Alzheimer's disease is the most prevalent neurodegenerative disorder leading to progressive cognitive decline and functional impairment. Although advanced neuroimaging and cerebrospinal fluid biomarkers have improved early detection, their high costs, invasiveness, and limited accessibility restrict universal screening. Quantitative electroencephalography (qEEG) offers a non-invasive and cost-effective alternative for assessing neurophysiological changes associated with AD. This review critically evaluates current evidence on EEG biomarkers, including spectral, connectivity, and complexity measures, discussing their pathophysiological basis, diagnostic accuracy, and clinical utility in AD. Limitations and future perspectives, especially in developing standardized protocols and integrating machine learning techniques, are also addressed.