In 2025, an entity known as Urban Chords released an AI-generated album, “Choir Refix,” which debuted at No. 43 on the Nigerian Official Top 100 Albums chart, with 834,000 on-demand streams.
Key takeaways
- Afrobeat’s global rise has collided with rapid advances in AI music generation and production tools.
- Beyond not just experimentation. AI is already influencing beat-making, mastering, songwriting, and distribution.
- The real tension is AI vs artists. But it’s also scale vs culture, efficiency vs originality.
- We must also account for economics. AI lowers production costs and speeds output in an industry built on volume and virality.
- I can’t see how the future of Afrobeat is fully AI-generated, but there’s an argument to be made for AI-augmentation.
Afrobeat reached a turning point the moment it stopped being a regional sound and became a global export. Once the genre began filling stadiums, topping international charts, and driving billion-stream economies, it entered the same pressure cooker that alters every global music movement: scale.
At the same time, AI-generated music quietly became a thing. What started as novelty tracks and experimental demos is now a full production stack, AI tools that can generate beats, suggest melodies, mimic vocal styles, master tracks, and even predict what sound might trend next. Inevitably, Afrobeat entered the conversation.
So the real question isn’t whether AI will touch Afrobeat (I’m sorry, but it already has). The question is how. This article unpacks that question.
What AI music actually means
When people say AI music, they often imagine computers replacing artists. In reality, there’s a critical distinction: AI-generated versus AI-assisted music.
AI-generated music
AI-generated music refers to systems that create entire compositions, such as beats, melodies, and sometimes vocals, based on patterns learned from massive datasets. While these models don’t understand music the way humans do, they calculate probabilities. Given millions of songs, they learn what usually comes next.
AI-assisted music
AI-assisted music, on the other hand, works more like a co-pilot. It suggests chord progressions, generates beat ideas, cleans vocals, or helps producers explore variations faster. The human still decides what stays and what goes.
What AI already does well is pattern-heavy work:
- Generating drum grooves and beat templates.
- Suggesting melodies that fit a scale or mood.
- Synthesizing or layering vocals.
- Speeding up mixing and mastering workflows.
Where it still struggles is where Afrobeat lives most deeply:
Victoria Fakiya – Senior Writer
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- Emotional context.
- Cultural nuance and slang.
- Originality beyond remixing what already exists.
Where AI is already touching Afrobeat today
AI is already inside the Afrobeat pipeline, quietly changing how music gets made.
Beat-making
AI tools dramatically speed up production. Producers can generate multiple rhythm variations in minutes, auditioning ideas that once took hours. This compresses the trial-and-error phase. A producer can spend less time searching and more time refining what actually resonates.
Vocals
AI is transforming how producers polish. Vocal cleanup, pitch correction, harmony layering, and mastering are faster and cheaper than ever. For Afrobeat, where vocals often sit lightly atop complex rhythms, this matters. Cleaner vocals mean tracks travel better across global playlists without losing their bounce.
Songwriting
AI tools can suggest hook structures, rhyme patterns, or melodic contours. Not full songs, but prompts. For artists stuck midway through a session, this can unlock momentum rather than dictate direction.
The case for AI in Afrobeat
The strongest argument for AI in Afrobeat is how it removes friction.
Faster experimentation and iteration
Afrobeat thrives on experimentation. Beats evolve mid-session, hooks get rewritten on instinct, tempos shift until the groove locks in. AI accelerates that loop. Producers can test ten variations of a rhythm, bassline, or melody in the time it used to take to build one. That speed doesn’t kill creativity; it gives artists more room to chase it.
Lower production costs for emerging artists
Studio time, engineers, session musicians, and post-production add up fast. For emerging artists, especially across Africa, AI-powered production tools lower the barrier to entry. Clean vocals, passable mixes, and professional-grade demos are now achievable without deep pockets. We can all agree that it matters in an industry where access has always shaped who gets heard.
Access for diaspora creators without studio infrastructure
Afrobeat’s global spread means creators in London, Toronto, Berlin, and Atlanta want to participate, but not everyone has access to culturally fluent producers or studios. AI-assisted tools help bridge that gap, allowing ideas to travel across borders before collaborators ever meet physically.
Global collaboration without physical borders
AI-enabled workflows make remote creation smoother: shared stems, tempo-matched sessions, instant revisions. Afrobeat has always been transnational; AI simply reduces the logistical constraint.
AI as a creative co-producer
This is perhaps the strongest argument for AI.
AI works best when it handles the repetitive, technical, and pattern-based work, freeing humans to focus on storytelling, emotion, and cultural specificity. Used this way, AI doesn’t flatten Afrobeat. It can actually give artists more bandwidth to lean into what makes the genre human.
The case against AI in Afrobeat
To a large extent, I understand the folks kicking against the use of AI in music. The resistance, as I see it, is less technophobia (because who are we kidding?) and more a cultural self-defense.
Cultural dilution and loss of lived context
Afrobeat is rooted in lived experience. The slang, the cadence, the confidence, the pain, the joy, all of it! These aren’t abstract patterns. They’re responses to specific places, histories, and social realities. AI doesn’t live anywhere. It recombines what already exists. That raises a real risk of cultural dilution, where the sound survives but the context vanishes.
Risk of soulless sound
There’s also the danger of formula. AI optimizes for what has worked before. Afrobeat’s evolution, however, has often come from rule-breaking, from unexpected rhythms to odd vocal deliveries. If creators lean too heavily on AI-generated suggestions, the genre could drift toward safe, repeatable templates. Yes, it may be catchy. But will it be memorable?
Data bias
Whose music is training the models?
AI models are trained on datasets, often skewed toward commercially successful, globally visible music. That means certain regions, languages, and subcultures within Afrobeat are underrepresented.
Whose Afrobeat becomes the default pattern the model learns?
And whose gets erased?
Ownership and royalties
Ownership and royalties complicate things further.
If an AI model trained on thousands of Afrobeat tracks contributes meaningfully to a new song, who deserves credit? The artist? The model provider? The creators whose work shaped the dataset?
The legal frameworks here are thin, and African artists historically lose out when systems are unclear.
Content vs culture.
When music is optimized for platforms, playlists, and algorithms, the incentive shifts from expression to output. AI can accelerate that shift. More songs. Shorter cycles. Less time to live with the music.
What artists, producers, and labels are saying
Inside Afrobeat’s creative community, AI has become a quiet fault line, but the conversation is no longer theoretical. Real professionals across the industry are now sharing their experiences, concerns, and hopes.
Producers who see AI as leverage
Jinmi Abduls, the Lagos-based producer, singer, and founder of Chase Music Nigeria, who has worked with Oxlade, Teni, and Joeboy, offers a nuanced perspective on AI’s role. With over 15 million career streams and a production discography spanning more than 100 tracks, he speaks from deep experience. “The next trend in music is AI,” he says. “I think it’s here to enhance our creativity and not to take it away.” His reasoning cuts to the heart of what makes Afrobeat human: “AI will never be able to be inspired. And that’s the switch.”
At the Music Business Conference in Lagos, Laolu Aranmolate, a music executive at Nooks Records, described AI as an “enhancement tool.” He revealed that he uses Lambda AI software to cut time on tasks like mixing and mastering, as well as Deezer’s developing tools for mix settings with precision. His philosophy is that “You craft your soul around the music,” and AI supports (but doesn’t hijack) creativity.
Mykah (born Aramide Babalola), a Nigerian-UK-based producer, has taken experimentation further. He recently released The Experimentalist, an eleven-track album created using the AI platform Suno. Speaking about his process, he explained, “I wrote a prompt saying ‘I want an Afrobeat song with so-and-so lyrics,’ it generated multiple versions, and I chose which I liked more.” For Mykah, the urgency is real: “You can make an album in a day. So all I can say is AI is here to stay, and we as creatives will need to embrace it and find a way we can work with it.”
Artists who view it as an existential risk
Puffy Tee, a veteran music producer whose career spans decades of Nigerian music evolution, pushes back firmly against the notion that AI can replicate human creativity. In a recent interview, he insisted that while technology can replicate patterns, it can never replace the soul of human artistry.
“For me, it’s all about storytelling and authenticity,” Puffy Tee explained. “When you create music that tells a genuine story, speaks to people’s experiences, and captures the essence of a moment, it transcends trends and becomes timeless.”
He acknowledged AI’s technical capabilities but stresses its limitations: “The spark, the vibe, the human touch — that’s what humans bring to the studio. AI can mimic rhythms, but it can’t replicate the energy, passion, and imperfections that make music feel alive.”
Excel Joab, A&R Manager at AWAL Africa, delivered one of the most pointed critiques at the Lagos Music Business Conference. Challenging AI’s depth, he said: “AI cannot make Laho (song by Shallipopi), AI didn’t live in Benin. AI hasn’t done Yahoo. AI is trained on human input. It is not sentient.”
Labels experimenting quietly vs publicly
Akachi Igboko, A&R Manager at Mavin, one of Africa’s most influential labels, offered a pragmatic view at the same conference. “It comes down to the individual use,” he said, citing his own use of Splice, a sample library he turns to for melodies. He posed a critical question: “Do you use it to accentuate what you are trying to do, or as the bedrock?”
The legal landscape remains murky, and labels are watching closely. According to recent reports, major music companies like Sony, UMG, and Warner Music Group are currently contemplating licensing and equity deals with AI music startups Klay Vision, Udio, and Suno, aiming to set a precedent for ethical AI training and artist compensation.
The players who are meeting halfway
Geraldo Ramos, Co-Founder and CEO at Music AI, offers a broader industry perspective on how AI is redefining musicianship itself. “In 2026, the definition of a musician will inevitably change,” he predicts. “If making a full song can be done with a text prompt, then ‘someone who can make music’ suddenly describes almost everyone. But that doesn’t diminish the value of artists who’ve spent years mastering their instruments; it actually raises the bar for what musicianship means.”
Audiomack Co-Founder and CMO David Ponte sees the shift toward democratization accelerating. He predicts that platforms and labels will increasingly embrace audio modification (e.g., remixes, edits, sped-up versions, and fan-made variations), allowing fans to engage with music beyond passive listening. For Afrobeat’s global future, he’s bullish: “The ascendant generation of African superstars, like Tyla, Wizkid, Amaarae, Davido, Tems, and Burna Boy, have gained massive popularity on the continent, but have yet to dominate US charts. This changes in 2026.”
What’s striking across all these voices, from Mavin’s A&R to independent producers, from veterans to digital natives, is that no one fully rejects AI. The disagreement isn’t whether it exists; it’s whether it should be addressed. It’s a question of how far it should go, who gets to decide, and whether the genre’s soul survives the journey. As Osarumen Osamuyi, producer and technology analyst, put it: more than tools, it is instinct that will define the success of AI adoption in Afrobeat.
What the future likely looks like
- Human-led, AI-assisted workflows will dominate. Artists and producers will use AI for speed, including drafting beats, cleaning audio, and testing ideas, while keeping final creative decisions in human hands.
- We’ll also see a stronger push for ethical datasets, clearer attribution, and better royalty frameworks. As awareness grows, creators will demand transparency, for instance: whose music trained this model and who gets paid when it profits?
- AI will quietly reshape timelines, budgets, and global reach. The genre will continue to evolve, just as it always has, absorbing new tools without surrendering identity.
FAQs
Can AI create Afrobeat music?
Yes, AI can generate beats, melodies, and even vocal patterns that resemble Afrobeat.
Are AI-generated songs legal?
The legality is still evolving. Copyright laws vary by country, and questions about training data, ownership, and royalties remain largely unresolved. If an AI model were trained on copyrighted material without permission, legal challenges are likely. Always consult legal expertise before commercial release.
Will AI replace Afrobeat artists?
No, but it may replace some tasks artists currently do. Artists who use AI as a tool will likely gain efficiency, while those who expect AI to replace creativity will be disappointed. The future is tending towards augmented, not automated.
Conclusion
AI won’t replace Afrobeat, but it will reshape how it’s made.
The artists and labels that use it well will expand access, speed experimentation, and lower barriers for emerging artists.
Used carelessly, it risks flattening culture, erasing context, and turning a living genre into algorithm-friendly output.
The difference will lie in control.
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