Picture the scene, replaying itself in conference halls from Nairobi to Cape Town, from Lagos to Kigali: a Generative AI masterclass is in session. The room is packed, on stage, a panel discusses the national AI strategy. The audience comprises aspiring developers, data scientists, and ML engineers, furiously taking notes on Python libraries and neural network architecture. It’s a picture of progress, of a continent determined not to be left behind by the next great technological wave. But there’s a glaring, almost invisible gap in this picture.
Where are the artists? Where are the filmmakers, the brand strategists, the poets, the musicians? As Africa’s governments and private sector race to build GenAI capacity, there is a dangerous overemphasis on the technical and a glaring neglect of the cultural and creative minds, who will make this technology truly valuable to our people.
Generative AI is actively shaping the future of how we think, communicate, market our goods, entertain our children, and connect with our heritage. It is a tool for constructing reality itself. This raises a critical question we are failing to ask: If GenAI is going to write our stories, teach our youth, and sell our products, shouldn’t the people shaping it include those who understand culture, language, identity, and meaning?
What GenAI Is And Why the Creatives Are Not Optional
There is a fundamental misunderstanding at the heart of our current approach. We are treating Generative AI as a purely computational challenge when, at its core, it is a cultural one. Its primary function is not just to crunch data, but to generate content. And all content, text, image, or music is a vessel for culture.
Large Language Models (LLMs) like GPT-4, generative art platforms like Midjourney, and AI music tools’ ultimate utility hinges entirely on creative human input and sensibility. They rely on:
- Aesthetic Sensibility: An AI can generate a thousand images of a “futuristic African city,” but it takes a designer with a deep understanding of Uli art, Ndebele patterns, or Dogon architecture to prompt it to create something that is not a generic, Afrofuturist cliché.
- Narrative Coherence: An LLM can write a marketing campaign, but it takes a brand strategist and a storyteller to imbue that campaign with the right tone, voice, and emotional resonance to connect with a consumer.
- Cultural Nuance: AI can produce a soundtrack, but it takes a musician steeped in the rhythms of Highlife or the melodies of Ethio-jazz to guide it toward creating something that feels authentic and not like a soulless, algorithm-generated approximation.
Without deep creative partnership, these powerful tools will simply perpetuate existing biases, produce aesthetic monotony, and churn out generic experiences devoid of local context. We see it already. Midjourney and DALL-E are powerful, but their output is only as compelling as the user’s visual literacy and prompting skills. A ChatGPT-powered customer service bot is only as effective as the writers who define its personality and conversational style. The potential is immense, but the code is only half the story.
The Current Reality: Training for a Future That’s Already Passed
Right now, Africa’s AI talent strategy is dangerously narrow. A map of the current landscape reveals a consistent pattern:
- Government AI Initiatives: National strategies and funding are overwhelmingly directed towards building capacity in software engineering, data science, and machine learning. Take 3MTT for example.
- Upskilling Programs: Bootcamps and corporate training programs are churning out backend developers and data analysts, promising to fill the “tech skills gap.”
- Venture Capital: The funding pipeline heavily favours founders with purely technical backgrounds, often overlooking those with expertise in media, design, or cultural production.
The result is an institutional blind spot. There is a conspicuous lack of inclusion for our design schools, liberal arts faculties, brand consultancies, and media houses in the national AI conversation. We are failing to build bridges between the engineers who are building the models and the creatives who understand the people these models will serve. In essence, we are preparing for the future like it’s 2010, not 2025.
What’s at Stake: The High Cost of a Homogenised Future
If our creative professionals are left out of the GenAI development cycle, the consequences will be severe.
We risk a future saturated with homogenised content that fails to reflect the profound diversity of African nuance, language, and experience. Our digital ecosystem will be filled with stories, images, and sounds that are algorithmically generated but culturally hollow.
We will miss the monumental opportunity to export African creativity at an unprecedented scale. Instead of building our own culturally intelligent AI tools, we will remain passive consumers of technologies trained on foreign datasets and Western aesthetics. This will lead to further youth disengagement, particularly for the millions already participating in the continent’s creative economy, who will see their skills devalued in a tech-first ecosystem.
The imperative is clear. If Africa is going to shape its AI future, it needs to stop importing culture and start building its own.
Modelling a Holistic GenAI Talent Pipeline
To correct our course, we need a deliberate, multi-stakeholder strategy that places creative intelligence at the heart of our AI ambitions. This requires action on four key pillars:
- Curriculum Reform: We must break down the walls between STEM and the arts. This means introducing mandatory GenAI literacy programs within university design, mass communication, theatre arts, film, and music departments. Future graphic designers should be graduating as expert prompters; future journalists as masters of AI-assisted investigation.
- Policy and Incentives: Governments must create targeted funding for “creative tech.” This includes offering tax incentives for R&D that occurs at the intersection of AI and creative industries, and earmarking grants for startups that are not just building algorithms, but are using AI to solve problems in media, entertainment, and cultural heritage.
- Public-Private Co-Labs: We need to build physical and virtual innovation hubs that are explicitly designed to encourage collaboration. Imagine “AI + Storytelling Labs” in Lagos or “Creative AI Accelerators” in Johannesburg, where coders and creatives are co-located, co-learning, and co-building the next generation of tools and content.
- Cultural Data Investment: An AI model is only as good as the data it’s trained on. We must fund the large-scale, open-source development of African datasets. This includes digitising and tagging our vast archives of languages, dialects, heritage imagery, folklore, and contemporary creative works. This is an act of cultural preservation and a strategic economic investment.
Glimpses of What’s Possible
Globally, we’ve seen Balenciaga use AI to generate entire fashion shows, Coca-Cola launch marketing campaigns co-created with DALL-E, and Disney begin using AI in its storyboarding and design processes.
Here in Africa, the seeds are being planted. Nigeria’s Magic Carpet Studios is already exploring the intersections of animation and AI. Innovation hubs like Imisi3D in Lagos are pioneering immersive storytelling with VR and AR. Across the continent, individual creators in Ghana, Kenya, and Nigeria are using tools like RunwayML and Luma AI to create stunning visual effects that were previously impossible without a Hollywood budget.
These are the bright spots. Our task is to turn these isolated examples into a continent-wide strategy.
Our Imagination is the Ultimate Algorithm
The path forward requires a radical re-evaluation of what we consider valuable in the AI age. Technical skill is essential, but it is not sufficient. The engineers can build the engine, but it is the artists, the storytellers, and the cultural strategists who will plot the course and make it worthwhile.
We must position our creatives not as purveyors of “soft skills,” but as core shapers of meaning, product, and experience. They are the architects of context and the innovators who can transform a powerful but generic technology into something that feels uniquely, authentically African.Tech alone will not secure our future. Our code will not save us. Only our imagination will. Africa’s competitive edge will not be found just in code; it will be found in our culture, our creativity, and our context. The future is not just engineered, it’s imagined.
