Testing ChatGPT in Music Promotion: Assessing AI Efficiency Compared to Industry Standards

Abstract

ChatGPT is now an everyday topic, attracting the interest of the general public, researchers and specialists interested in exploring its capabilities. In the music industry, although artificial intelligence (AI) already has known uses, there is a lack of analysis of how chatbots can help promotional efforts. This research performs a comparative content analysis on AI-generated texts, using several music promotion prompts, to evaluate the success and efficiency with which ChatGPT offers advice on promoting artists. It examines promotion tools, more specifically artist websites, social media and video content, through the lens of efficiency criteria from specialised literature. This study asks whether ChatGPT can generate music-promotion strategies for artist websites, social media and video content that meet literature-derived efficiency criteria and how consistent these outputs are across repeated runs. The results suggest that ChatGPT does not consistently meet every efficiency criterion imposed by the industry, but it can serve as a useful starting point. Inconsistent results raise questions regarding the reliability and practical implications of AI for artists navigating an increasingly competitive industry. One of the solutions this paper suggests for generating efficient and comprehensive information is for the user to enter several detailed prompts and refine them progressively. Moreover, the present results encourage users to pass the AI outputs through the filter of industry professionals or specialised resources. These results show how important it is to understand how ChatGPT processes and delivers information and music promotion strategies, offering a fertile ground for further research through the obtained data, the prompt efficiency suggestions and the novel tools it provides.