Can AI Make A Hit Song? Australia Says It Still Needs A Human Touch

Australia’s music industry has drawn a firm line around artificial intelligence in music.

The Australian Recording Industry Association (ARIA) announced on August 25 that wholly AI-generated songs would no longer qualify for its charts.

The decision followed controversy over an AI remix of Madonna’s 1989 hit Like a Prayer.

Australian music producer and DJ Josh Fawaz created the version using AI-generated vocals and drums.

The track gained viral attention and spent several weeks in Australia’s top 20. It reached second place on ARIA’s top 20 Australian singles chart and accumulated more than 23 million YouTube views. Its AI origins were not initially disclosed clearly, triggering criticism from listeners and musicians.

ARIA has not prohibited artificial intelligence across music production. Instead, its revised rules distinguish between AI-assisted and wholly AI-generated recordings.

Songs can still enter the charts when humans write them and perform the lead vocals and primary instruments.

AI can support parts of the creative process, including certain production tasks, provided the final recording remains substantially human-made.

ARIA requires eligible recordings to avoid concerns involving streaming practices or chart manipulation. Tracks created through unlawful AI services will not qualify.

The organisation said the updated approach aims to protect the credibility of Australian music charts. It further seeks to preserve human artistry as generative AI develops rapidly.

AI-generated recordings will remain excluded from the prestigious ARIA Awards.

The controversy highlights a wider challenge facing the global music industry. Artists and record companies have taken AI music platforms such as Suno and Udio to court. They accuse these services of using copyrighted recordings without permission.

The industry is seeking clearer AI labelling on streaming services. Platforms such as Spotify and Apple Music could combine artist disclosures with their own detection systems. This would help listeners distinguish between human-created and synthetic music.

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