While utopian views persist, there are also some waves of dystopia. There are concerns about what AI means for creativity, cultural authenticity, intellectual property, and job availability within the cultural industries. For instance, writers are prized assets in Nollywood. Though most are poorly paid, multiple writing jobs mask precarious wages. However, AI tools like ChatGPT are threatening writers’ engagement. Storyboarding artists are among the worst hit in these early stages of AI adoption. Another strand of dystopia emerges from observed cultural contradictions in the creative processes. The notion is that Generative AI tools do not have sufficient data for culturally specific creative output that speaks to the multiplicity of cultures and traditions in Nigeria. For context, Nigeria boasts over 300 ethnic groups and 500 indigenous languages. Each ethnic group could be categorised as “nations” in anthropological sense as they are characterised by distinctive histories, cultural elements, and senses of identities. West-trained AI tools such as ChatGPT and Jasper lack requisite data capturing the nuances of Nigerian ethnicities while video generation tools like Google’s Veo 3 often falls short in character consistency and linguistic properties. There are also experiences of cultural misappropriation such as wrongly assigned names and misrepresentation of customary norms.

There are also concerns around intellectual property and contractual complications in a context characterised by weak regulatory and policy landscapes. A lot of labour relations within the Nigerian creative industries continue to operate under informal agreements and personal relationships. This has its benefits, but it also exposes workers to precarious labour conditions with minimal legal protections. This mode of industry self-governance is ingrained in the sustainability of the industry. However, there are permutations that AI companies may exploit existing regulatory loopholes in ways disadvantageous to creatives. The fear of heightened precarity of work is also rife in these industries as is the case in global cultural industries. There are permutations around likely reduction of jobs in the pre-production and post-production phases, but there is minimal conviction of outright replacement.

Following the ongoing wave of AI in the Nigerian creative industries and Africa more broadly, Africa-focused AI startups are gearing up to penetrate local markets to address contextual demands. Plotweaver and Awarri are among the notable AI start-ups in this adventure. Plotweaver’s Founder, Oluwole Fagbohun, has started intense publicity and partnership with Nollywood and other stakeholders ahead of its public launch. Plotweaver intends to be the go-to place for cultural producers in under-served markets, while Awarri is much invested in providing solutions to linguistic challenges in the AI space by training Large Language Models using indigenous data. For Plotweaver, operating in the more developed countries is presumably less cumbersome due to advanced infrastructure and availability of open-source data. In contrast, penetrating Africa entails peculiar localisation strategies to aid local adoption. Oluwole has spoken about the challenging infrastructural climate and dearth of policy support for AI startups in Nigeria. Yet, Plotweaver aims to invest locally to be positioned for the projected £20 billion by 2030 African creative economy boom.  The startup is already rivalling Awarri in indigenous language investment as it is already developing its Orisa Itan 1.0 model which is trained to capture African languages, dialects, and cultural contexts.

As contending voices continue to mark the adoption of AI in the Nigerian creative industries in these early stages, the actual manifestation of the concerns and postulations remain subject to empirical work. Unpacking these dynamics in Nigeria and elsewhere necessitates critical media industry research that questions how AI intersects with the political economy of cultural production through the lived experiences of creatives and operational accounts of AI start-up executives. Such empirical adventures must take cognizance of the nuances of power relations within the creative industries. Essentially, attention must be on the institutional, economic, and techno-cultural realities that shape the dynamics of AI in these industries. Significant to this conversation is how what we are currently witnessing connects to the broader history of the industries, pointing out patterns of continuities and departures from established norms. In a context like Nigeria with historically weak creative industry policies, it will be productive to see how policy gaps interface with the informal dynamics of work in shaping the implications of AI for creative workers. And of vital importance is the question of industry sustainability in inherently precarious contexts, such as the Nigerian creative industries. These and other relevant research concerns would help provincialize AI and creative industries research, not only in Nigeria, but in other contexts.

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