Three Ways AI is Reshaping the Music Business
The role of artificial intelligence (AI) tools in business and the global economy is a hot topic across industries. This is not surprising given the fact that AI has the capacity to effect tremendous transformations in the way businesses interact with their respective consumers. This future of a business landscape reshaped by technology is no longer something organizations can ignore. 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 advantage of AI’s wave of change.
How impactful will AI be? Well, according to a recent report by McKinsey, 70 per cent of companies will likely adopt at least one type of AI technology by 2030. The same report says AI also has the potential to deliver additional global economic activity of around $13 trillion by 2030, or about 16 per cent higher cumulative GDP compared with today. For the music business, AI may serve as one of the most influential tools for growth, as we enter an era where humans – from artists and songwriters to A&Rs (artists and repertoire) and digital marketers in labels – will be complemented by AI in various forms. The introduction of mature AI will ultimately allow creatives and corporations alike to reimagine the creative process, target new fans, and identify the next set of musical stars with greater accuracy and precision than we ever imagined. We, as a business and culture, need to embrace AI as an enablement tool to shape the music business of tomorrow.
Music that Combines Emotions and the Power of Machine Learning
The big question for artists is: will AI assist the musician or is it going to be the musician? The answer appears to be both, and top technology companies, music labels, and venture capital firms have already begun investing in the future of machine-created and/or assisted music. For instance, Google has already shown a deep commitment to AI music, with its Magenta project which has already produced songs written and performed by AI. Google’s commitment to developing AI in music is so strong, that the organization allowed their project Magenta to be an open-sourced, allowing other coders and developers to create their own unique products such as a note predictor through AI predictive learning. Likewise, labels like Sony created an AI system called FlowMachine, which released an AI-created song called “Daddy’s Car” in 2016, which has already racked up over two million views on YouTube alone. The software was able to analyse a database of songs to follow a particular musical style, ultimately creating similar compositions. Many of these advancements still require a human element and so will not be replacing artists any time soon. Still, the ability for this technology to adapt and learn an artist’s writing style and sound can help songwriters, producers and artists around the world take their creativity to a whole new level, making songwriting, producing, and mixing even more competitive in the years to come. In order to stay competitive, the creatives of the future need to develop tech-savvy skills to harness these new tools that will soon enter the market.
Personalized Marketing To Music Fans
Because listeners have limited time for music consumption, one of the biggest challenges for any manager, artist or label is the point at which a fan discovers a new, competing artist. Maintaining fan loyalty is such an important business objective that according to the International Federation of the Phonographic Industry (IFPI), record companies are estimated to invest $4.5 billion annually worldwide in A&R-targeted marketing. This represents about 26 per cent of industry revenue. The same report found that the entry-level spend to break an artist is somewhere between 500,000 to 2 million dollars. This represents a significant investment from the labels, which is why AI is so critical to ensuring records show a significant ROI. To do this, labels need the technological ability to break down and analyze the billions of streams they collect a year. According to BuzzAngle Music’s 2018 Year-End Report, audio on-demand streams set a new record high in the US of 534.6 billion total streams. This number rose 42 per cent over 2017 when audio on-demand streams reached 376.9 billion streams. With so many users around the globe streaming, the need for a technology to handle this influx of data will be critical to identify which fans will enjoy which artists music.
That is why platforms like Spotify have invested significant resources in machine learning not only in its consumer products such as Discovery Weekly, a playlist that pulls in a weekly selection of music tailored to a user, but overall making its product smarter. This includes acquisitions such as music intelligence company Echo Nest for $100 million, and smaller AI startup Niland, which helps make recommendations and search results smarter.
These investments are all geared towards one simple goal: help the fan find the best music possible for their specific taste and interest. As AI continues to mature across the music business, fans and artists will greatly benefit.
Leveraging AI to Identify the Next Musical Stars
A&R has always been a tricky business. It requires shuffling through thousands of songs and beats to find those few golden nuggets. Since technology has lowered the barrier for creating and putting music online, streaming platforms have become saturated with new music. For instance, Spotify recently confirmed that it’s adding 20,000 new tracks to its service every day, totaling over seven million-plus tracks each year. That is why AI has become a critical tool to assist in the A&R process, and companies across the board are taking notice.
In March 2018, Warner Music Group acquired Sodatone, a Toronto-based tech start-up with an algorithmic platform that combines social, streaming, and touring data to identify promising unsigned artists. Streaming giant Apple is also investing heavily in musical A&R, including its acquisition of Asaii, a startup which specializes in A&R-boosting music analytics. Both acquisitions are part of a larger trend towards searching for technologies that can analyse various industry data points on up and coming artists and predict who the next big stars may be. Although most music industry executives believe that AI will never completely replace A&Rs, it will certainly change the way the industry goes about searching for and evaluating talent.