Pericoronary adipose tissue (PCAT) attenuation — measured from standard coronary CT angiography using AI — has emerged as a non-invasive imaging biomarker for coronary inflammation. Fat surrounding inflamed coronary arteries has a different attenuation signature detectable on CT; AI algorithms can now quantify this automatically across entire coronary trees in minutes. The FAI (Fat Attenuation Index) has been validated as an independent predictor of cardiac mortality, and commercial AI tools for PCAT analysis are now entering clinical use in select centers. This represents one of the most concrete applications of AI in cardiovascular medicine — not in drug design, but in identifying high-risk patients who might benefit from anti-inflammatory therapy before a cardiac event occurs.