As artificial intelligence reshapes economies, industries and societies around the world, one question continues to loom large across Africa: will the continent become a meaningful producer of AI technologies, or simply a consumer of systems built elsewhere?
For Dr Najeeb G. Abdulhamid, the answer may determine whether Africa captures the economic and social benefits of the AI revolution or remains dependent on technologies designed for other realities.
In an exclusive interview with AIBase.ng reporter Ahmad Ibrahim, Abdulhamid shared his perspectives on the future of AI in Africa, the risks of technological dependence, the opportunities for Nigerian innovators and why local participation in AI development matters more than ever.
Abdulhamid noted that the views expressed during the interview are his personal opinions informed by his research and professional experience. They do not represent the views or policies of Microsoft or any other organisation with which he is affiliated.
According to him, the most important question facing AI today is not simply what the technology can do, but who gets to benefit from it.
“I am most interested in ensuring that AI expands people’s agency and economic opportunity rather than simply automating existing work,” he told AIBase.ng.
In the African context, he believes that means building AI systems capable of helping workers, educators, entrepreneurs and public institutions solve real-world problems, particularly in environments where connectivity, computing resources, language support and data availability remain limited.
“The question I find most important is not merely what AI can do, but who gets to benefit from it and who participates in shaping it,” he said.
Africa’s biggest AI misconception
According to Abdulhamid, one of the most common misconceptions about artificial intelligence in Africa is the belief that AI is a finished product that can simply be imported and deployed without adaptation.
He argues that AI systems are shaped by the environments in which they are developed, including the languages, data, assumptions and institutional priorities embedded within them.
“A system that performs well elsewhere may misunderstand African languages, occupations, cultural practices or infrastructure constraints,” he said.
For that reason, he believes Africa must stop viewing itself solely as a market for AI products developed elsewhere.
Instead, the continent should actively participate in defining what useful, responsible and locally relevant AI looks like.
“Africa therefore needs to see itself not merely as a market for AI, but as a participant in defining what useful and responsible AI should be,” he said.
Why foundations matter before scaling AI
As governments and businesses increasingly embrace artificial intelligence, Abdulhamid cautions against rushing into large-scale deployment without building the necessary foundations.
According to him, reliable electricity, affordable internet connectivity, computing infrastructure, representative datasets, skilled talent and accountability mechanisms must all be developed alongside AI applications.
“Scaling applications without those foundations could increase dependence, exclusion and harm faster than it creates durable value,” he warned.
He also rejected the idea of treating Africa as a single AI market.
Instead, he believes technologies should be tested and evaluated within specific countries, languages, sectors and communities before broader deployment.
“Systems must be evaluated within particular countries, languages, sectors and communities before being expanded,” he said.
The risk of becoming an AI consumer
One of Abdulhamid’s strongest warnings concerns Africa’s long-term role in the global AI economy.
While imported AI technologies may deliver short-term benefits, he believes relying entirely on foreign systems could leave African countries dependent on external infrastructure, standards and decision-making processes.
“Africa may gain useful services in the short term but surrender much of the long-term value and decision-making power,” he said.
In such a scenario, African users would generate valuable data, while intellectual property, high-skilled jobs, and commercial returns accrue elsewhere.
He also sees a bigger cultural risk.
“If Africans do not participate meaningfully in building these systems, our languages, knowledge, social structures and policy priorities may remain peripheral to their design,” he said.
Which jobs face the greatest disruption?
When asked about AI’s impact on employment, Abdulhamid identified jobs involving highly repetitive and digitised cognitive tasks as among the most exposed.
These include clerical and administrative work, data entry, basic customer support, bookkeeping, back-office operations, and some entry-level positions across technology, finance, and business process outsourcing.
However, he cautioned against assuming that exposure automatically translates into unemployment.
“In many occupations, AI is more likely to change tasks than eliminate the entire job,” he explained.
According to him, the workers most vulnerable to disruption may ultimately be those who lack access to training, digital tools and opportunities to transition into higher-value roles.
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The skills Nigerian youth need now
For young Nigerians preparing for an AI-driven economy, Abdulhamid believes technical skills alone will not be enough.
While coding remains valuable, he argues that future success will depend on combining technical literacy with domain expertise, critical thinking and execution skills.
“The advantage will increasingly belong to people who can combine AI with judgment, domain knowledge and responsibility,” he said.
He encourages young people to develop AI literacy, understand the strengths and limitations of AI systems, build expertise in specific industries, strengthen their analytical and communication skills and learn how to transform local problems into sustainable solutions.
“Coding alone is not a sufficient future-of-work strategy,” he said.
Are Nigerian universities moving fast enough?
Abdulhamid believes progress is being made in Nigeria’s higher education sector, but not at the pace required to meet future demand.
Some universities have introduced AI programs, innovation hubs and research collaborations, which he describes as encouraging signs.
However, he argues that isolated examples of excellence are not enough.
“Adaptation is happening, but not quickly or evenly enough,” he said.
According to him, many institutions still require stronger computing infrastructure, updated curricula, research funding, faculty support and interdisciplinary approaches to AI education.
More importantly, universities must move beyond teaching students how to use AI tools.
“They should teach students how to test, adapt, govern and create AI for Nigerian problems,” he said.
The growing threat of misinformation and deepfakes
As generative AI becomes more accessible, Abdulhamid sees misinformation and synthetic media as one of the most serious challenges facing societies worldwide.
“It is a serious and growing threat because AI reduces the cost and expertise needed to manufacture persuasive text, audio, images and video at scale,” he said.
He believes the danger is particularly significant during elections, public health emergencies, security incidents, and periods of social tension, when citizens must make decisions based on incomplete information.
Yet he argues that the biggest risk extends beyond people believing false content.
Repeated exposure to manipulated media, he says, can create what researchers often call a “liar’s dividend,” in which authentic evidence is dismissed as fake.
“The deeper danger is not only that people will believe false material,” he explained. “Repeated exposure to synthetic media can also create a situation where genuine evidence is dismissed as fake.”
To address the challenge, Abdulhamid advocates a combination of trusted journalism, public education, platform responsibility, provenance systems and rapid institutional communication.
Building AI around African realities
A recurring theme throughout the interview was the importance of ensuring AI systems reflect African realities.
According to Abdulhamid, local communities should not simply serve as sources of data for AI development.
Instead, language communities, cultural custodians, subject-matter experts and intended users should participate in defining problems, determining how data is used and evaluating system outputs.
“It must begin with participation rather than extraction,” he said.
That approach becomes particularly important when dealing with local languages and indigenous knowledge.
He argues that African-language AI requires investment in ethically sourced datasets, support for oral communication patterns, accommodation for low-bandwidth environments, and careful consideration of intellectual property rights and community consent.
“Indigenous knowledge should not simply be scraped into a dataset,” he said.
“Consent, attribution, community authority and the right to withhold sensitive knowledge must be respected.”
What Nigeria must do to become an AI producer
Rather than funding isolated pilot projects, Abdulhamid believes Nigeria should focus on building what he describes as a complete AI production system.
That includes strengthening electricity infrastructure, broadband access, cloud computing, university research, talent development and responsible data governance.
He also sees opportunities for Nigeria to focus on sectors where local context provides a competitive advantage.
“Nigeria does not need to reproduce every layer of the global frontier-model industry immediately,” he said.
Instead, he points to opportunities in language technologies, agriculture, healthcare, education, finance, public services and the creative economy.
Those areas, he argues, offer opportunities for Nigerian innovators to build AI solutions grounded in local realities while addressing pressing societal challenges.
The AI development Africa is underestimating
Despite the excitement surrounding large AI models, Abdulhamid believes that some of the most important innovations may emerge from much smaller, more focused systems.
“I believe people are underestimating the importance of smaller, locally adapted AI systems,” he said.
Rather than a single breakthrough model, Africa’s most transformative AI applications may be tools that help farmers access information through voice interfaces, assist healthcare workers with documentation, support teachers in adapting learning materials or enable small businesses to serve customers across multiple languages.
He also believes African workers themselves are often underestimated.
“The important innovation may occur in how people combine AI with local expertise, social networks and institutional practices,” he said.
For Abdulhamid, Africa’s AI future will not be determined solely by advances in algorithms or computing power.
Instead, it will depend on whether Africans participate in shaping the technology, build local expertise, and ensure that AI reflects the realities, languages, and priorities of the communities it is meant to serve.
“The question is not whether AI will affect Africa,” he said. “The question is whether Africa will help shape what AI becomes.”
