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Since Alzheimer’s disease is a neurodegenerative disorder affecting cognitive skills, including language, from the earliest stages of the disease, connected speech analysis is seen as a powerful medium for assessing and screening for the disease. Thanks to recent technological advances in artificial intelligence, with the development of automatic analysis models based on natural language processing, the analysis of connected speech has taken off in leaps and bounds, surpassing the performance of manual analysis. After a brief introduction to the principles of natural language processing, this article outlines the perceptible differences in language production in people with Alzheimer’s disease and mild cognitive impairment as identified through natural language processing analysis. Finally, this article concludes with a reflection on the challenges of integrating these tools into clinical practice, offering potential avenues for addressing the barriers to implementation.