The new era of logistics: AI and robotics in use?

Part 5 of the series on the ‘Supply Chain of the Future’ focuses on transport 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 stringently digitally networked processes can prevent bottlenecks, reduce costs and increase service levels. At the same time, however, the survey also makes it clear that many companies' ambitions in the area of transport and warehouse logistics for 2035 are surprisingly modest – not so much because the technologies are lacking, but because their implementation is difficult alongside all the current operational challenges.

Global competitive pressure is increasing and the pressure to act in terms of efficiency and cost optimisation remains high. Energy, transport and personnel are becoming more expensive, growth impulses in the industrial sector are rare in many developed countries, and efficiency is no longer a side effect. Even small improvements in throughput times, utilisation or error rates have a direct impact on delivery dates and costs. In manufacturing companies, logistics forms the backbone of stable processes, and downtime is therefore not an option. At the same time, the shortage of skilled workers often increases the pressure to act: in the United Kingdom and other countries, jobs in warehousing and transport are becoming increasingly difficult to fill, especially where processes are still manual and fragmented.

In future, tasks will have to be solved differently – through greater automation, targeted assistance systems, the use of AI and bold rethinking of processes. Against the backdrop of increased pressure to act, the results of a survey conducted in April 2025 paint a mixed picture: 39 per cent of respondents expect significantly greater digitalisation and data-driven warehouse processes by 2035, with considerable advances in responsiveness and transparency. Twenty-eight percent anticipate the use of advanced technologies such as autonomous vehicles or drones in transport and material flow scenarios, while another 28 percent see AI agents as integral support tools for dispatchers, warehouse management and drivers. In addition, 20 percent expect networked ecosystems with real-time data exchange across company boundaries. The direction is therefore clear, but expectations appear moderate compared to the technological prospects and existing use cases. One possible reason for this is that the vision exists, but clear implementation plans are often lacking due to a shortage of time, expertise and resources. Many companies are lagging behind in modernising their processes and systems and are therefore unable to integrate the potential of innovative technologies and real-time data into their daily work and decision-making to the extent necessary.

At the same time, the survey reveals weaknesses in the current situation: only 17 percent of the 180 companies surveyed make comprehensive use of real-time data for warehouse optimisation. Only 9 percent rely on real-time transparency with precise arrival time forecasts in the transport sector, and only 6 percent have established collaborative planning and execution models with partners. On a positive note, 19 per cent of companies have already gained initial experience with generative AI, so progress is clearly being made in this new field. Overall, however, the figures show that the widespread implementation of digital innovations in practice still lags significantly behind the possibilities.

What needs to be done? Successful implementation of innovations requires a clear, prioritised strategy and a willingness to adapt processes and technologies – supported by comprehensive, high-quality data, intelligent analytics and effective orchestration. On the one hand, a robust digital backbone is needed to integrate process and sensor data into a consistent picture of the situation regarding transport, yard and warehouse. Both orchestration within the company and data exchange across company boundaries are crucial. This data forms the basis for AI-supported decision-making logic, such as predictive ETA forecasts, dynamic capacity and slot control, and anomaly detection. AI agents are designed to take on routine tasks, structure exceptions and offer suitable options for action. Furthermore, AI technologies are increasingly finding their way into physical logistics processes, where many experts expect further groundbreaking developments – both in software and hardware. These include increasingly flexible robots and cobots linked to innovative business models (e.g. models in which robots can be flexibly hired to handle seasonal peak loads). Fast connection and the ability to scale these solutions up and down to existing systems are crucial in this context.

In order to bring about the transition to innovative technologies and processes, it is essential to proactively address cultural resistance and implement effective change management. For innovations to take hold at all levels of the company, managers must communicate a holistic vision and actively involve employees in the change process. An open communication culture and continuous employee training help to create a positive environment in which technological innovations are accepted.

Why, then, do ambitions remain muted? Many companies are tackling several transformation projects at the same time. Logistics is still often viewed as a pure cost centre and slips down the priority list – even though it often delivers rapid and measurable effects. Depending on the corporate context, the first step in systematically tapping this potential could be to develop an innovation roadmap. This identifies clear areas for action and bottlenecks and links business objectives with the appropriate choice of technology: not just ‘Which robot?’, but ‘Which problem, which flow, which bottleneck – and which measure scales across locations?’.

Our appeal: better to start now than catch up too late. The technologies are ready for use, there is a need for action, and market pressure is increasing. Those who understand implementation as a continuous process with a clear roadmap, iterative scaling, and measurable effects will close the gap between aspiration and reality – and transform logistics from an often reactive element of the value chain into a strategic advantage.