Artificial intelligence is beginning to reshape manufacturing operations, but industry experts say the real challenge is not the technology itself. It is the quality, accessibility, and organization of industrial data. A recent panel discussion at Rapid + TCT 2026 in Boston, covered by Design News, explored how manufacturers are using AI tools to optimize production while confronting major gaps in data readiness and workforce confidence.
The discussion featured representatives from ASTM International, AV Inc., amsight GmbH, and the University of Maryland. Panelists argued that manufacturing facilities already generate enormous amounts of operational information, but much of that data remains fragmented, inconsistent, or unusable for AI systems. According to the speakers, manufacturers often struggle with disconnected machines, incompatible software environments, and poor data labeling practices that limit the effectiveness of machine learning tools.
Several participants emphasized that AI should not be viewed primarily as a replacement for workers. Instead, they described it as a way to reduce repetitive low-value tasks and improve human decision-making. AI systems can help operators identify defects, monitor equipment performance, and analyze production trends faster than traditional manual approaches. Panelists also discussed the importance of preserving manufacturing expertise as experienced workers retire and labor shortages continue across the sector.
Despite enthusiasm surrounding AI, the conversation highlighted ongoing skepticism inside the manufacturing industry. Some companies remain hesitant to trust automated systems, particularly in environments where reliability, safety, and quality control are critical. Speakers argued that successful adoption will require stronger collaboration between manufacturers, technology providers, and standards organizations to build common frameworks for industrial AI deployment.
The article presents AI not as a plug-and-play solution, but as part of a broader transformation in manufacturing culture and infrastructure. According to the panelists, the companies most likely to benefit from AI will be those that invest early in structured data practices, workforce education, and cross-industry cooperation rather than focusing only on the latest software tools.