As the 2026 FIFA World Cup, co-hosted across the United States, Canada and Mexico, draws near in June and July, a new digital trend has taken social media by storm: football fans are leveraging artificial intelligence to mass-produce viral team support anthems that rack up millions of streams across YouTube, TikTok and Instagram. What began as a novel creative experiment has now ignited urgent industry-wide conversations around intellectual property, artist compensation, and the inherent value of human creativity in the age of generative AI.
Oddly enough, many soccer supporters have openly expressed a preference for these homemade AI tracks over official releases commissioned by FIFA. The governing body tapped popular musicians Jelly Roll and Carin Leon for its official anthem, and global superstar Shakira also dropped a highly anticipated World Cup track last week. Still, the grassroots AI anthem movement continues to build massive engagement and excitement across social platforms.
The trend traces its origins to February, when French creator Crystalo – who bills himself as France’s “premier AI musical creator” on Spotify – released *Imbattables*, a rousing tribute to the French men’s national team. The track’s format, which opens with a call-and-response segment listing star players including Kylian Mbappé, quickly caught on. It was soon followed by a Brazilian take that adopted the same name-chanting structure paired with a trending phonk melody. Guilherme Maia, the Brazilian producer behind the track who creates under the artist name M4IA, explained that he built the song by layering original components, with AI acting only as a creative assistant for specific elements.
In the months that followed, AI-generated anthems for other top contending nations – including Portugal, Argentina, and Germany – flooded major streaming and social platforms, earning widespread praise from fans. While the Brazilian track loosely followed the French prototype, most subsequent releases copied Maia’s formula almost verbatim: they reuse the signature phonk beat, list each squad’s key players, and close with a shoutout to the team’s “king” – Cristiano Ronaldo for Portugal, and Lionel Messi for Argentina, naturally.
Maia, for his part, frames the wave of emulation as nothing new. “What I see happening now is more about people following a trend or trying to recreate a feeling,” he told AFP, noting that artistic imitation has long been a core part of music culture. He remains enthusiastic about the creative doors AI opens for independent producers, but he also acknowledges the technology introduces uncharted legal and ethical questions around authorship and copyright. “In music, there are clear rules. You can’t just copy someone else’s work or use samples without permission, even if AI is involved,” he emphasized.
Unlike many AI creators who generate full tracks from a single text prompt on tools like Suno, Maia stresses he built his Brazilian anthem from the ground up, only using AI to assist with select production elements. But industry experts point to broader systemic gaps in credit and compensation that run far deeper than individual creator choices. Jason Palamara, assistant professor of music technology at Indiana University, explains that current generative AI models operate with profound opacity when it comes to training data: it is almost impossible to track if copyrighted work from human artists was used to train the models, leaving those creators uncompensated and uncredited. “It had to come from somewhere,” Palamara noted.
AI-generated music also carries common quirks and limitations that mirror the inconsistencies often seen in AI-generated visual art. For example, one fan-made AI anthem for Portugal was delivered with an accidental Brazilian accent, and another AI track for Colombia mispronounced star James Rodríguez’s first name with an English inflection instead of the correct Spanish pronunciation. Palamara added that most current AI-generated music also tends to lack the textural complexity of work created entirely by human teams, noting that AI outputs are often streamlined single products rather than layered works built from multiple overlapping creative contributions.
Still, not everyone sees these limitations as a downside. Morgan Hayduk, co-CEO of music rights technology firm Beatdapp, points out that many fans engaging with these AI anthems are not looking for high art in the first place. “There seems to be a cohort of people who actually don’t care,” Hayduk observed. “They like the music, and they like the back story that it came from a large language model and not a songwriter or a group.”
For the current stage of generative AI development, Hayduk noted that quick, customizable tracks built for fan chants or promotional content are a perfectly logical and popular use case – even as the industry grapples with how to regulate and adapt to the new technology. “Knowing what goes into a generative output, like a World Cup fan song, is the thorny Rubicon that the music industry has to cross now,” he said.