Justin Nhan

AI Vision is rapidly reshaping inspection and quality control by moving manufacturers beyond manual checks and isolated hazard detection toward continuous, scalable, and highly accurate visual intelligence. As automotive and asset intensive operations push for zero defect performance, AI Vision is becoming a core enabler of consistent execution, faster root cause identification, and real time decision making on the line. This panel brings together leaders who are embedding AI powered inspection into daily workflows, reducing variability across sites, and building the trust, skills, and change readiness needed for frontline teams to adopt and rely on intelligent visual systems.

• How AI Vision is improving defect detection accuracy, reducing false positives, and enabling real time quality decisions at scale

• Strategies for integrating AI Vision into existing inspection workflows without slowing production or overwhelming frontline teams

• Approaches to capturing expert knowledge and training AI models to recognize complex defects, edge cases, and evolving product variations

• How organizations are building trust in AI driven inspection through transparency, cross functional communication, and frontline engagement

• Lessons learned from scaling AI Vision across multiple plants, including data governance, model retraining, and change management practices