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Sector briefing · AI and automation

Warehouse automation: the economics behind the robots

Where automation pays back and where people still make the difference.

ConfX editorial2 October 20263 min readSupply chain and logistics
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Why it matters

Labour availability, service expectations and falling technology costs are making warehouse automation viable for more operations. The business case depends on volume stability, flexibility and integration costs.

Automation projects often take years to plan and install, while demand patterns can change quickly. More flexible systems, such as mobile robots and modular storage, let operators add capacity gradually and redeploy equipment.

By the numbers

117,500professional transport and logistics robots sold worldwide in 2025, up 21% 1
47%of all professional service robots sold went into transport and logistics 1
~250,000professional service robots sold in total, up 24% 1

What's changing

  • Autonomous mobile robots allow more flexible deployments than fixed conveyor systems.
  • Robotics-as-a-service models reduce upfront investment.
  • Warehouse management systems must orchestrate people and robots together.

How leaders are responding

  • Modelling business cases across several demand scenarios.
  • Starting with processes such as goods-to-person picking, where gains are well understood.
  • Involving operations staff early in design and change management.

What good looks like

  • Automation sized to peak and average volumes, not just peak
  • Robots-as-a-service where demand is uncertain
  • Warehouse management systems ready to orchestrate people and robots together

What to watch

  • Piece-picking robots for mixed product ranges.
  • Robotics-as-a-service contracts and their terms.
  • Safety standards for people working alongside robots.

Where to start

Model volumes, peaks and product mix for the next five years before choosing technology, and test the case under lower and higher demand.

Questions for your leadership team

  1. How stable and predictable are our volumes?
  2. Can our systems orchestrate mixed human and robot workflows?
  3. How much flexibility do we need if our network changes?