A statistical model predicts likely words. A semantic system knows what concepts mean and how they relate. It combines the fluency of language models with an explicit map of a domain, so answers respect the actual structure of a field.
This pairing matters for accuracy. When AI can consult a formal model of concepts, it grounds its reasoning in something verifiable. Terms are used precisely. Relationships hold. The output can be traced back to defined knowledge rather than to a guess.
Semantic AI is how meaning enters the machine.