Data analytics and AI specialist Dr. Eugene Frimpong has welcomed Kwame Nkrumah University of Science and Technology’s (KNUST) decision to mandate a one-credit Artificial Intelligence course for all students, but warned that the policy will not translate into economic advantage unless it is backed by legislation, core infrastructure and a pipeline that links AI training to business and market outcomes.
Speaking to The High Street Journal, Dr. Frimpong called the initiative “a very good strategy” for a science-driven university, but noted that KNUST is likely to “be ahead of the country” given the absence of a cohesive national AI strategy.
He argued that AI education, if treated as a stand-alone literacy exercise, creates a delivery gap. He said the mandate should be supported by enabling law in the same way cybersecurity is being legislated, and underlined that AI “depends on constant electricity and broadband connectivity”, conditions that are not guaranteed at national scale.
Dr. Frimpong mapped the policy to broader implementation failures in the digital economy. He cited “lack of political will” and unfunded policies that remain “on paper” without appropriation. He said Ghana must begin extracting return on investment from the digitalisation stack, including the national ID system, e-government platforms and public-sector automation, by feeding those data assets into regulated AI systems that drive productivity.
He warned that Ghana will miss the commercial moment if AI is taught in abstraction rather than embedded in local problem-spaces such as agriculture, healthcare logistics, urban planning and resource governance. He pointed to Kenya’s use of AI in agriculture as evidence that economic value emerges only when AI is tethered to sector demands.
On market effects, he said Ghana could become “a digital coast” for remote AI hiring by foreign firms, but cautioned that without incentives for local adoption, the country risks accelerating a new brain-drain cycle. He referenced the U.S. CHIPS Act as a model for tax-based incentives to stimulate private-sector AI deployment.
He argued that a “one-size-fits-all” course architecture is inefficient for business outcomes, insisting that AI curricula must diverge by discipline, with agriculture, medicine, engineering and social sciences receiving domain-specific application paths. He called for year-one impact measurement and ethics controls to prevent academic abuse and unsafe data practices.
Dr. Frimpong said the KNUST mandate places Ghana on a necessary runway but stressed that the country must “start, and be prepared to run” if the move is to produce competitive AI capacity rather than symbolic compliance.
