The controversial rise of AI in tech-driven Afro-house

The controversies centre on cultural homogenisation, considering AI's tendency to average out data. Therefore, AI could dilute sub-genres like gqom despite their unique, hyper-regional sounds. If more companies adopt AI, the Afro-house landscape could become sterile and generic. The issue trickles down to job losses, as human producers may be discarded in favour of computers. Humans are integral to music creation, and their skills and cultural knowledge are necessary.

Afro-house music originated from indigenous rhythms and digital production in the 1980s. Technology has rapidly accelerated the genre, especially with the rise of artificial intelligence (AI). This advanced tool has quickly become used for generating beats and creating entire compositions. While the possibilities are vast, there are just as many questions. From ownership to authenticity, conversations are necessary to determine the role of AI in the genre. 

The controversies of AI in Afro-house music

AI learns music by identifying patterns in datasets. Recent innovations have helped AI understand music in real time, reducing the need for human labels [1]. When training on Afro-house, the tool may use the top 10 000 songs in the genre as a reference. While studying the genre comprehensively is helpful, it can lead to the averaging-out effect. 

AI may take the most commonly used tempos, drum patterns and chord progressions and use them for a new song. Therefore, Afro-house music becomes generic and less diverse. The genre loses its identity because the new content sounds generic and lacks distinctiveness. It needs the outliers and hyper-regional sounds that make it unique — otherwise, the music feels culturally sterile. 

For example, gqom originates from Durban [2] and is characterised by broken beats. Artists like DJ Lag and Babes Wodumo have revolutionised the genre since the early 2010s. The syncopated rhythms are intentionally off-kilter and stumbling, and AI may try to correct the broken beats and use standard 4/4 rhythms for gqom songs. However, this change would deviate from the genre’s traditions and the music’s urgent feelings.

Removing the human element from the genre

AI has improved over time and can become more adept at learning specific sub-genres. However, the technology devalues the roles of the producers and beat-makers who built the genre. These music professionals are visionaries and the creative forces behind each song. They sample, mix and synthesise tracks to invoke particular moods and textures. 

While AI can be helpful, it could also be a mimic. Well-trained ears are essential for mastering music theory and demonstrating strong technical skills. Now, producers can use tools to generate music from text descriptions and style prompts [3]. The musical product may sound similar to the average listener’s ears. However, the process behind each track significantly differs. 

Even if AI can create gqom or singeli music, it is unable to understand why it is making the music. Technologically advanced tools can identify patterns, though their best capability is rearranging data points. History and meaning are no longer prerequisites for creating music, which lowers the barrier to entry and dilutes the quality of the product. Making music creation accessible is terrific, but the tracks pay the price. 

The rise of AI in Afro-house music can lead to a drop in demand for human producers and beat-makers. This phenomenon is similar to that of other tech-driven sectors, such as the video game industry. Companies are using AI to save money in production and reduce labor costs [4]. Afro-house professionals are necessary to prevent a generic monoculture from taking over and to keep the recognisable sound. 

Respecting cultural copyright in Afro-house music

The AI controversies go beyond creativity and accuracy. There is ambiguity as to who owns AI-generated music, considering humans participate less in the process. AI tools are trained on existing songs, which brings up points of contention. If it uses music from Black Coffee or DJ Maphorisa, it may have been taken without their permission. 

AI-focused enterprises may say they are utilising fair use laws for research purposes. Meanwhile, the original artists could claim that the technology is stealing their intellectual property. Recent lawsuits have involved major music companies and AI tools, with the labels alleging copyright infringement [5]. If the commercial products are made to compete, the problem could worsen. 

Afro-house music is at risk because its value derives from sonic palettes. If AI can produce amapiano log drum sounds, its parent company can monetise this regional beat despite not creating it. The person behind the screen used a prompt, which raises questions about the level of creativity. If they minimally modify the AI-generated music, they may have a less substantial copyright claim. 

The Afro-house industry must also consider how it will protect the legacies of artists who have passed away. Winnie Khumalo, Aurlus Mabele and Manu Dibango have left behind strong legacies in the genre. However, artists may use their music without their permission, leading to controversy. If the artist is unable to control their legacy, it may be problematic to use their music for commercial purposes. 

The argument being made for AI 

While AI is controversial, some argue that it can benefit Afro-house music. One of the most commonly cited points is the supposed democratisation of production tools. High-quality tracks can be expensive to produce, considering the hardware and software necessary. Supporters of AI claim that AI-powered technology helps level the playing field by allowing aspiring producers to create more polished music. In this view, creators may only need minimal equipment instead of paying R2 000 [6] or more to make a song.

Humans remain essential for creating high-quality Afro-house music, even as advocates suggest producers can work in collaboration with AI. For example, producers may use machine learning models to analyse the sonic fingerprints of their music. From frequencies to rhythmic patterns, production teams can extract audio elements for manipulation. Afro-house DJs could then incorporate AI-assisted mashups into their shows, though these techniques still depend heavily on human curation and taste.

Copyright infringement remains a significant concern for AI music companies. Proponents argue, however, that AI can be useful when artists apply it to their own work. Afro-house musicians might use AI tools to alter their voice or experiment with new synth patches. Generative technology is often described as leveraging sonic DNA to create virtual instruments rather than relying on static recordings. In theory, this allows artists to preserve the character of the original sound, though questions remain about authorship and originality.

AI is also frequently positioned as a tool for the future of Afro-house music, particularly in education. Aspiring producers could upload their music to learning platforms and receive automated feedback on their work. These critiques might include suggestions on drum patterns or chord progressions. While this feedback loop is sometimes compared to a personalised music professor, its effectiveness depends on how well the technology understands cultural context and stylistic nuance.

Navigating AI for the future of Afro-house music

As AI advances, Afro-house music faces the challenge of balancing innovation with identity. This technology is often promoted as expanding access and offering educational support by lowering barriers to production. At the same time, the risks are significant, including cultural homogenisation and the spread of generic sounds. Artists must remain aware of how AI systems may use their intellectual property without compensation. Ultimately, producers, artists, and listeners share responsibility for cautiously handling the noticeably increasing push for AI in Afro-house music.

Resources and citations

[1] https://news.mit.edu/2025/ai-learns-how-vision-and-sound-are-connected-without-human-intervention-0522

[2] https://www.afropop.org/audio-programs/the-gqom-generation-of-durban-south-africa-2

[3] https://chutes.ai/docs/examples/music-generation

[4] https://modded.com/games/even-when-successful-game-studios-are-still-being-shut-down/
 
[5] https://theconversation.com/universal-music-went-from-suing-an-ai-company-to-partnering-with-it-what-will-it-mean-for-artists-268773

[6] https://problematic.co.za/the-complete-guide-to-music-production-costs-in-south-africa/

Disclaimer: Jack Shaw is a writer based in the US. The opinions and views expressed herein are solely his own and do not reflect the position or stance of the publication. Music In Africa's Overviews provide broad information about the music scenes in African countries. Music In Africa acknowledges that the information in some of these texts could become outdated with time. If you would like to provide updated information or corrections to any of our Overview texts, please contact us at info@musicinafrica.net or ano@musicinafrica.net.