Artificial Intelligence (AI) is increasingly applied in Alzheimer's disease (AD) research to improve diagnosis, prognosis, and treatment. This paper reviews AI applications in AD, including etiology discovery, computer-aided diagnosis (CAD), computer-aided prognosis (CAP), and treatment. AI technologies, such as machine learning and deep learning, are used to analyze large-scale, high-dimensional data, including genetic, neuroimaging, and linguistic data, to identify risk factors, biomarkers, and potential treatments for AD. The paper discusses the challenges and future directions of AI in AD research, emphasizing the importance of integrating multi-modal data for more accurate diagnosis and prognosis. AI-based CAD systems use neuroimaging, linguistic, and genetic data to classify AD stages, while CAP systems predict disease progression and dementia onset. AI also aids in drug discovery and repurposing, offering new therapeutic approaches. The review highlights the potential of AI to enhance the efficiency and accuracy of AD diagnosis and treatment, and to support personalized medicine. The paper concludes that AI has significant potential to advance AD research and improve patient outcomes.Artificial Intelligence (AI) is increasingly applied in Alzheimer's disease (AD) research to improve diagnosis, prognosis, and treatment. This paper reviews AI applications in AD, including etiology discovery, computer-aided diagnosis (CAD), computer-aided prognosis (CAP), and treatment. AI technologies, such as machine learning and deep learning, are used to analyze large-scale, high-dimensional data, including genetic, neuroimaging, and linguistic data, to identify risk factors, biomarkers, and potential treatments for AD. The paper discusses the challenges and future directions of AI in AD research, emphasizing the importance of integrating multi-modal data for more accurate diagnosis and prognosis. AI-based CAD systems use neuroimaging, linguistic, and genetic data to classify AD stages, while CAP systems predict disease progression and dementia onset. AI also aids in drug discovery and repurposing, offering new therapeutic approaches. The review highlights the potential of AI to enhance the efficiency and accuracy of AD diagnosis and treatment, and to support personalized medicine. The paper concludes that AI has significant potential to advance AD research and improve patient outcomes.