Alzheimer’s disease (AD) is an acute brain disease that affects neural functions and destroys the memories and abilities of human beings. AD causes severe chronic, progressive, and irreversible cognitive declination and brain damage. It is one of the most common forms of dementia that affects the elderly. Early identification of AD is critical for developing new treatment options. Artificial intelligence (AI) is an excellent tool for detecting AD since these methods are used in clinical settings as a computer-aided diagnosis (CAD) system and play an important role in detecting alterations in brain images for AD detection. This chapter discusses the recent methods and developments in medical image analysis and image processing for AD detection using AI. The primary objective of this chapter is the development of easy-to-implement methods that promote early AD detection based on deep feature extraction methods. We developed a deep feature extraction methodology with machine learning approaches to achieve a good performance in AD detection. Furthermore, some of the techniques that were used by previous researchers are reviewed. A discussion on the existing state-of-the-art methods, a review of emerging trends, and future research problems will round up the chapter.