How AI is Helping Redefine the Music Streaming Industry

Technology fascinates me the way it has fuelled the growth of the music industry at every step in the last five decades. Coming through from Vinyl Records then cassettes, to the moment we started using CDs and then switching to music streaming apps thanks to the digital disruption, the music industry has profited from accelerated technological advancements.  Thanks to deeper mobile penetrations, cheaper data and the emergence of Artificial Intelligence (AI) and Machine Learning (ML) have enabled streaming players to grow exponentially. Several players are ruling the streaming industry and are working with high-level technology to allow listeners to access an extensive collection of songs and artists from all over the globe. In India, the transition from feature phones to smartphones, the data rates being the cheapest in the world, coupled with the fact that Indian consumers spend 21.58 hours per week listening to music (surpassing the global average of 17.89 hours a week), there are a myriad factors bolstering the growth of the Indian music streaming market. The role of AI tools in business and the global economy is a hot topic across all industries. It is not unusual given the fact that AI can effect colossal transformations in the way enterprises combine with their respective consumers. This future of a business landscape reshaped by technology is no longer something organisations can overlook. The fourth industrial revolution is in full effect, and companies, particularly in the music business, need to prepare a new set of strategies if they are to adapt and take full benefit of AI's surge of change. The RIAA (Recording Industry Association of America) reported an estimated growth of $21.5 billion in 2000 for the music industry, which due to piracy, plummeted and lasted for almost two decades. Thanks to the mass adoption of smartphones, which helped in the rise of music streaming apps since 2005 provided hope for the music industry. RIAA predicts that for the first time in this millennium, the industry has posted an increase in revenues in three consecutive years! The music streaming industry is revolutionising the way we used to consume and enjoy music, including the revenues generated and the user behaviour analysis. In a profoundly dog-eat-dog marketplace, the fundamental brand differentiator would be how these music streaming platforms make the best use of g-algorithm-based AI engines and machine learning, to create a seamless experience for the users. By uncovering the specific tastes and preferences of every individual, streaming players are now working to build a better, more intuitive playlists. These algorithms take into consideration the music listening history of the user, analysing genres, tonality, length, pitch, tempo, vocal styles, chord progression, instrumentals used, and more, to suggest similar songs, albums, and artists that the listener might like. As a result, users are frequently exposed to personalised suggestions and playlists full of new music, keeping in line with their peculiar tastes, thereby creating an unfathomable market for music consumption. However, these music streaming services are still at a nascent stage when it comes to leveraging technology to enhance their offerings. The most flourishing practice, however, is a mix of both, with human editors analysing the data accumulated by the AI engines to supplement the algorithms further. This method is used by less number of current market dominators, but the application of AI in music still has a long way to go. While music streaming brands have come up with innovative value added services like voice assistant, automated one-touch personalised playlists, song mixing, and more, the real potential of AI lies ahead of such features. Thorough research is currently being carried out on the possibility of using state-of-the-art AI to analyse music, not just using metadata, but by examining the actual song itself, to gain a deeper understanding of the melodic medium. This presents an incredibly high prospect for its application in the music industry, and the domain, as a whole. The vital question for artists is: will AI serve the musician, or is it going to be the musician? The answer seems to be both, and top technology companies, music labels, and venture capital firms have now begun investing in the future of machine-created and/or assisted music. A prime example of the same is Google's project Magenta, which has already produced songs written and performed by AI. The company's commitment is so strong that they have allowed Magenta to be open-sourced, allowing others to create their unique products. Even Sony has created an AI system called 'FlowMachine' which released its first song called 'Daddy's Car' in 2016 and already has two million views on YouTube alone. Several musicians have, over the years, designed and created AI programmes to mix and master songs recorded in the studio, or even develop compositions and lyrics based on inputs. An excellent example of this is the Verbalizer created by David Bowie and Ty Roberts, which enables the user to input up to 25 sentences and word groups into the tool to generate potentially significant lyrical combinations. Music streaming services are currently driving the market in AI adoption, constantly experimenting with several purposes for this quickly mutating futuristic technology. Personalised music suggestions have not only been a blessing for consumers but artists as well. Working as a platform for a myriad of promising musicians to showcase their work and present it to the world, allows many musicians to have a direct audience, even before growing into a breakout star with mass recognition. As a result, users have often found gifted musicians on streaming platforms, who have later gone on to gain critical acclaim, purporting the creation of a symbiotic pathway for growth in the industry, both for the services and the artists. Hence, presenting a highly optimistic prospect for the future of AI in the industry as this will create new opportunities for brands as well. Businesses will reform their strategies according to the vast amount of data collected and analysed for more profound insights into the consumer. If anything, this sounds like a win-win for the industry, the musicians and the consumers.