AI is rapidly entering the food and equipment manufacturing ecosystem, but its usefulness depends entirely on the quality, consistency, and structure of the data it consumes. Today, the industry faces fragmented terminology, inconsistent documentation, and a lack of standardized digital representations of sanitary design principles. Without harmonization, AI tools risk producing unreliable or unsafe outputs.

This session demystifies AI for the sanitary design community and highlights why standardization is the foundation for safe and effective AI adoption. We’ll explore how structured data can support design validation, risk modeling, equipment selection, and regulatory alignment. We’ll also discuss the boundaries of AI and uncovering where it is safe to use, where it is not, and what safeguards are needed to protect both manufacturers and processors.

Attendees will gain a practical understanding of how 3‑A and its members can lead the industry by defining the data structures, taxonomies, and digital standards that will power the next generation of AI‑enabled tools.