Written by Reese Lamping
History of Spotify and AI
Artificial intelligence is no stranger to Spotify’s operational and logistic efforts. Spotify’s Vice President of Engineering stated that “machine learning is at the heart of everything we do at Spotify,” and it is evident that their position as the largest music streaming service globally has been catalyzed by their adoption of AI technology (Kaput, 2019). Before developing DJ, Spotify used AI and machine learning to analyze consumer listening behavior and pinpoint pattern recognition. This is showcased by Spotify’s personalized recommendations that are located for each user on the home screen. Spotify specifically uses reinforcement learning which advances past typical machine learning to use “environmental signals to optimize toward a long-term reward” (Kaput, 2019).
This includes evaluating both historic and current listening behaviors (including songs skipped, songs played all the way through, songs played most often, and so on) to craft new recommendations to listeners, helping them find new music. Similarly, Spotify is using AI to curate and design playlists for listeners. These playlists range from circulating their most listened-to songs to resurfacing some old favorites and pushing new music from smaller artists with similar sounds to their favorite songs.
Finally, Spotify has used AI and natural language processing to cultivate a natural language search technique for users. This eliminates the need for users to search specific titles/terms in order to find accurate results and instead allows users to type in keywords that match the desired search item. Since natural language search is capable of comprehending semantic matches between phrases and words, searches don’t have to be as specific to produce accurate results. Overall, these three particular uses of AI allow Spotify to be the most technologically efficient, advanced, and personalized music streaming service which furthers its market share and allows them to be the most user-friendly streaming platform.
There are numerous implicit ways in which Spotify’s extensive use of AI has streamlined its functionality. The music industry is beginning to see a full-circle production distribution process that is spearheaded through AI. AI, specifically machine learning, is being used in music composition “to generate new music fragments or ideas, which are then combined into a complete piece of music by a human composer” (Konieczka, 2023). This allows for more accessible ways for artists to produce music and allows for more artists to infiltrate the industry. Furthermore, this music is then released on Spotify (either independently as Spotify has allowed users to upload their music directly to their platform since 2018 through Spotify for Artists, or through their label) and introduced through the AI algorithm to be marketed toward listeners.
Now that AI music composition is gaining popularity, AI is directing the music industry and the process from start to finish. AI both helps Spotify build a larger portfolio of available music and helps them to distribute the music to an appropriate audience. All of this to say, AI and machine learning are unavoidable in the music industry and Spotify has catalyzed its success in the streaming industry by adapting and implementing AI quickly and effectively.
Figure 1 includes a succinct timeline of Spotify’s acquisitions and adoptions of AI throughout history.
Figure 1: Timeline Showcasing Spotify’s AI Acquisitions and Logistics Improvements. Source: Kaput, M. (2022, September 19). How Spotify uses artificial intelligence-and what you can learn from it. Marketing AI Institute.Visualization via author
breakdown of the technology
The main focus of this analysis is Spotify’s current and future implementations of AI and the impacts which will follow. Spotify’s most considerable AI advancement is the launch of its DJ program. Spotify DJ, at its core, is “a personalized AI guide that knows you and your music taste so well that it can choose what to play for you,” that also “will deliver a curated lineup of music alongside commentary around the tracks and artists we think you’ll like in a stunningly realistic voice” (Naomi, 2023). DJ was programmed using Spotify’s partnership with Open AI and voiced by Spotify’s Head of Cultural Partnerships, Xavier “X” Jernigan. Along with developing the most innovative, advanced, and creative AI software program in the music streaming industry to date, Spotify’s DJ program is also showcasing Black voices in an industry to which they have previously been neglected by having a Black man represent the voice of DJ.
Spotify has been the first to execute user-first, personalized listening programs, such as their Weekly Discovery, Daily Mix, and Recommendation programs that have been in play for years. They were also one of the first digital streaming companies in the market. Due to its historical presence and application of innovative listening enhancements, Spotify has been able to capture and maintain more market share than any other streaming platform to date. Apple Music is second in line for market share ownership; however, they are only holding 15% of the market share, which is less than half of Spotify. Figure 2 (located below) showcases a graphical representation of the market share divide in the music streaming industry.
Figure 2: Percentages of Market Share Represented by Top Global Streaming Services in 2021 Source: Music streaming market share and Revenue Statistics: Details on the biggest music streaming services. SiriusXM Music for Business. (2023, January 27).
Spotify DJ allows Spotify to uphold its reputation of putting its users first and constantly working to enhance its listening experience. DJ is no more than what the name speaks.... a pocket DJ that talks to you about the music, plays old favorites and new discoveries alike, and switches up the vibe according to your mood. A photograph displaying the features and logistics of DJ mode is attached below in Figures 3, 4, & 5.
Figure 3: Image via author
Figure 4: Image via author
Figure 5: Image via author
Impact of AI on the Music Streaming Industry
AI is at the basis of operations for every major player in the music streaming industry. Likewise, AI is vertically integrating into the music production process. In order to remain competitive, streaming companies must offer similar features on their platform as the front-runner, Spotify, does. For example, one of Spotify’s most anticipated and beloved features is their “Yearly Wrapped” system that they provide users with each December. This system provides users with their top artists, genres, songs, listening habits, and so on from the year. Spotify launched the Yearly Wrapped feature in 2016, while Apple Music waited until 2019 to launch its comparative version. Timely and personalized innovations like these keep Spotify the number-one streaming service in the world.
The conglomerate of AI-powered enhancements on Spotify’s roster is keeping audiences engaged and is aiding in sustaining Spotify’s competitive advantage. While most streaming platforms have caught up with most of Spotify’s previous AI-driven features (similar to the Discover Weekly recommendation feature, the Daily Mixes, and so on), DJ was launched “to attract and retain users who want a more lean-back experience while introducing a new feature that can’t be quickly copied by the competition” (Perez, 2023). This can further differentiate Spotify from its competitors and cause a mild disruption (or at least a speedbump) in the streaming industry by continuing to focus on integrating user-first, AI-based enhancements.
With every major advancement comes a multitude of critiques and a lurking sense of the unknown. While DJ is mainly disrupting the industry in terms of competition between streaming services, AI is disrupting the music industry by impacting production. AI can assist greatly in searching through millions of songs to expose listeners to smaller artists or generate playlists that best fit their interests. However, AI can also cause a lot of animosity in terms of the creative side of the music industry. AI, while powered/programmed by humans at its core, is still viewed by society at large as inhuman and often frightening. Similarly, there are many genres of music (Rap, RnB, Jazz, etc.) that have immense historical ties to underrepresented communities. Nearly every genre of popular, modern music is/was created from the work of Black individuals. An article aptly titled “How Black People Created Every Music Genre in America” displays the tagline: “America’s love for Black culture, but not Black people has erased African Americans’ role in pioneering American music.” Black people have been erased from rightful credits to music production, and this issue is likely to be heightened by AI music production.
Since “AI only exists in the algorithm of the coder and not in the cultural milieu in which human beings exist,” AI (in its current state) remains partially inhuman and cannot appropriately replace the human experience (Roy, 2020). Since Black people make up only “8 percent of employees in tech jobs,” there is a blatant lack of representation in the tech industry (Brown et al., 2023). How can we expect non-Black people to attempt to represent Black culture accurately? Likewise, how can we ethically produce music with AI that offshoots from genres created by the Black community without crediting them for the original work? Overall, AI has phenomenal impacts on the music streaming industry in terms of streaming and distribution, but major pitfalls in terms of music production. The gap of connecting technology and centuries of culture is something that AI cannot currently bridge, and the industry is likely to see animosity as AI becomes a more prevalent factor in music production.
Conclusion
While Spotify has been a frontrunner in the AI field for a decade, its increased infusion of AI into its algorithmic content suggestions has put it into the spotlight with its AI DJ. Consumers return again and again to Spotify largely for its enhanced personalization that few other music streaming platforms can match. While AI is central to that personalization, it hasn’t surfaced without baggage and consumer retaliation. It is also worth considering how this technology might further perpetuate algorithmic biases that disproportionately affect Black musicians.
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