The Future of Supply Chain Management | Part 5 of 6

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Supply Chain 2035: The New Era of Logistics: AI and Robotics in Action?

Part 5 of the “Supply Chain of the Future” series focuses on transportation and warehouse logistics where speed, reliability, and transparency determine costs, service, and resilience. The joint study by SAP Business Consulting and Kühne Logistics University clearly shows that companies who tightly integrate their processes digitally can prevent bottlenecks, reduce costs, and increase service levels. At the same time, however, the survey also makes it clear that the ambitions of many companies in the field of transport and warehouse logistics for 2035 are surprising – less because the technologies are lacking, but because their implementation is difficult alongside current operational challenges.

Global competitive pressure is increasing, and the pressure to act in terms of efficiency and cost optimization remains high. Energy, transport and staff are becoming more expensive, growth stimuli in the industrial sector are scarce in many developed countries, and efficiency is no longer achieved incidentally. Even small improvements in lead times, utilization, or error rates have an immediate impact on delivery dates and costs. In manufacturing companies, logistics is the backbone of stable processes, and standstill is therefore not an option. At the same time, the shortage of skilled workers often exacerbates the pressure to act: In Germany and other countries, jobs in warehouses and transport are increasingly difficult to fill, especially where processes are still lived manually and fragmented.

Tasks must be solved differently in the future – through higher automation, targeted assistance systems, the use of AI, and the courageous rethinking of processes. Against the backdrop of increased pressure to act, the results of a survey conducted in April 2025 show a mixed picture: 39 percent of respondents expect significantly stronger digitalization and data-driven warehouse processes with significant advances in responsiveness and transparency by 2035. 28 percent expect the use of advanced technologies such as autonomous vehicles or drones in transport and material flow scenarios; another 28 percent see AI agents as integral support tools for dispatchers, warehouse managers and drivers. In addition, 20 percent expect connected ecosystems with real-time data exchange across company boundaries. So, the direction is clear, but expectations seem moderate compared to the technological perspectives and already existing use cases. One of the possible reasons: the vision exists, but there is often a lack of clear implementation plans, as time, know-how and resources are scarce. Many companies are lagging behind with the modernization of their processes and systems and can therefore integrate the potential of innovative technologies and real-time data into their daily work and decision-making to the required extent.

At the same time, the survey reveals weaknesses in the current situation: Only 17 percent of the 180 surveyed companies use real-time data comprehensively to optimize warehousing. Only 9 percent are committed to real-time transparency in the transportation sector with accurate arrival time forecasts, and only 6 percent have established collaborative planning and execution models with partners. It is positive to mention that 19% of companies have already gained initial experience with generative AI – so this is a new field where progress has been made. Overall, however, the figures show that the comprehensive implementation of digital innovations in practice still falls significantly short of the possibilities.

What needs to be done? Successful innovation requires a clear, prioritized strategy and readiness to adapt processes and technologies, supported by comprehensive and high-quality data, intelligent analytics, and effective orchestration. On the one hand, a resilient digital backbone which integrates process and sensor data into a consistent situational picture across transport, yard and warehouse is required. Orchestration within the company as well as data exchange across company boundaries is crucial. This data forms the basis for AI-driven decision logic, such as predictive ETA forecasts, dynamic capacity and slot controls, and anomaly detection. AI agents should perform routine tasks, structure exceptions, and provide appropriate options for action. In addition, AI technologies are increasingly moving into physical logistics processes, where many experts expect further groundbreaking developments – both in the software and hardware sectors. This includes increasingly flexible robots and cobots paired with innovative business models (e.g., renting robots to flexibly absorb seasonal peaks). Fast integration and the ability to up- and downscale these solutions within existing systems are crucial.

To achieve the transition to innovative technologies and processes, it is essential to proactively address cultural resistance and implement effective change management. To drive innovation at every level of the business, leaders must deliver a holistic vision and actively involve employees in the change process. An open communication culture and continuous training of employees help to create a positive environment in which technological innovations are accepted.

Why do ambitions remain subdued? Many companies are running multiple transformation projects at the same time. Logistics is still often seen as a pure cost center and shifts backwards in priority – although it often delivers quick and measurable effects. The first step to systematically unlocking this potential can be, for example, to develop an innovation roadmap, depending on the business context. This identifies clear areas of action and bottlenecks and links business goals with the appropriate technology choice: not only “Which robot?”, but “What problem, which flow, which bottleneck – and which measure scales across locations?".

Our appeal: start now rather than catch up too late. The technologies are up and running, there is a need for action, and market pressure is increasing. Understanding the implementation as a continuous process with a clear roadmap, iterative scaling, and measurable effects closes the gap between ambition and reality – and transforms logistics from an often more reactive element of the value chain into a strategic advantage.

Figure: Vision 2035 and Reality 2025 in Transportation and Logistics

This article was written in collaboration with Prof. Kai Hoberg (Kühne Logistics University) in the context of the SAP-KLU study "The Supply Chain of the Future”.