Procalcitonin (PCT) is a crucial biomarker for early detection of bacterial infections and management of sepsis. As smart hospital infrastructures increasingly integrate artificial intelligence (AI) and the Internet of Medical Things (IoMT), the reliability of PCT measurements becomes critical for clinical decision support. This study evaluated the precision and measurement uncertainty of the Architect BRAHMS PCT assay to determine its suitability for AI- and IoMT-enabled workflows. Following ISO 15189 and the French accreditation committee (COFRAC) guidelines, precision was assessed using patient samples and quality control materials at low, medium, and high PCT concentrations. The assay demonstrated low coefficients of variation (<4.4% for repeatability and < 6.9% for intermediate precision) and minimal measurement uncertainty across all levels, consistent with published benchmarks. These results confirm the assay’s robustness in providing accurate biomarker data for real-time predictive models. PCT-guided algorithms and AI/IoMT platforms have been shown to reduce unnecessary antibiotic use, shorten treatment duration and intensive care unit stays, and lower sepsis-related mortality, underscoring their clinical value. However, variability in PCT assay calibration and cut-off harmonization remains a key challenge that can affect the generalizability of AI models and clinical thresholds. Standardization efforts are therefore essential to fully exploit PCT’s potential within smart hospital ecosystems and ensure reliable implementation of predictive sepsis management strategies.