AGV robots, drones, automated shelves, order picking robots — without a doubt, logistics has undergone a true revolution in recent years. However, for the hardware in logistics centers to function efficiently, a "brain" is still needed. In this role, artificial intelligence fits perfectly.

Thanks to the use of AI in logistics processes, they become more integrated, and the planning, monitoring, and optimization of goods flow is done in a precise and dynamic manner. The technology allows massive data sets to be translated into practical operational decisions.

From this article, you will learn:

  • how artificial intelligence in logistics can increase productivity;
  • what AI-based warehouse management systems are available for small and medium-sized enterprises;
  • that artificial intelligence is helpful at every stage of the supply chain — from route planning and inventory management to returns processing and operational data analysis;
  • what AI-based solutions support process automation and customer service in the logistics industry.

Key information at a glance:

  • artificial intelligence has become an indispensable element of modern logistics;
  • AI supports both operational and decision-making processes in logistics;
  • the application of AI helps to increase operational efficiency and accuracy, while also reducing operational costs and task completion time;
  • companies investing in AI-based technologies gain a competitive advantage, greater operational flexibility, and higher customer satisfaction.

AI in logistics: warehouses that think

Smart warehouses are no longer futuristic concepts, but an increasingly common reality. Warehouse Management Systems (WMS) using AI analyze data on product receiving and turnover, forecast demand, and optimize goods placement.

There are several types of WMS available, but even the simplest ones, designed for small and medium-sized businesses — standalone WMS — streamline processes such as:

  • tracking product expiration dates,
  • barcode scanning,
  • receiving, picking, packing and shipping goods.

More advanced systems enable ERP integration and offer features like customer relationship management.

According to research from Bialystok University of Technology, such solutions increase productivity, shorten order fulfillment times, and reduce the risk of human error.

Autonomous vehicles — AI behind the wheel of a forklift?

According to current legislation (as of November 2025), driverless vehicles are not allowed on public roads in Poland. But they can operate within warehouses and logistics centers. AGV forklifts or AGV tow tractors are autonomous machines equipped with navigation systems, sensors, and AI algorithms.

They can safely navigate the warehouse floor, avoid obstacles, and complete transport tasks without human involvement. Their advantages include 24/7 operation, route optimization, and task sequencing. All of which translates into savings and labor cost optimization.

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Demand forecasting and inventory optimization

Worried your stock isn’t ready for Black Friday, Children’s Day, or the seasonal sales? Or maybe after the holiday shopping peak your warehouse shelves are overflowing with unsold goods? Artificial intelligence can minimize this risk by analyzing historical data, sales seasonality, market trends, and external factors — even weather.

Based on this, AI systems generate accurate demand forecasts that help maintain optimal inventory levels — avoiding overstock or stockouts. They analyze far more variables than traditional methods and respond to changes much faster. In addition, they allow for better budgeting, warehouse space planning, and goods flow management. All of which results in cost savings and improved customer service levels.

Examples of systems and solutions that support inventory management include:

  • Datup AI for Inventory Control,
  • StockTrim Inventory Forecasting (aimed at small and medium-sized companies),
  • Linbis AI Inventory Forecasting.

Artificial intelligence in logistics helps couriers arrive on time

Logistics is not just about warehouse and inventory management — it includes the entire transportation ecosystem. And every business owner knows how important on-time delivery is to customers and business growth. AI helps by analyzing in real-time, among others:

  • traffic data,
  • weather conditions,
  • accidents,
  • fleet availability.

Based on this data, route planning systems calculate the most efficient connections, minimizing the risk of delays. This also helps reduce costs — the chosen route may be the most economical one in terms of fuel consumption or vehicle wear and tear.

AI-powered courier route planning software includes, for example, Routin Planer Trasy, which analyzes traffic volume and delivery priorities to create optimal schedules for the entire fleet. Similar features are offered by AI Route Optimization by Upper.

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"Artificial intelligence employees": RPA and AI in logistics

AI can support not only warehouse floor processes but also those in customer service offices, accounting, or planning departments. RPA systems (Robotic Process Automation) combined with artificial intelligence automate routine tasks — from issuing invoices to delivery notifications. Thanks to them, many simple duties can be delegated to machines, freeing employees for other tasks that matter more to the company.

Moreover, RPA systems can be linked to complement each other’s actions. For example, in the field of returns processing: a return can be registered, accounted for, and routed back into the warehouse automatically — in minutes, not hours. Return processing costs can thus be reduced by 30–65% thanks to automation. Additionally, companies gain greater process transparency, faster information flow, and fewer errors.

RPA systems can also be integrated with intelligent payment systems. Przelewy24 offers solutions that automate settlements, support invoice processing, and accelerate cash flow.

AI in logistics: Summary

Warehouse automation, warehouse robotics, demand forecasting and resource management, supply chain management and distribution optimization, intelligent warehouse space usage, performance monitoring and improvement, fleet control…

These are all examples of areas where artificial intelligence is already changing the way logistics operates. Its application enables real-time data analysis, prediction of potential disruptions, and automatic operational decision-making. As a result, logistics processes become more accurate, scalable, and resilient to human error.

Sources:

  • Golubiewska W., Bolesta E., Czajkowski J. A., Leończuk D. (2024), "The Role of Artificial Intelligence in Enhancing Logistics Systems", Academy of Management, 8(4), pp. 288-302.
  • Skurzyńska A. (2019), “Opportunities and threats resulting from the use of artificial intelligence in the TSL industry”, Journal of TransLogistics, 5(1), pp. 275-286.
  • Transform your returns process with AI-based automation, online source: https://gibion.ai/pl/blog/automatyzacja-zwrotow-w-e-commerce-za-pomoca-ai-inteligentniejsze-procesy-zwrotow/, accessed: November 5, 2025.