Artificial intelligence (AI) has moved from a distant promise for wholesale distributors to a practical reality, driving measurable improvements in efficiency, profitability, and customer experience. Yet for many in the industry, the challenge is as much about knowing where and how to apply it in real-time as it is about discovering AI’s long-term potential. Present-day impact is as important as future success. That’s why the latest research from Modern Distribution Management (MDM) and Epicor is so valuable: it offers 52 real, implemented use cases for AI in distribution, mapped across every stage of the value chain.
The State of AI in Distribution: Adoption Is Accelerating
Epicor commissioned this research to gain a deeper understanding of how distributors are currently utilizing AI. According to 100 distribution executives, AI adoption has skyrocketed. Eighty-three percent of respondents say their organizations have implemented AI in at least one business function, up from just 35% in 2023. Most distributors started using AI within the last two years, and nearly all expect to deploy it soon.
Where is AI making the biggest impact? Sales and marketing lead the way, followed by inventory management and pricing optimization. AI-powered customer service is also gaining ground, with chatbots and virtual assistants improving support and reducing costs.
How Distributors Are Deploying AI
Distributors use a mix of strategies: Thirty-nine percent combine in-house development with external providers, 30% build entirely in-house, and 31% rely on partnerships or outsourcing. Notably, 70% turn to external resources for faster deployment, often leveraging solutions from existing software vendors.
Lessons Learned: What Works in AI Implementation
Early adopters share five key lessons:
- Start Sooner: Early projects—especially scalable ones like chatbots—deliver quick wins.
- Prioritize People: Change management is crucial; employee buy-in makes or breaks success.
- Champion Collaboration: Partnering with experienced vendors and thorough research improves outcomes.
- Sample, Then Scale: Controlled experimentation helps manage risk and build momentum.
- Structure the Support: Dedicated internal resources accelerate implementation and reduce friction.
Mapping AI Across the Distribution Value Chain
Here are the six value chain categories, from inbound logistics to procurement.
Inbound Logistics
- Inventory Forecasting: AI-driven forecasting reduces errors by up to 50%, slashing lost sales and overstock costs. Distributors using this technology report substantial savings and improved customer satisfaction.
- Tariff Schedules: Generative AI matches products to tariff codes with 95% accuracy, speeding up compliance and reducing risk.
- Demand Planning: AI optimizes reorder points and quantities, saving millions in inventory costs while maintaining service levels.
Operations
- Digital Twin Warehouses: Virtual replicas powered by AI optimize layouts, workflows, and energy use, cutting costs and improving order-to-delivery times.
- Predictive Maintenance: AI analyzes equipment data to schedule repairs before breakdowns, reducing downtime and extending asset life.
- Order Processing: NLP automates order entry from emails and documents, reducing errors and speeding fulfillment.
Outbound Logistics
- Transport Management: AI systems like UPS’s ORION optimize delivery routes, saving millions of gallons of fuel and improving on-time delivery.
- Dynamic Routing: Machine learning adapts to real-time traffic and fleet data, minimizing delays and boosting customer satisfaction.
- Cargo Documentation: Generative AI automates shipping paperwork, cutting lead times and preventing delays.
Marketing and Sales
- Collateral Development: GenAI automates the creation of sales and marketing assets, freeing up reps’ time and enabling personalization of key communications.
- Customized Outreach: AI tailors email campaigns to individual customer preferences, driving higher engagement and sales.
- Sales Rep Insights: AI recommends products and cross-sell opportunities, streamlining sales cycles and boosting revenue.
- Smarter Pricing: Dynamic pricing models maximize margins and negotiation effectiveness.
- Order Entry and RFP Response: AI automates proposal generation and order processing, accelerating sales and improving win rates.
Customer Service
- Self-Service Agents: AI chatbots deliver instant, 24/7 support, improving satisfaction and reducing costs.
- Real-Time Translation: AI breaks language barriers, expanding market reach and improving global support.
- Customer Experience Diagnosis: AI analyzes service data to identify gaps and recommend improvements.
- Account Planning: AI generates actionable success plans for account managers, boosting retention and engagement.
Firm Infrastructure, HR, Technology, Procurement
- Cybersecurity: AI detects and neutralizes threats in real time, protecting operations and data.
- Talent Analytics: AI matches employees to roles, supports succession planning, and improves retention.
- Software Development & IT Support: AI automates coding, bug detection, and IT troubleshooting, enhancing productivity.
- Supplier Risk and Predictive Reorder: AI evaluates supplier reliability and automates reordering, strengthening supply chain resilience.
Insights: Where AI Is Concentrated and Where It’s Emerging
Marketing, sales, and customer service are the sectors with the most AI use cases, reflecting their direct impact on revenue and engagement. Outbound logistics and technology are less represented, suggesting opportunities for innovation and investment.
Use cases vary in complexity and maturity. Some, like inventory forecasting and dynamic pricing, are plug-and-play and widely adopted. Others, like digital twins and generative prospecting, require advanced infrastructure but offer transformative potential.
The Art of the Possible, Grounded in Practicality
AI is reshaping wholesale distribution, but success depends on practical, strategic implementation. Our research shows that, in 52 use cases, AI is transcending the hype and delivering real value. Whether you’re just starting your AI journey or looking to scale, it’s important to focus on proven use cases, learn from early adopters, and align your strategy with your business goals.
The future of distribution is intelligent, efficient, and customer-centric. With the right approach, AI can help your business thrive in an industry that’s built on timeliness and productivity.
For more insights or to learn how Epicor can help your business scale and grow in a fast-changing world, visit www.epicor.com or contact distributionsexperts@epicor.com.
