
The institutional momentum driving the integration of artificial intelligence into core business workflows has collided with a sobering reality regarding the fallibility of automated decision-making systems. While the technical frameworks required to sustain large-scale language models have matured significantly, the actual utility of these systems is increasingly compromised by a profound disconnect between linguistic fluency and factual grounding. This phenomenon,










