Small and medium-sized enterprises in Ghana are turning to artificial intelligence to inform business decisions, with new research showing that AI-driven analytics produce statistically significant improvements in both operational efficiency and strategic decision-making, even as cost, skills shortages, and infrastructure gaps continue to constrain how widely and how well the technology is being used.
The findings come from a study published in Business and Management Horizons, which surveyed 396 owners, managers, and decision-makers across SMEs in Ghana’s retail, manufacturing, technology, finance, and agricultural sectors. The research found that AI’s strategic value is now the most widely recognised benefit among SME respondents, with businesses reporting that AI implementation has “enhanced the decision-making process” more strongly than any other application measured.
The shift indicates that AI has moved, in the words of the study, from “a futuristic concept” to “a practical solution for enhancing business decisions” for a meaningful segment of Ghana’s SME population.
The operational gains being recorded are concrete. Businesses are using AI to automate routine tasks, personalise customer experiences based on purchase history and preferences, and apply predictive analytics to marketing and financial planning, including budgeting and forecasting.
One technology firm owner described experiencing “a substantial decrease in the amount of time spent on repetitive analysis,” freeing up capacity for innovation. A retail SME owner reported using AI tools to “monitor customer preferences and purchase histories” to improve product recommendations and customer satisfaction.
The study’s structural analysis found that AI-driven analytics have a statistically significant positive effect on both operational efficiency and strategic decision-making among the SMEs surveyed. Respondents described AI as removing guesswork from planning, with one business owner noting that AI had “eliminated the uncertainty from our strategic planning,” shifting decision-making toward data rather than instinct, while another credited AI with helping the business “predict sales trends and adjust strategies accordingly” to remain competitive.
The barriers, however, are substantial and consistently ranked. Cost emerged as the most significant obstacle to AI adoption, with respondents describing the expense of acquiring and maintaining AI systems as simply “too high for a business” of their size.
Closely behind is a shortage of skilled personnel capable of managing AI tools, a gap one manufacturing sector respondent described as the absence of “an internal technical expert who can operate or interpret the systems.”
Limited awareness of what AI can actually do for a business of their scale was also flagged prominently, with one technology start-up employee noting that colleagues continue to view AI as “exclusively utilised by large corporations,” unaware that it can be adapted for smaller enterprises.
Infrastructure constraints compound these challenges, particularly for SMEs operating outside major urban centres. One retail sector respondent put it plainly: the issue is “not always cost, but rather whether we have the appropriate infrastructure, such as cloud storage or fast internet, to support AI.”
The study also identified regulatory ambiguity as a constraining factor, noting that the absence of clear national guidelines on AI adoption contributes to “a lack of confidence in AI systems” among SME operators who might otherwise invest.
The research situates these findings within Ghana’s broader digital transformation agenda, noting that SMEs account for more than 90 percent of businesses in the country, yet fewer than 10 percent currently use AI technologies in their operations, even as the Ghana National Artificial Intelligence Strategy 2023–2033 aims to democratise access and promote inclusive innovation.
The gap between aspiration and uptake, the study suggests, is not primarily a matter of awareness alone but of accessible tools, technical capacity, and an ecosystem that supports adoption at SME scale rather than only at enterprise scale.
The study’s recommendations are directed at government, financial institutions, and industry stakeholders jointly. It calls for investment in digital infrastructure to ensure equitable access, particularly in underserved regions; targeted capacity-building and training programmes to close the skills gap; flexible financing models and innovation grants from financial institutions to lower the cost barrier to entry; and clearer regulatory frameworks to reduce uncertainty around AI adoption.
Crucially, the research emphasises that AI solutions need to be designed for SME-scale operations rather than adapted from enterprise-grade systems that are often too complex or too costly for smaller businesses to deploy effectively.
The broader implication is that the AI dividend already being captured by Ghana’s more digitally capable SMEs, those with what the study describes as “moderate digital literacy and foundational infrastructure”, could be extended across the wider SME population with the right combination of infrastructure investment, training, financing, and policy clarity.
Without that coordinated push, the study warns, the benefits of AI adoption will remain unevenly distributed, limiting the technology’s transformative potential for the segment of the economy that employs the largest share of Ghana’s workforce.
