Distributors are moving artificial intelligence beyond experimentation and into day-to-day operations, but adoption remains limited across many business functions, according to research presented Wednesday at Distribution Strategy Group's Applied AI for Distributors Atlanta Forum. The data shows a widening gap between companies deploying AI in core operations like collections and inventory management and those still planning their first projects.
Where AI is delivering results
Jonathan Bein, Ph.D., co-founder and managing partner of DSG, opened the Aug. 12 event at the Georgia Tech Hotel and Conference Center with a presentation examining where distributors are putting AI to work. The core functions include accounts receivable, warehouse operations, sales and customer relationship management, quote and order processing, and inventory management.
In accounts receivable, AI systems are automating invoicing, payment processing, and collections. Bein cited implementations that have reduced time spent on manual accounts receivable work by more than 75% and cut the number of days customers take to pay by 20% to 35%.
Warehouse operations are also seeing AI deployments. Bein discussed autonomous robotic picking systems that use lidar, 3D vision and mapping technology to navigate without fixed floor markers. These systems have produced efficiency gains of more than 75%.
Order processing and inventory
Order processing remains a significant use case because distributors continue to receive much of their business in formats requiring manual data entry. More than 75% of business-to-business orders arrive through email, PDFs, spreadsheets, voicemail, or handwritten notes rather than standardized electronic formats, the research found. AI systems can read those documents, identify products, and convert the information into orders ready for enterprise resource planning systems. Bein cited a 57% conversion rate on AI-processed transactions compared with about 20% for average transactions, along with productivity gains of 20% to 30%.
Inventory management is another developing application. Machine learning systems can combine a distributor's historical sales information with outside data such as weather and regional demand patterns to improve inventory decisions. Bein shared implementations that reduced inventory by more than 10% while increasing inventory turns by as much as 40%.
Current adoption lags
Despite those examples, DSG research shows that AI adoption remains concentrated in a small number of business functions. The highest current use among distributors was in marketing at 21%, followed by information technology and website and digital operations, both at 17%. Purchasing, physical security and warehousing had among the lowest current adoption rates, although those functions also had some of the largest percentages of distributors planning deployments within the next one to two years.
Bein also addressed AI's potential effect on employment. A DSG model using a hypothetical distributor with 500 employees in 2026 projected that automation could reduce staffing needs by 226 positions by 2030, primarily in warehouse and customer service operations. He said those reductions could be absorbed through normal employee turnover rather than layoffs because projected attrition exceeds the estimated reduction in staffing needs across most functions. The result would be slower hiring as companies automate more work.
"The swift will beat the slow, more than the large will beat the small," Bein said, describing how he expects AI adoption to affect competition among distributors.
DSG's modeling also projects that distributors using AI could reduce labor costs by 3 to 5 percentage points, increase revenue and inventory turnover by 6% to 10%, and improve Net Promoter Scores by 10 to 15 points.
Why this matters for operations managers
For operations managers, the data shows immediate opportunities to cut costs in accounts receivable, order processing, and warehousing, while also freeing employees from manual work. The gap between early adopters and companies still planning is widening, and the DSG AI Learning Path for Operations Managers offers concrete direction for those who need to move from planning to production. With most distributors still one to three years away from deploying AI in core operational areas, the operations professionals who push now will likely see the biggest gains. The related AI for Operations hub provides more resources on these topics.
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