Field notes from the Regional AI Executive Group, convened by iNDustry Labs at the University of Notre Dame. Read the full report below, or open it in a new tab.
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What the report covers
Across 30+ AI projects with more than 50 companies in the Regional AI Executive Group, the same questions kept coming up. They fall into three groups: process, infrastructure and people. The group has 130+ members from 53 companies, most of them manufacturers, with others in logistics, healthcare, finance and real estate.
Key findings
- Start with the business problem. The companies that did best with AI focused on actual business problems first, then chose the tools, not the other way around.
- The harness matters more than the model. The systems around a model, and the interface people use, decide what gets done and how fast an organization adopts it.
- Adoption is a mindset change. It works when it is led from the top and the bottom at once, more than when it is rolled out as “just another system.”
01 Process
Personal productivity, functional use cases and the agentic enterprise: how to get started, prioritize projects, see where AI applies, think about ROI and build versus buy, decide who leads, and set up governance.
02 Infrastructure
Model, harness, system and user interface: which tools to use, how good the data needs to be, privacy and free tiers, permissions, why Copilot alone is not always enough, and how to ground AI in company context.
03 People
Change management versus mindset change: training for adaptability, job descriptions, the “beaver” problem, dedicated AI roles, and releasing automation without fear.
iNDustry Labs runs the AI Executive Group alongside the AI Leaders of Tomorrow fellowship at the University of Notre Dame. To learn more about working with iNDustry Labs, visit industrylabs.nd.edu or our companies page.