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This book explores the design and implementation of an intelligent audit recommendation system to improve audit processes in public companies in the Democratic Republic of Congo. The aim is to overcome the limitations of traditional audit methods, which are often marked by human bias, slowness and inefficient recommendation management. The proposed system uses artificial intelligence (AI) and natural language processing (NLP) to automate data analysis, generate relevant recommendations and ensure rigorous follow-up.This work is based on a study of the shortcomings of current practices, a model of the intelligent system and an experimental validation that demonstrates its effectiveness. The results obtained show a significant improvement in the transparency, speed and accuracy of audits, thereby strengthening the management of public resources. The book presents a scientific and technical breakthrough for modernizing audits and improving the governance of Congolese public enterprises.