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AI should change how Nigerian films can be made, but not who holds creative authority or whose culture the images represent. The evidence points to a practical middle ground: use generative AI where it expands filmmakers’ options, while addressing uneven access, cultural misrepresentation and the informal work it can displace.
What recent evidence says about AI in Nollywood
A peer-reviewed study by Godwin Simon, Thomas Poell, David Nieborg, Smith Mehta and Lorena Caminhas, published online in AI & Society on 7 August 2026, examines how generative AI is being integrated into Nigeria’s film industry. It is based on 21 semi-structured interviews with Nigerian filmmakers. The authors’ central finding is not that AI replaces filmmaking wholesale: they identify specific forms of informal labour, particularly in pre-production, as more susceptible to substitution. The University of Groningen record and abstract describe the study; its full text is embargoed until 7 February 2027, so the detailed interview methods and findings are not available in that record.
Where AI could change the industry—and what should guide that change
Access can reinforce existing production divides
AI tools do not create equal opportunity simply by being available. The study links uneven access to paid generative-AI tools with a risk of reinforcing the divide between higher-budget productions aimed at cinemas and international streaming services, and lower-budget work oriented toward domestic streaming and YouTube. If subscriptions, computing resources and relevant skills are concentrated among better-funded producers, AI may strengthen existing market divisions rather than open the field to everyone. Improving access and training is therefore part of the creative question, not a separate technical concern.
Representation needs Nigerian creative direction
The study also identifies cultural misplacement, stereotyping and what its authors call “unrepresentation” as risks when models trained predominantly on Global North data generate material about Nigerian cultures. A generated image or voice may look polished and still misrepresent a language, place, tradition or community. Filmmakers interviewed in the study respond through hybrid workflows, model customization and efforts to build localized AI infrastructure. In practice, Nigerian creators need the authority to inspect, revise and reject outputs—not just a tool that produces them.
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Track whose work shifts, not only which jobs disappear
The study’s finding about informal pre-production labour matters because work can be lost or reorganized without an entire profession disappearing. Tasks that once created paid opportunities or helped sustain working relationships among Nollywood practitioners may be absorbed by a tool. The study does not establish that all film jobs are being replaced. A responsible production should identify which tasks AI takes on, who previously performed them, and how contributors are consulted, credited and paid when their work, likeness or performance informs generated material.
A Yoruba-language feature shows one hybrid approach
Asiri Ilu Awon Osu (Mystery of Osu Land) offers a specific example, not a measure of industry-wide adoption or impact. Punch reported on 20 August 2026 that the Yoruba-language science-fiction feature was co-created by Mysterious Tech Studio and Yoruba actress Tanwa Hameed, also known as Asake Omogbajumo. The creators told the newspaper that about 80% of the film’s visuals were generated with AI tools, with the balance involving human direction and live-action performances. That percentage is the creators’ account as reported by Punch, not an independently audited production measurement. They said AI was intended to complement human creativity rather than replace actors, directors or other creative professionals; that statement records their intent, not proof of the tool’s wider labour effects. Read the report.
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The Nigeria Television Authority described the film as Nigeria’s first Yoruba photorealistic AI feature and reported that it draws on Yoruba cultural identity and traditional themes. “First” here is the broadcaster’s characterization, not an independently established industry-wide category. NTA’s account also describes festival recognition and selections. The example demonstrates a hybrid production claim; it cannot establish that AI has generally lowered costs, widened access for independent producers or improved audience response across Nollywood.
Adoption figures and Nigeria’s policy context
A 12 December 2025 article by DLA Piper Africa in Nigeria – Olajide Oyewole LLP reports that a 2024 survey found 35% of Nigerian film and TV stakeholders already used AI at work, while another 35% were considering it. The opened article does not give the survey’s sample size or methodology, so treat this as an attributed survey finding, not a census or a measure of current use. The article also discusses potential applications and challenges for the sector.
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That same December 2025 legal-industry analysis described Nigeria as having no AI-specific regulation at the time, while noting approval of a National AI Strategy and a National Intellectual Property Policy and Strategy. It also identified privacy, copyright and cybersecurity laws as relevant to AI use. This is a dated account, not a verified statement of the law in October 2026; anyone making a production or distribution decision that depends on current legal requirements should check the law’s present status.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How much should AI change Nigerian filmmaking?
It should change the available methods, not remove Nigerian filmmakers’ power to decide what a story means, whose labour it uses or how Nigerian people and cultures appear on screen. That means judging AI use by more than whether it produces an image quickly: ask whether creators can access and control the tools, whether the output is culturally grounded, and whether the people whose work is affected remain visible in decisions about credit and pay. The evidence supports experimentation with human direction and local capacity—not treating automation as a substitute for either.
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