance can be accordingly stronger. Choosing ways to mitigate it (e.g., through education) is a key element of the process of introducing AI into the company.
Trends
Similar to other industries, companies operating in the logistics sector will use technological development to optimize processes occurring within it or to achieve and increase their competitive advantage. Among the most popular forecasts are:
The development of solutions using AI (for example, in creating more advanced WMS systems, during the construction of autonomous vehicles, drones, or warehouse robots supporting manual work),
Continuation of actions related to promoting and implementing sustainable development principles, including optimizing routes and distribution channels, using electric vehicles, and minimizing the amount of waste generated by the industry.
Summary
Proactively applied artificial intelligence will be the engine of fundamental changes towards creating a more efficient, sustainable, and resilient global supply chain. AI-related technologies in logistics will also play a part in establishing new standards of global goods transportation.
For local logistics companies, using artificial intelligence and new technologies is not just a path to efficiency and cost reduction - it's a strategic imperative to remain competitive and meet the challenges associated with last-mile delivery, among others, by offering faster, more reliable solutions.
As progress is made, successful integration of artificial intelligence will define leaders in the rapidly changing world of global logistics.
Despite the increasingly complicated market situation, higher requirements, and rising costs, the future of logistics may look bright. Artificial intelligence leads to the creation of a more connected, intelligent, and sustainable global supply chain. It will also have an undeniable impact on establishing new standards for the global distribution of goods and commodities.
Jakub Olech
Managing Partner
Kuba combines econometrics and information technology expertise with a keen interest in business analysis and statistics. His analytical skills contribute significantly to strategic decision-making.
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Jakub Olech
Managing Partner
