A cooperative's leadership team is evaluating why adopting a shared, standardized AI vocabulary, aligned with frameworks like ISO/IEC 23053, matters before scaling AI across multiple regional offices. Select TWO accurate reasons. (Select TWO.)

A shared, standardized vocabulary reduces miscommunication between business and technical stakeholders who might otherwise use the same term to mean different things, and it supports more consistent governance and reporting when multiple regional offices need to compare practices using common definitions. The claim that adopting standardized vocabulary automatically certifies a company's AI systems as compliant with all applicable regulations overstates what terminology alone can do; using standardized terms doesn't automatically satisfy regulatory requirements, which typically involve substantive practices well beyond shared language. The idea that a shared vocabulary eliminates the need for staff AI literacy training going forward is also inaccurate — common terms are a foundation for clearer training, not a replacement for it, since staff still need ongoing literacy development regardless of how consistent the terminology is. The suggestion that standards bodies require companies to rename their AI products to match standard terminology exactly misrepresents how these frameworks operate; adopting a standard's vocabulary for internal governance doesn't require renaming commercial products. The two correct reasons both center on improved internal communication and consistency, which is the practical payoff of unified vocabulary as a cooperative scales across offices.