Anyone operating a distribution center or manufacturing plant today knows the equation: open positions in order picking, goods receipt, and production supply remain unfilled for months, turnover in physically demanding areas is rising, and the baby boomer generation is retiring faster than new talent can enter the workforce. On the flip side: e-commerce peaks, smaller order sizes, increased manufacturing variants, and tighter delivery windows. No amount of employer branding will close this gap. It can only be bridged through processes that achieve more with fewer people—and that is precisely what the current generation of material flow automation is designed to deliver.
Chapter 01The Imperative: Automation is the Answer to a Structural Problem
Three developments are turning robotics in logistics and manufacturing from an efficiency project into a strategic necessity:
- Demography beats economic cycles. The labor shortage in logistics and manufacturing is structural. Anyone who bases their capacity planning solely on recruitment is planning with a resource that will not exist in this form in five years.
- Volatility demands scalable capacity. Seasonal peaks, promotional business, product variety, and geopolitically driven rerouting require capacity that can be scaled up and down within weeks. Mobile robotics is currently the most flexible form of this: fleets can be rented, expanded, and easily retrained during layout changes – both in the warehouse and on the shop floor.
- Ergonomics and Employer Attractiveness. Robots take over lifting, pushing, and long walking distances—the tasks that cause physical strain and make positions unattractive. Automation is therefore also a key instrument for retaining remaining staff.
The decisive shift in management mindset: automation does not primarily replace existing staff—it compensates for staff that is no longer available.
Chapter 02Availability: What has proven effective today – from warehouse to production
The good news: For the vast majority of material flow processes, waiting for futuristic technology is unnecessary. Three technology families are mature, proven in the field, and economically viable:
- Autonomous mobile robots (AMRs) and automated guided vehicles (AGVs) handle transport between goods receipt, warehousing, and shipping – as well as line supply in production, the removal of finished goods, and inter-factory transport, extending up to driverless forklift trucks. Operating without induction loops or structural modifications, this entry scenario delivers the fastest return on investment, with a typical payback period of 18 to 36 months.
- Goods-to-person systems – shuttle systems, cube storage, mobile shelf robots – bring the goods to the operator instead of the other way around: to the packing station in the distribution center, or directly to the assembly line as small parts and Kanban provision in manufacturing. They multiply productivity per person while practically eliminating walking distances.
- Cobots – collaborative robotic arms without safety fencing – bridge the gap in palletizing, depalletizing, and packaging, as well as in machine loading, assembly support, and quality inspection. Their advantage lies less in speed and more in retrofitting flexibility: they integrate into existing workstations rather than replacing them, and can be reprogrammed without requiring robotics specialists.
Intralogistics in manufacturing operations in particular is often the overlooked domain: between goods receipt, pre-assembly, the line, and shipping lie transport, buffering, and staging processes that are rarely budgeted as “logistics” – yet they tie up skilled workers day in and day out who are then missing from value creation. And cobots are perhaps the most underestimated category for mid-sized enterprises: they unlock automation precisely where traditional industrial robotics fail due to volume, space, or budget constraints – serving as a tool alongside humans rather than a system replacing them.
«The question is no longer whether robots will enter warehouses and production facilities. The question is whether they will enter your processes – or those of your competitor, who will use them to challenge your skilled workforce, your margins, and your delivery times.»
Chapter 03Humanoid robots: between hype and pilot practice
Scarcely any topic is currently generating more attention – and more misjudgments. The investment momentum is real: in 2025 alone, around five billion US dollars flowed into humanoid robotics worldwide, surpassing the total investment of the preceding decade. And the technology has reached practical application: in Germany, the retail group Rossmann has been testing a humanoid robot in its own logistics center since spring 2026 as part of a one-year pilot project – featuring a clear roadmap ranging from simple use cases to the evaluation of a potential rollout. Simultaneously, initial pilots are underway in the automotive and light industries, where humanoids handle containers and supply workstations.
Pilots of precisely this kind provide the most honest baseline assessment. The interim conclusion publicly drawn by the participants: there is a significant gap between media reports and what a humanoid robot actually achieves in daily operations today—building knowledge, competencies, and programming environments is demanding and takes time. Research as well, such as the Fraunhofer IML study on the potential of humanoid robots in warehousing and intralogistics, paints a nuanced picture: immense potential where traditional automation fails on variable, non-standardized tasks—yet open questions remain regarding availability, safety, standards, and costs.
For decision-makers, this realistically means:
- Time Horizon: Market observers anticipate the transition from pilots to initial limited production deployments in logistics and light manufacturing between roughly 2027 and 2030, depending on reliability, cost, and safety approvals.
- High-value initial use cases: Tote and container transport in human-centric environments—both in warehouses and manufacturing facilities—light-duty material handling between workstations, and inspection rounds. Not intended for high-performance order fulfillment, heavy payloads, or mass production cycle times.
- The real bottleneck is increasingly not the AI itself, but the surrounding ecosystem: functional safety in mixed operations with humans, liability issues, documentation, and integration into WMS, MES, and ERP landscapes. Companies that build competence in these areas early on gain the competitive edge that hardware alone can never deliver.
Our recommendation is therefore intentionally twofold: Scale today with proven automation, while simultaneously learning through small, clearly defined humanoid pilots. Those who wait until humanoids are "ready" will then lack the processes, the data foundation, and the workforce to integrate them—because one rule applies equally to every generation of robots: automation only makes a bad process a fast bad process.
Conclusion: First the process, then the robot – but now
The sequence of successful automation projects is always the same: streamline processes and data foundations, prioritize use cases with measurable business cases—in warehousing as well as in production material flow—start with scalable technology, integrate employees from day one, and plan extensions up to humanoids as options rather than bets. Building precisely this bridge between technological promise and operational reality is our craft.
Therefore, the honest question for your organization is not: "Do we need robots?" Instead, it is: Which three processes in your warehouse or production would you no longer staff with personnel today if you could design it from scratch?
