From influential cultural prescribers to mere “user interfaces,” DJs have watched their power erode in the face of rising algorithms. A look back at ten years of silent transformation.
2019: Weekly radio listening still reached 89% of Americans over 12 years old. 2022: This figure drops to 82%, marking a continuous erosion of a medium that had remained stable for decades. Between these two dates, a revolution took place in silence: algorithms have supplanted humans as the primary musical prescribers.
This decade witnessed the collapse of a sixty-year-old model – that of the DJ as “tastemaker” capable of directing the listening habits of millions of people. But at what cost to musical diversity and artistic innovation?
2015-2025: Chronicle of a Documented Dispossession
The Collapse of the Radio Model (2015-2020)
PwC’s figures are unequivocal: terrestrial radio advertising revenues have declined every year since 2015. This constant erosion reflects a fundamental change in listening habits, well before the pandemic dealt the final blow.
The traditional radio industry is shaking on its foundations. iHeartMedia and Cumulus Media, the two largest American radio broadcasters, have filed for bankruptcy in recent years. Bob Pittman, CEO of iHeartMedia, had to completely redefine the economic model: “We no longer provide music to people. We provide companionship to people.”
The most brutal transformation comes in 2020. iHeartMedia lays off hundreds of radio DJs, replacing them with artificial intelligence systems. Monisha “Mo” Mann, hip-hop DJ from Fresno, testifies to this bitter reality: “They decided to replace a lot of workers, a lot of live shows, with AI… and another DJ in another state, another city.”
The Inexorable Rise of Streaming (2018-2025)
70% of Americans now listen to audio online weekly, according to 2023 Edison Research data. This massive migration to digital completely redefines the rules of musical prescription.
Spotify establishes itself as the new king of discovery. With its recommendation algorithms and automated playlists, the platform reaches hundreds of millions of users without any human DJ. But this apparent efficiency hides questionable practices: users systematically report that algorithmic curation is “impersonal.”
Even more concerning: Spotify uses practices similar to payola with its “Discovery Mode,” where labels accept reduced royalties in exchange for better algorithmic visibility. Glenn McDonald, former Spotify data scientist, explains: “The idea of payola is to substitute money for taste. In the modern version, you pay by accepting a lower royalty rate, and the algorithm plays your song more because you’re paying.”
The Podcast Explosion and New Prescription Models
42% of Americans listen to podcasts monthly in 2023, compared to only 12% in 2013. This exponential growth creates new models of musical prescription, often more specialized but fragmented.
Musical podcasts partially replace traditional DJs. However, unlike radio DJs who reached millions of simultaneous listeners, podcasters address specialized niches, reducing the overall impact of human prescription.
The Massacre of Physical Venues
Mass Club Closures
The British underground perfectly illustrates this crisis. About 400 clubs have closed in Britain over the past five years, representing more than a third of the total number. These closures deprive DJs of their natural laboratories for experimentation and prescription.
Real estate costs explode while audiences fragment across digital platforms. Without a captive audience, DJs lose their ability to test and validate new tracks in real-time, a skill historically crucial for their role as prescribers.
The Electronic Industry Resists
Paradoxically, the electronic music industry shows robust financial health. The global electronic music industry reaches $12.9 billion in 2025, representing 6% growth compared to the previous year.
However, this growth masks a profound transformation of power dynamics. SoundCloud reports a 50% increase in electronic music uploads, but this democratization of production comes at the expense of expert curation.
Algorithm: The New Master of the Game
TikTok and Pure Algorithmic Prescription
TikTok represents the culmination of this evolution: the platform has become the primary source of musical discovery, with millions of users discovering new tracks daily. The TikTok algorithm can make a track explode without any human DJ intervention.
Concrete example: the worldwide success of “Savage Love” by Jawsh 685 and Jason Derulo, which went viral on TikTok in 2020, illustrates this new logic where 15 seconds of algorithm are worth more than years of DJ expertise.
Systemic Biases in Recommendations
Academic research reveals the structural limitations of these systems. Musical recommendation algorithms tend to create “filter bubbles” and naturally favor popular content at the expense of diversity.
This homogenization directly affects musical creation. Producers adapt their compositions to algorithmic requirements rather than artistic innovation, creating a feedback loop that progressively impoverishes stylistic diversity.
Resistance and Counter-Trends
The Renaissance of Certain Genres
Not all genres suffer the same fate. UK Garage and Drum & Bass are experiencing spectacular renaissance, with a 100% increase in Garage uploads on SoundCloud in 2024. These genres still benefit from strong human curation via specialized DJs.
The African scene is also exploding: Amapiano, Afro House, and Afrobeat are among the year’s big winners, reflecting the industry’s boom on the continent. These successes demonstrate that human expertise retains its relevance for bringing new musical territories to light.
The Emergence of New Models
Female DJs finally gain visibility: female DJs saw their festival bookings increase by 40% in 2024. This progression suggests a diversification of curation perspectives, potentially beneficial for musical richness.
Alternative stations prosper. FIP Radio in France or NTS Radio internationally prove that an audience exists for expert human curation, even in an algorithm-dominated environment.
The Culture of Belonging Resists
The Tribal Identity of Electronic Music
Electronic music fans maintain a particular relationship with their music. 68% of them declare being part of something that others “don’t understand.” This tribal dimension explains why certain communities resist algorithmization.
Festivals and live events show record attendance, proof that collective experience remains irreplaceable. The need for authentic human prescription hasn’t disappeared, it has moved toward more specialized formats.
The Quest for Authenticity
The era of generative AI paradoxically reinforces the appeal for human touch. Faced with 28% of musical content now generated by AI (according to our previous article), listeners actively seek guarantees of human authenticity.
DJs become “human quality labels,” certifying that the music they broadcast has been selected by authentic sensibility rather than algorithmic calculation.
Decade Assessment: An Irreversible Transformation
Winners of the Revolution
Streaming platforms now dominate the musical economy with revenues in billions
Algorithms become the new gatekeepers, concentrating power among a few tech companies
“Algorithm-friendly” producers who master the codes of automated recommendations
Ultra-specialized niches that escape mainstream standardization
The Lost of the Transition
Traditional radio DJs: mass layoffs and replacement by AI
Medium-sized clubs: serial closures facing costs and digital competition
Mainstream musical diversity: increasing homogenization of recommendations
Serendipitous discoveries: reduction of the unpredictable in favor of optimization
Open Questions
Was this algorithmization inevitable? Data suggests yes: the economic efficiency and scalability of algorithms make any return difficult. However, the limitations of these systems are becoming increasingly apparent.
Larry Miller, director of NYU’s music business program, predicts that “we’re in the last decade of influence as we grew up with radio influence on musical listening.”
Conclusion: Human – Eternal Outsider or Next Comeback?
This decade has demonstrated that algorithmic efficiency has its limits. Users find algorithmic curation “impersonal” and actively seek more authentic alternatives.
The challenge of the coming years will be to create hybrid models that value human intuition and computational power. Because while algorithms excel at optimizing the existing, they struggle to invent the unpredictable. Yet music, by essence, feeds on the unexpected.
DJs won’t disappear, but their role is transforming radically. From mass broadcasters, they become niche curators, guardians of authenticity in a world of algorithmic artifice. Their survival will depend on their ability to reinvent themselves as credible alternatives to digital standardization.
The battle for the future of musical discovery is just beginning. And it will be played out on the ability to preserve the human in the equation, without renouncing the benefits of technology.
Coming next: “The Hidden Cost of Musical Democracy” – How the apparent egalitarianism of platforms conceals new inequalities.
