A widening gap between academic qualifications and practical workplace capability is increasingly constraining Nigeria’s preparedness for artificial intelligence (AI), according to corporate leaders.
Speaking at BusinessDay’s Talent Management Conference 2026, held under the theme “Employability Reimagined: Thriving in Nigeria’s AI-Driven Work Economy”, they argued that, although interest in AI is growing, Nigeria’s workforce is still “not yet AI-ready”.
According to them, Nigeria’s challenge is not a lack of interest in AI, but a lack of deliberate capability-building. Degrees alone, they argued, will not prepare the workforce for an AI-driven economy.
Progress therefore will depend on mindset shifts, skills-focused learning, stronger corporate involvement and partnerships that extend training beyond urban centres. Without these changes, Nigeria risks falling behind in a global economy where capability, not credentials, increasingly defines value.
That is because the rules governing work, talent, and employability are being rewritten at an unprecedented speed. Also, Nigeria, Africa’s largest talent hub, finds itself at a critical crossroads to redefine productivity and accelerate global competition.
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Rethinking talent: from certificates to capabilities
Joshua Ademuwagun, HR director at Pernod Ricard Nigeria argued that while academic degrees remain valuable, they are no longer sufficient on their own. Employers, he added, are now more interested in the problems candidates can solve than the certificates they hold.
For him, the starting point must be a shift in mindset as Nigerians need to think globally rather than locally if they are to compete in an AI-driven economy.
For example, long-term projections places Nigeria among the world’s largest economies by 2050 and should therefore prompt urgent preparation. Although 2050 appears distant, he warned that technological change is moving far faster than most people expect.
“The first thing is to become visionary and understand that we are on a global stage,” he said, adding that correcting mindsets makes it easier to correct behaviour.
Ademuwagun also stressed that the future of work is increasingly skills-based. Citing the World Economic Forum Future of Jobs outlook, he said analytical thinking, creativity and AI literacy are emerging as core skills globally.
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Capability gaps in AI adoption
Turning to how AI is currently used in Nigeria, Dotun Adeoye, co-founder of AI in Nigeria, said many professionals still treat AI as a search engine rather than a problem-solving tool.
In his view, a major gap lies in how people approach work. Rather than designing workflows and applying AI to solve specific business problems, many users focus on surface-level tasks.
He also highlighted weaknesses in what he described as “sub-skills”, including communication, judgement and critical thinking. These, he said, are essential when working with AI, particularly in assessing outputs and avoiding errors or hallucinations.
AI literacy itself remains uneven, he added, noting that deeper understanding must cut across industries rather than being confined to technology roles.
Corporate responsibility and grassroots inclusion
Addressing the role of organisations, Adeoye said companies must play a stronger role in widening access to AI skills, particularly at the grassroots because it is part of a broader industrial shift rather than a passing trend.
He therefore pointed to the importance of partnerships and hubs, noting that collaborative learning environments accelerate skills transfer. Drawing on the experience of AI in Nigeria, he said hubs that bring together researchers, policymakers, startups and students help demystify AI and speed up adoption.
This can be done under corporate social responsibility, which can be deployed more strategically by supporting training hubs and partnering with organisations already embedded in communities. Interestingly, he cited examples from Borno state where partnerships helped sustain AI training initiatives that might otherwise have struggled.
For individuals, Onuora said AI can also be a learning companion. With careful prompting, he said, professionals can use AI tools to design personalised learning paths, provided they critically review outputs rather than accepting them at face value.
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Why training often fails to deliver results
On the organisational challenge of training, Olateju Olugbenga, consultant, people transformation at Phillips Consulting argued that many companies fail to see returns on AI training because learning is poorly designed.
Training, she said, is often treated as a standalone event rather than being tied to business outcomes. As a result, employees attend courses that have little relevance to their actual work.
According to her, organisations need to start by defining what they want to achieve, then map AI tools to workflows and identify where human judgement remains essential. Learning interventions should be embedded into daily work and measured by improvements in performance, not attendance or feedback forms.
“Work is everything,” she said, adding that learning should be designed around how work is done, not separated from it.
Recruitment, CVs and the unintended consequences of AI
The discussion also touched on recruitment, where AI-generated CVs are reshaping hiring processes. Olugbenga observed that many applications now appear polished and impressive, often masking gaps in real capability.
She said some candidates rely heavily on AI-generated content without fully understanding or reviewing it, creating challenges for recruiters who must now sift through highly similar applications.
To manage this, she noted that employers are increasingly turning to AI-based assessments, sentiment analysis and skills testing to identify genuine capability. Used properly, she said, AI can also help organisations analyse workforce data more accurately and identify hidden gaps.
