A new study from Mecalux and the MIT Intelligent Logistics Systems Lab at the MIT Center for Transportation and Logistics reports that artificial intelligence is now embedded in a majority of warehouses worldwide, signalling a rapid shift toward intelligent logistics operations.
The study, conducted by Mecalux in partnership with the MIT Intelligent Logistics Systems Lab, draws on responses from more than 2,000 supply chain and warehousing professionals across 21 countries.
According to the report, more than nine in 10 warehouses now use some form of AI or advanced automation.
Over half of surveyed organisations reported operating at advanced or fully automated maturity levels, with larger businesses leading adoption.
The findings state that AI is now supporting a wide range of day-to-day warehouse functions, including order picking, inventory optimisation, labour planning, equipment maintenance and safety monitoring.
Mecalux CEO Javier Carrillo said the research shows clear performance benefits linked to intelligent systems.
“The data show that intelligent warehouses outperform not only in volume and accuracy, but in adaptability,” Carrillo said in the release.
He noted that companies with AI-enabled operations were demonstrating stronger resilience and predictability ahead of peak-season demand.
The report states that AI investments are delivering quicker returns than expected, with most organisations allocating between 11 and 30 per cent of their warehouse technology budgets to AI and machine-learning initiatives.
The study reports typical payback periods of two to three years, driven by gains in labour efficiency, inventory accuracy, throughput and error reduction. Motivations for AI adoption include cost savings, customer expectations, sustainability goals, labour shortages and competitive pressures.
However, the release notes that businesses continue to face challenges when scaling AI across their operations.
Dr Matthias Winkenbach, Director of the MIT ILS Lab, said the “last mile” of integration remains difficult as companies work to align people, data and analytics with existing systems.
Barriers identified in the study include limited technical expertise, system-integration issues, data-quality constraints and implementation costs. Even so, organisations reported strong foundations in data and project management and pointed to clearer roadmaps, expanded budgets and improved tools as key enablers for continued adoption.
The joint release also addresses ongoing concerns about automation replacing human workers, reporting that AI is contributing to workforce expansion rather than reduction.
More than three-quarters of respondents saw increases in employee productivity and satisfaction after implementing AI tools, and over half reported growing their workforce.
Emerging roles cited in the study include AI and machine-learning engineers, automation specialists, data scientists and process-improvement experts.
Looking ahead, the release states that nearly all surveyed companies plan to expand their use of AI within the next two to three years.
Eighty-seven per cent expect to increase their AI budgets, and 92 per cent are implementing or planning new AI projects.
Generative AI is identified as the next major area of value, supporting tasks such as automated documentation, warehouse-layout optimisation and code generation for automation systems.
Dr Winkenbach said generative AI is increasingly helping companies design solutions rather than simply predict problems.
