My work takes me into warehouses and DCs (distribution centers) throughout North America, observing the various processes needed to receive, process, and ship products to businesses and consumers every day, and recommending automation solutions to improve process efficiency and accuracy.
In the past few years, especially up through 2025 to date, the deployment of software and automation solutions in warehouses and DCs that are based on AI (artificial intelligence) algorithms has grown significantly. If you have read my earlier articles here in Connected World, you can see both my interest–and concerns–about this trend.
These deployments have been made to remedy some nationally relevant issues, not the least of which is the shortage of workers in the warehousing space. AI-infused software and automation, including the human/robot collaborative work processes (cobots), are either intended to improve human performance in operational processes—or eliminate the human from the processes altogether.
What motivated me to look deeper into this trend was this recent report: https://iceberg.mit.edu/report.pdf
The first question that popped into my mind was how deep was AI’s penetration into warehouse and DC operations? What I found gave me pause, and I had to adjust my understanding of just how rapidly AI has been adopted in this space. It has been much faster than I thought. Here are some of the results of my research:
- A recent study by Mecalux in partnership with MIT Intelligent Logistics Systems Lab (2025) reports 60% of warehouses already integrate AI in their operations.
- Market research shows the global “AI in warehousing” market (software, robotics, etc.) is growing, which implies that more of the warehousing industry is moving toward AI-enabled tools over time.
Warehouse and DC operations include basic WMS (warehouse management systems), inventory tracking, robotics, AI-driven forecasting/predictive analytics, and order fulfillment.
There’s an important caveat to bring up here: Size matters! The levels of penetration cited above relate to larger operations run by companies that have the financial resources to make the investment in AI-infused automation deployments.
Looking at the entire market for all warehouses (including small / mid-size / basic operations), likely quite a minority have AI integrated across their software stack, due to cost, complexity, and resource constraints. McKinsey did an analysis of the available data that concluded only roughly 20% of North American warehouses have any automation.
Overall, a substantial and growing portion of warehouses and distribution centers, maybe half to two-thirds especially among larger or more modern facilities, now use at least some AI in their operations software and automation tools.
How this AI-based reality affects human workers is now a real concern, one that can either be positive, helping humans be more productive, or negative, eliminating human workers in these essential processes.
Both alternatives have profound implications for the future of work. Warehouses and DCs have traditionally been employers of people with basic levels of education. If AI can help augment such people to be more productive, allowing them to achieve the financial benefits of work incentive programs, then this is a positive outcome that should be welcomed.
If AI eliminates the need for people, then the question that matters is: Where do people with basic educations go for work if this venue is closed to them? This is a negative outcome.
The torrid pace of AI adoption in warehouses and DC will no doubt accelerate the choice of outcomes that companies adopt as we head into the new year.
About the Author
Tim Lindner develops multimodal technology solutions (voice / augmented reality / RF scanning) that focus on meeting or exceeding logistics and supply chain customers’ productivity improvement objectives. He can be reached at linkedin.com/in/timlindner.