Distribution Industry Leaders Gather in Denver to Share Lessons on AI Adoption
Why It Matters
Colorado hosted a national gathering of wholesale distributors this week, where industry leaders confronted an uncomfortable reality: artificial intelligence investments are falling well short of projected returns. The distribution sector, which serves as a critical link between manufacturers and end consumers, is grappling with how to close the gap between AI’s promise and its actual performance across thousands of companies nationwide.
What Happened
The Shift | The Future of Distribution conference convened at The Inverness Denver hotel, drawing executives from across the wholesale distribution industry to exchange practical lessons on technology adoption. The National Association of Wholesaler-Distributors (NAW) organized the event, which centered heavily on the current state of AI implementation in warehousing, logistics, and purchasing operations.
One of the conference’s candid moments came from Jenni Detert, vice president of information technology at Endries International, who described a failed AI deployment at her company. Endries automated a purchasing workflow — routing supplier emails through an AI-monitored inbox intended to handle follow-up steps automatically. The system worked mechanically but produced poor results. “We realized that we had just kind of automated chaos,” Detert said. She added that the real lesson was understanding the underlying process before deploying AI at scale, rather than using technology to accelerate a flawed workflow.
By the Numbers
A survey of 426 distribution companies by a research firm affiliated with NAW illustrated how wide the expectation gap has grown. While 73 percent of companies anticipated a minimum 2 percent improvement in pricing and profit margins from AI tools, only 16 percent actually achieved that result. Additionally, 54 percent of respondents said AI was not currently on their planning roadmap, despite widespread industry discussion of the technology’s potential.
The distribution industry as a whole has grown to an estimated $8.7 trillion market, up from roughly $8 trillion about a year ago, according to NAW president Eric Hoplin. Hoplin attributed part of that growth to a tax legislation package that incentivized business investment in technology and research and development. A separate data point: U.S. Treasury figures showed corporate income tax revenue fell by roughly one-third — approximately $52 billion — between July and November compared to the same period the prior year, a decline Hoplin connected to the effects of that tax policy.
What Industry Leaders Said
Patti Rausch, NAW’s vice president of research and innovation, urged attendees not to write off AI as a failed experiment. She described the gap between expectations and results as a timing issue rather than a fundamental flaw. Companies that hit their margin targets, she noted, began earlier and built organizational habits around the technology before rolling it out broadly.
Rausch also pushed back on overhyped AI applications that don’t fit distribution’s operational realities. Dynamic route-adjustment algorithms, for instance, are impractical for delivery trucks already loaded in stop sequence. “The philosophy is to make the planning smarter before the truck leaves, not after,” she said, emphasizing the value of better upstream data — historical delivery patterns, weather trends, and traffic history — over real-time algorithmic course corrections that drivers cannot safely act on.
Hoplin, who testified before a congressional committee earlier this year on AI’s role in workplace safety, pointed to established uses of the technology that predate the current AI boom. Predictive systems that track equipment wear — such as forklift brake degradation — and wearable sensors in hard hats and vests that alert workers to unsafe conditions are already embedded in many distribution operations. Warehouse robotics, which reduce the need for workers to traverse large fulfillment floors, have similarly become standard at major facilities.
Zoom Out
The distribution sector’s AI reckoning mirrors broader patterns across U.S. industries, where enterprise technology investments frequently take years to generate measurable returns. Adoption challenges — workforce training, change management, and process redesign — often receive less attention than vendor selection and software deployment. Colorado’s own legislative and economic environment has seen similar debates about long-term investment versus near-term costs.
Globally, rising tariffs and softening consumer demand have created additional headwinds for distributors, though Hoplin indicated spending on automation and infrastructure has helped the industry continue expanding despite those pressures.
What’s Next
NAW leaders indicated that companies seeing early success with AI share a common trait: treating technology adoption as a long-term capability-building exercise rather than a one-time purchase. Industry observers expect the share of distributors with active AI programs to grow as early adopters demonstrate repeatable results and peer-to-peer knowledge sharing — like that on display in Denver this week — accelerates the learning curve for smaller firms.