Midwest Wheel Anchors AI Expansion to a Single Cloud Foundation

The century-old distributor is automating invoices and product recommendations while setting guardrails for autonomous agents.

By The Company WireOctober 7, 2026 at 7:46 PM UTC3 min read

Midwest Wheel Companies — Midwest Wheel Anchors AI Expansion to a Single Cloud Foundation. Photo: SiliconANGLE.

Enterprise software vendors are increasingly embedding autonomous artificial intelligence agents into operational platforms, but distributors must determine which tasks software can resolve independently and which require human oversight. Midwest Wheel Companies, a century-old truck parts distributor, is addressing this transition by anchoring all digital tools to a unified enterprise foundation, senior vice president Steve McEnany told theCUBE at Infor Velocity Week, in remarks reported by SiliconANGLE (https://siliconangle.com/2026/10/07/midwest-wheel-builds-ai-agents-fix-problems-inforvelocity/).

Midwest Wheel operates on cloud software from Infor (US) LLC. Moving infrastructure to the cloud removed physical server maintenance and routine update cycles from its lean IT team, allowing internal staff to develop and deploy new tools in weeks. The distributor has since introduced automated features into daily operations, including a product recommender embedded in order entry and automated parsing of emailed PDF invoices directly into the core system.

The company's longer-term objective is to move beyond passive problem detection toward agentic systems capable of autonomous remediation. Rather than merely flagging operational issues, McEnany stated the distributor aims to provide software agents with business rules so they can automatically execute standardized resolutions for routine issues.

McEnany emphasized that expanding autonomous execution requires strict data governance. Midwest Wheel maintains mandatory human oversight for any workflows touching cash or accounts. The company instituted tighter checks after discovering that a companywide sales report card generated by AI contained calculation errors, an issue detected only after a secondary AI tool audited the figures. Infor similarly argues that domain-specific context is required to avoid errors, citing research showing generic off-the-shelf AI models fail to meet operational demands for two out of three businesses.