The purpose of the paper was to investigate the identification of text generated by Artificial Intelligence (AI) and to analyze manual and software methods for detecting such content. The paper describes what the identification of text generated by artificial intelligence entails, highlights manual methods of identification that are based on human judgment and experience, and software methods that rely on algorithms and machine learning technologies. The advantages and disadvantages of various AI content generators such as Jasper A.I., Writesonic, Clickup, etc. were analyzed, highlighting their effectiveness and potential problems such as unreliability or lack of authenticity. Also, the paper investigated the most famous tools used to detect AI-generated content such as ZeroGPT, Writer's AI content detector, Hive Moderation AI content detector, etc., analyzing their accuracy and reliability in identifying such content. To conclude, this paper explores the possibilities of tagging content generated by Artificial Intelligence and considers the question of how to properly label such content in order to provide transparency and reliability to users. The goal was to provide an overview of the procedures and tools used to identify AI-generated text, highlight the risks of such content and analyze the most popular AI content generators and AI generated content detection tools to provide users with a better understanding and awareness of the opportunities and challenges associated with using AI-technologies in creating and recognizing content.