Music and Artificial Intelligence: Implications Artists and Industry

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Artificial intelligence-powered tools can now provide insight into many of the questions that previously confused stakeholders across the music industry. Analytics and predictive models allow labels to make smarter decisions regarding their investments — decisions that are now informed by a more comprehensive understanding of the competitive environment and audiences’ preferences.

Clearly, AI technology is here to stay. Yet it’s being applied in new and innovative ways beyond understanding listeners and their preferences: It has become the latest method for creating music.

Let’s not panic. This is not the dystopian nightmare about real musicians being replaced by computers that some might fear, but an opportunity for artists and content creators to explore paths they wouldn’t otherwise discover.

AI nor a Creative Tool

Some musicians train machine-learning models with data based on what they want their sound to be. Others feed a neural network — an algorithm system modeled after the human brain’s neurological activity — with music preferences based on bands or digital sounds that then create compositions of melodies and rhythm patterns.

According to a piece on AI and music from Red Bull, one of the first pop songs, “Daddy’s Car,” crafted by AI debuted in 2016. The year after, American YouTuber Taryn Southern “went one step further to release the first LP by a solo artist composed and produced with AI, titled I AM AI.” Pop songs aside, AI is even being used to compose symphonies.

As music production by AI becomes more sophisticated and ubiquitous, the way in which artists use it will likely continue to evolve. Who knows what unimagined rhythms and sounds will be the result.

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Opportunities for Content Creators

The demands of a content-driven music industry, in which producers are expected to constantly deliver volumes of music for video content and more, can be difficult to meet. Independent creators need original music for their content, preferably without paying the high costs of licensing music or using recording studios.

Apps such as Mubert, Ecrett Music and Songen allow independent creators to generate royalty-free music in a few steps. Such services use AI-assisted engines that sketch song ideas users can customize and finish according to their needs and preferences. They also help creators avoid misusing copyrighted material, which, by the way, AI has been instrumental in detecting.

Helping Music Reach its Audience

The music industry has faced many challenges in the last few decades of the digital revolution, from piracy to the rise of streaming services. AI has been the one technological advancement that has brought clarity for labels and creators in a context of a rapidly changing market with overstimulated consumers.

Machine and deep learning help apps like Spotify and Apple Music, which generate the majority of the revenue in the overall music industry, help ensure a satisfactory experience for the listener. User data on demographics, listening habits and other behavior inform and improve artist and album recommendations within the platform. All this data is also available for labels and artists through social listening. Looking at the data and listening to fans can revolutionize the business strategy, offering improved insights that benefit artists, the industry and fans.

In conclusion, the music industry could continue to undergo changes as the use of AI proliferates. AI will not replace musicians in transmitting sensory experiences through music, but it could become increasingly essential for musicians — and all those participating in the current music industry — to understand and leverage it.

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