The Transformative Role of Artificial Intelligence in Enhancing Transparency and Efficiency in Music Royalty Distribution in Kenya

Abstract

This study aims to explore the capacity of Artificial Intelligence (AI) to restructure the music royalty framework in Kenya. The research specifically investigates whether the deployment of AI can alleviate existing systemic issues within Kenya's music royalty distribution. Aligned with the Kenya Vision 2030 strategy, the music industry is recognised as a pivotal economic sector; however, its potential is currently constrained by the deficiencies of its collective management organisations (CMOs). These deficiencies primarily involve the ineffective utilisation of technology for royalty collection, a lack of transparency in reporting artist royalty payments, and governance challenges that have eroded artists' trust in CMOs. By adopting a documentary analysis approach within a theoretical framework to synthesise findings from international intellectual property case studies, KECOBO audit reports, and relevant legal frameworks. This comparison aims to compare global best practices for AI implementation against the structural limitations prevalent in Kenya's music industry. Furthermore, the study applies Giddens' Structuration Theory to analyse how the current manual systems perpetuate inefficiency through recursive processes within the music industry. The study also proposes a model where AI catalyzes "re-structuring," facilitating new norms of algorithmic accountability and providing new resources of verifiable data. The findings indicate that while various AI technologies could be applied to track and distribute royalties in Kenya, their successful implementation is hindered by challenges related to data infrastructure and digital literacy. This research concludes that a phased approach to AI adoption should be pursued, positioning AI not only as a tool for increased efficiency in music royalty distribution but also as a mechanism to restore artist agency and institutional trust.