By Chiamaka Okorie
Technology company ipNX Nigeria has cautioned industries against excessive reliance on artificial intelligence (AI) without first establishing reliable systems, quality data, and sustainable digital infrastructure.
The warning was issued during the 2026 IoT West Africa Conference and Exhibition in Lagos, where stakeholders gathered to discuss the future of digital transformation across the continent.
AI Is Not a “Magic Bullet”
Chief Technology Architect at ipNX, Oluwaseun Oluboyo, speaking at a boardroom dialogue titled “Tech Transformation: A Masterclass to Enable the C-Suite to Lead Digital Transformation in Nigeria”, stressed that organisations must avoid adopting technology simply because it is trending.
“AI is not a magic bullet. AI will produce nonsense faster than any human can do, so your data quality is of critical importance. Your workflow has to be just right because AI also doesn’t know when to pause,” Oluboyo said.
He explained that poor data management and weak operational processes could undermine the benefits of AI, urging firms to properly map out their systems and prepare infrastructure before deployment.
Need for Local Infrastructure
Oluboyo also raised concerns about Africa’s growing dependence on foreign-based cloud infrastructure, warning that over-reliance on external systems could expose organisations to data privacy, security, and regulatory risks.
“We can’t rely only on powerful computers located in the cloud to run our AI and digital services. Apart from delays in speed, there are also important concerns about data privacy, security, and government regulations around where information is stored and controlled,” he noted.
He maintained that building local digital infrastructure would strengthen Africa’s digital sovereignty, improve efficiency, and ensure long-term sustainability.
Preparing for Digital Transformation
According to Oluboyo, successful digital transformation begins with understanding customer needs and identifying business problems before introducing technological solutions. He emphasised that organisations must invest time in mapping data, strengthening workflows, and training staff to ensure AI adoption delivers meaningful results.