AI Is Reshaping Nigerian Music Not Replacing It

In 2014, Harrysong was everywhere. After years grinding on the fringes, the Nigerian singer-songwriter broke into the mainstream with “Mandela”, a tribute track that travelled far beyond radio playlists. Its reach was powered largely by telecom syndication, at a time when ringback tunes were one of the industry’s most powerful distribution and monetisation tools.

That moment marked the peak of the ringback tone era, a period when Nigeria’s music industry reportedly generated more than $100 million from caller tunes alone. Long before streaming platforms took over, Nigerian music had already demonstrated a willingness to experiment with technology, often earlier and faster than many global markets.

That instinct hasn’t changed.

A History of Tech-Driven Adaptation

Nigeria’s music ecosystem has repeatedly leaned into technology sometimes eagerly, sometimes cautiously but almost always in step with global shifts. Social media quickly became a non-negotiable part of artist discovery and fan engagement. Other innovations, like NFTs and broader Web3 experiments, generated hype but failed to achieve lasting, large-scale adoption.

Artificial intelligence now sits at the centre of a similar debate.

The technology has triggered excitement, fear, and plenty of scepticism. Yet, as with previous waves of innovation, the reality is proving more nuanced than the extremes suggest.

When AI Extends a Song’s Lifespan

A recent example illustrates this shift clearly. Nigerian singer FAVE saw her July 2025 single “Intentions” resurface across social media after an AI-generated version was released by studio Urban Chords. The remix gained traction quickly, introducing the song to new audiences and giving it unexpected longevity.

The response reportedly surprised FAVE herself. Rather than pushing back, she leaned in officially re-releasing the new version in collaboration with Urban Chords. The move reflects a subtle but important change: AI is no longer viewed only as an external threat but increasingly as a tool artists can strategically engage with.

Still, the bigger question remains unanswered.

What does AI mean for the future of music and the humans who create it?

AI as an Enabler, Not a Replacement

Music creation is complex, technical, and often resource-intensive. In that sense, AI can function much like a calculator does for mathematics: not a replacement for understanding, but an accelerator for process.

There are already compelling examples of AI being used to enable creativity rather than erase it. American rapper Beanie Sigel, for instance, announced plans to use AI to create music in his original voice after a near-fatal shooting in 2014 left him unable to record traditionally.

More broadly, AI has enabled the emergence of non-human artists and AI-assisted production at scale. In Nigeria, this includes projects like Kumi Bora, described as “an emotionally intelligent AI artist making Afrobeats music,” as well as human producers such as Mykah and Eclipse Nkasi, who have released AI-generated Afrobeats albums.

Over time, however, the most sustainable use of AI is likely to be contextual, quietly embedded into workflows to improve efficiency, expand creative options, and lower barriers, without positioning itself as a wholesale substitute for human expression.

The Case for Clear Labelling

AI’s growing sophistication raises another issue: transparency.

In recent months, Urban Chords released Choir Refix, an AI compilation built on reinterpretations of popular songs. The project broke into the top 50 of TurnTable’s Nigerian Official Top 100 Albums chart, underscoring just how convincing AI-generated music has become.

That success also exposes a choice problem. Listeners should be able to decide whether they are engaging with music made by humans, machines, or a blend of both. Clear and consistent labelling of AI-generated content would empower consumers to make informed decisions about what and who they are supporting.

Implementing this transparency introduces new responsibilities across the value chain, particularly for streaming and distribution platforms that act as the primary bridge between creators and audiences.

Read More: Spotify Rolls Out Built-In Tool to Import Playlists From Other Music Services

The Unresolved Question of Licensing

Perhaps the most complex challenge lies in compensation.

There is currently no widely recognised framework governing how AI studios should pay artists whose voices, styles, or likenesses are used to train models. Several approaches are being debated:

• One-off licensing deals for the use of an artist’s likeness
• Ongoing royalty-style payments whenever a trained preset generates new work
• Sampling-style models, where a portion of revenue from each AI-generated track flows back to contributing artists

Each option carries trade-offs, but avoiding the issue altogether is not sustainable. As AI becomes more embedded in music production, licensing and remuneration structures will have to evolve with it.

Despite AI’s rapid progress, music remains more than recorded sound. Live performances, shared spaces, and the emotional energy of human connection are still central to how fans experience artists.

In recent weeks, the rising cost of Nigerian concert tickets has sparked widespread discussion. Yet those prices also signal something important: demand for live, human-led music experiences remains strong. Fans are willing to pay for moments that go beyond what algorithmically generated music can currently offer.

This experiential layer is where AI struggles to compete and likely will for the foreseeable future.

A Tool, Not the Identity

AI will almost certainly become a permanent fixture in music creation, much like Auto-Tune, once controversial, is now a standard production tool. It will shape workflows, expand creative possibilities, and carve out its own niches.

What it is unlikely to do is replace human artists as the defining force of music culture.

Generative AI musicians and projects may grow into meaningful subcultures, but the broader music ecosystem especially in Nigeria will continue to be anchored by human stories, performances, and identities. AI may disrupt the process, but it won’t replace the soul of the sound.Top of Form