A new MIT and Mechalux study finds that AI is now integrated into 60 percent of warehouses

• A new report from Mecalux and MIT’s Intelligent Logistics Systems Laboratory reveals that more than 90 percent of warehouses worldwide are now using AI or automation, with most companies achieving returns on investment within two to three years.
• The survey of more than 2,000 logistics leaders in 21 countries shows that AI is now central to daily warehouse operations – not only enhancing speed and accuracy but also boosting workforce satisfaction and creating new highly skilled roles.
• As companies prepare for peak demand, the next wave of innovation will focus on generative AI for advanced decision-making and process automation.

As retailers brace for the annual surge in Black Friday demand, a new study by Mecalux and the MIT Intelligent Logistics Systems (ILS) Laboratory at the MIT Center for Transportation and Logistics reveals that the warehouses that power today’s global supply chains have entered a new era of intelligence. The research, based on responses from more than 2,000 supply chain and warehousing professionals in 21 countries, shows that artificial intelligence and machine learning are no longer experimental tools but rather the primary drivers of productivity, accuracy and workforce development.

With more than 9 out of 10 warehouses now using some form of AI or advanced automation, the sector has reached a surprising level of maturity. More than half of the organizations surveyed reported operating at advanced or fully automated maturity levels, especially among larger companies with complex, multi-site logistics networks. Warehouses have moved beyond isolated pilots, with AI increasingly supporting daily workflows, including order picking, inventory optimization, equipment maintenance, work planning, and safety monitoring.

“Data shows that smart warehouses outperform not only in terms of scale and accuracy, but also in terms of adaptability,” says Javier Carrillo, CEO of Mecalux. “As peak season approaches, companies that have invested in AI are not only faster, but also more agile, more predictable, and better positioned to handle volatility.”

The study also found that AI investments are paying off more quickly than many expected. Most companies now allocate between 11% and 30% of their warehouse technology budgets to AI and machine learning initiatives, and the typical payback period is only two to three years. These returns stem from measurable gains in inventory accuracy, productivity, business efficiency and error reduction. It also promotes a shift from exploratory spending to long-term capacity building. Cost savings, customer expectations, labor shortages, sustainability goals, and competitive pressures are all driving these investments, demonstrating that the value of AI extends far beyond automation alone.

Despite this progress, organizations still face challenges as they scale AI across their operations.

“The hard part now is the last mile: seamlessly integrating people, data and analytics into existing systems,” says Dr. Matthias Winkenbach, director of the MIT ILS Laboratory.
Key barriers include technical expertise, system integration, data quality, and implementation cost, reflecting the groundwork required to connect advanced tools to legacy systems. However, companies are touting strong foundations in data and project management, identifying better tools, clearer roadmaps, expanded budgets, and stronger internal expertise as key accelerators of continued adoption.

Most importantly, the report challenges persistent concerns about automation replacing human workers. Rather than replacing them, AI contributes to increased productivity, increased job satisfaction, and expanded workforce opportunities. More than three-quarters of organizations surveyed saw an increase in employee productivity and satisfaction after implementing AI tools, and more than half reported an increase in the size of their workforce. New roles are emerging across the board, including AI/ML engineers, automation specialists, process improvement experts, and data scientists – evidence that intelligent automation is expanding, rather than shrinking, the human role in warehouse operations.

Looking ahead, almost all of the companies surveyed plan to increase their use of AI over the next two to three years. 87% expect to increase their AI budgets, and 92% are currently implementing or planning new AI projects. The report shows that the next frontier will focus on decision-making technologies, especially generative artificial intelligence. Companies identify generative AI as the single most valuable method in logistics facilities today, citing applications such as automated documentation, warehouse layout optimization, process flow design, and even code generation for automation systems. As these capabilities advance, AI will help an increasing number of warehouses move from predictive visibility to automation.

“Traditional machine learning is great at predicting problems, but generative AI actually helps you engineer the solution,” says Dr. Winkenbach. “That’s why companies see it as the biggest value generator in warehouses today. Ultimately, the measurable gains from automation are productivity gains, making existing systems run more smoothly, faster and with fewer disruptions.”
The study confirms that as the logistics sector enters its busiest season of the year, the warehouses behind Black Friday orders have not only become more automated, but have smarter systems. As AI enhances performance, supports workers, and enables new capabilities across global networks, the coming years suggest deeper integration of data and decision-making into the core of warehouse operations.