Artificial A&R: The Music Industry’s Answer to Moneyball
Independent music production has seen explosive growth over the last decade. The age of the ‘Bedroom Artist’ is here, mostly as a result of advances in music technology. Never before has it been so easy to create professional-quality sounds from the comfort of your own home. These days, the barrier-to-entry in the music industry is lower than ever, thanks to the power of social media platforms like YouTube, Instagram, and more recently, TikTok.
As Spotify alone publishes over 20,000 new tracks per day, the music industry is experiencing saturation like never before. Labels are racing to cut through the noise and find the next big hit.
Traditionally, A&R (Artist and Repertoire) scouts would scour venues and listen to recordings in an attempt to find talent. But with such vast volumes of material accumulating online on a daily basis, traditional A&R scouting methods just won’t cut it.
According to Chartmetric, a music analytics start-up, “finding a rising star today is like Where’s Waldo on steroids”. With A&R costs reaching upwards of $4.1 billion in 2017 among major record labels, alternative methods are becoming increasingly necessary. Recent years have seen the birth of new AI-powered technologies.
One such tool is the product of UK based start-up, Instrumental. Instrumental aims to eliminate a large part of the risk associated with scouting new talent by blending data from all social and streaming platforms, assigning hot scores and indexes to artists. These measures compare growth and engagement stats against many thousands of other emerging artists.
Instrumental is just one example from an extensive list of start-ups producing algorithms to separate the wheat from the chaff. A similar machine learning venture was developed by Sodatone and acquired by Warner Music in 2016. Their goal with the application was to predict the extent to which unsigned artists will experience future success, through analysis of streaming, social and touring data.
Further illustrating this emerging field of technology is Dublin-based start-up, Andrson, who are taking a slightly different approach. One of Andrson’s features offers artists the chance to upload their music and receive a ‘sound-like’ percentage which compares the traits and attributes of their music to that of well-known artists. A&R scouts, in turn, may search Andrson’s database for specific artists who match certain criteria, such as their likeness to other artists and their location.
This bares the question: Will artificial intelligence eliminate the need for A&R scouts altogether?
While many major labels have begun to incorporate AI technologies into their scouting routines, there is ongoing debate in the industry as to whether these technologies can replicate the human expertise that comes about through years of experience and practice. Can an algorithm detect an artist’s passion, dedication, and willingness to improve? Can AI be used to predict social media trends or the evolution of music and creation of new genres?
The practicality of artificial intelligence in this setting is undeniable— certainly as a tool filtering through the massive amount of artists publishing their music online, cutting it down to a volume that is manageable by human standards. For now, the final decision remains in the hands of the human scouts and A&R executives.
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