Hit-making has created some of the most iconic and pivotal moments in the music industry. Hits define eras, cement the influence of artists, and shape pop culture. Today, however, many hits sound remarkably similar. Take Sabrina Carpenter’s Short n’ Sweet and Taylor Swift’s The Life of a Showgirl, for example: two chart-topping albums that, to many listeners, feel almost indistinguishable in style.
The incentive to produce hits has long driven the music industry. Labels and artists seek commercial success—high revenue and mass streaming. In the past, music titans like Britney Spears or Elvis Presley mastered hit-making while retaining distinctive sounds that made their music memorable.
Now, advancements in data-tracking technology and AI have added a new layer: formulas for predicting commercial success. Billboard charts, Spotify Wrapped, and streaming analytics all provide metrics that guide decisions on what sounds will generate popularity.
The result is an increasingly homogenous mainstream. When formulas dictate creativity, artists often prioritize replication over originality. According to a Harris Poll, 52% of listeners feel there is less variety in music today compared to previous decades. Similarly, a Rutgers study titled “Manufacturing Hits” found that machine learning algorithms which identify characteristics of popular songs tend to produce music that achieves higher commercial success and streaming numbers.
These formulas have shaped much of contemporary music. Many mainstream songs follow predictable structures: upbeat verses leading into repetitive choruses, lyrics focused narrowly on love or attraction, and shallow ballads that claim depth but rarely exceed three minutes. Artists such as Sabrina Carpenter, Morgan Wallen, and Drake exemplify this trend, though they are far from the only ones.
The obsession with charts reinforces this uniformity. Success is measured numerically, and commercial incentives often discourage risk-taking. Once an artist secures a top streaming spot, maintaining it can mean producing more of the same rather than experimenting with new sounds. Both the music industry and our culture have an intense focus on tracking this data—which means we’re allowing charts and statistics to control the public’s perception of what successful music means.
A prime example is Taylor Swift. Swift, arguably the most commercially successful artist of her generation, blocks the chart-success of other artists. She has repeatedly released multiple versions of her songs to extend chart longevity, sometimes coinciding with other artists’ releases.While claims that this “blocks” competitors can be overstated, the strategy illustrates how commercial considerations can shape music output, often prioritizing chart positions over innovation. All of Swift’s alternate versions were hardly different. Lesser-known artists with unconventional or experimental music face even greater barriers to recognition.
Social media, particularly TikTok, further intensifies formulaic production. Viral potential often dictates what songs are released, shifting focus from artistry to shareability. Prominent artists including Halsey, Florence + The Machine, Charli XCX, and FKA Twigs have expressed frustrations with public and label pressures to produce ‘TikTok music’ shifting the focus from their artistry to virality and easily-consumed content, effectively pushing the ‘TikTok’ formula.
When data guides the music industry, we center materialist values as what makes art successful; music is degrading into a replicated formula, a commodified production, a lost art that sparks comparison and scrutiny—in all, a business more than art. We are neglecting the core aspects of music: passion, expression, authenticity, creativity, experimentation. Mainstream music doesn’t leave room for good music. We don’t listen or create anymore, we track and replicate.
