As interfaces become conversational and adaptive, language is no longer just something users read. It is what systems act on. In AI-driven products, content doesn't simply describe an experience; it shapes how the experience behaves.
This talk explores why treating language as flat text no longer works in UX. When meaning remains implicit, it fragments across UI copy, chatbots, help content, and AI responses. The result is inconsistency, loss of intent, and experiences that feel unreliable.
By treating language as data, as something that can be structured, interpreted, and reused, meaning becomes a shared foundation rather than a series of rewritten strings. Content shifts from being an output to becoming part of the system itself, guiding how interfaces respond across context and time.
This shift reframes content strategy as the design of meaning systems, ensuring AI interfaces remain consistent, explainable, and reliable as they grow.
