A year ago, I wrote that AI was barely visible in WMS. That has changed. AI is quickly moving toward the warehouse floor, though the gap between marketing and reality remains large. It’s helpful to distinguish three types: traditional algorithms, machine learning, and deep learning.

1. Traditional algorithms – fixed rules that always do the same thing

These rules have been in WMS software for years. They follow fixed logic that can be adjusted via parameters.

Examples:

• Deciding where new inventory should be stored
• Determining efficient walking routes
• Allocating available inventory to orders

Advantage: easy to understand and predictable.

Disadvantage: labor-intensive to maintain and inflexible.

2. Machine learning – software that recognizes patterns

Machine learning learns from historical data and automatically adjusts control. We don’t see this much in WMS packages yet.

Examples:

• Automatically reorganizing storage locations when demand changes
• Smartly determining when replenishment is needed
• Predicting busy zones and preventing congestion

Advantage: reduces management work and adapts to circumstances.

Disadvantage: sensitive to messy or incomplete data. Also, machine learning mainly looks backward and misses new developments.

3. Deep learning – powerful models that process complex signals

Deep learning goes further and can interpret and generate text, images, speech, movement, and large data streams.

Examples:

• Having warehouse tasks executed by chatbots and agents
• Automatic quality inspection via cameras
• Robots that can pick loose items from bins or boxes

Advantage: next step in continuous warehouse optimization.

Disadvantage: choices are hard to explain, which can lead to distrust.

AI will drastically change warehouse control, but only with a solid foundation: good data, predictable processes, and active management. Because AI only recently entered WMS, features are still in full development. Therefore, carefully check what vendors actually support today, what is still in pilot phase, and what plans are on the roadmap.

What do you think: Where do you expect AI to make a difference in warehouses?

About the author
Jeroen van den Berg is the author of Highly Competitive Warehouse Management and holds a PhD in warehouse algorithms from the University of Twente. He has been advising companies on warehouse optimization and WMS since 1997, running his own consultancy since 2001. He develops Metrica, a Warehouse Optimization System.