Alzheimer’s disease (AD) is the most common neurodegenerative disease among the elderly with a progressive decline in cognitive function significantly affecting quality of life. Both the prevalence and emotional and financial burdens of AD on patients, their families, and society are predicted to grow significantly in the near future, due to a prolongation of the lifespan. Several lines of evidence suggest that modifications of risk-enhancing life styles and initiation of pharmacological and non-pharmacological treatments in the early stage of disease, although not able to modify its course, helps to maintain personal autonomy in daily activities and significantly reduces the total costs of disease management. Moreover, many clinical trials with potentially disease-modifying drugs are devoted to prodromal stages of AD. Thus, the identification of markers of conversion from prodromal form to clinically AD may be crucial for developing strategies of early interventions. The current available markers, including volumetric MRI, PET, and CSF analysis are expensive, poorly available in community health facilities, and relatively invasive. Taking into account its low cost, widespread availability and non-invasiveness, EEG would represent a candidate for tracking the prodromal phases of cognitive decline in routine clinical settings eventually in combination with other markers. After providing a short overview of the epidemiology and markers in AD, this review aimed to explore whether advanced analysis of EEG rhythms exploring brain function has sufficient specificity/sensitivity/accuracy to screen out the risk of conversion from Mild cognitive Impairment (MCI, a condition which is prodromal to AD in a high percentage of cases) to AD as a first-level screening method.