The Challenge
A global manufacturing firm with 12 plants across North America had invested heavily in AI-powered predictive maintenance and quality control tools, but adoption was stalling at 15%. Floor engineers didn’t trust the AI recommendations, data teams couldn’t communicate with operations, and leadership had no framework to measure AI competency.
Our Approach
We designed and delivered a training and enablement program calibrated to three distinct audiences. The program addressed executive cohorts to establish AI literacy and governance frameworks, floor engineers to teach prompt design and agent interaction across plants, and central data teams to transition them from ad-hoc model building to systematic agent engineering.
The Results
- 500+ engineers trained: Across all 12 plants in a 90-day rollout.
- AI adoption jumped to 78%: From 15% pre-training, as engineers gained confidence in interpreting and acting on AI recommendations.
- 35% reduction in unplanned downtime: Predictive maintenance recommendations were finally being acted on consistently.
- $22M annual savings: Higher AI adoption directly translated to fewer breakdowns, less scrap, and optimized maintenance schedules.