Adoption, Barriers, and Scaling Opportunities of Artificial Intelligence and Internet of Things in the Zimbabwean Food Manufacturing Industry

The adoption of Artificial Intelligence (AI) and the Internet of Things (IoT) offers significant opportunities to enhance competitiveness, efficiency, and sustainability in Zimbabwe's food manufacturing sector amid the global shift towards the Fourth Industrial Revolution (4IR). However, the adoption rate of these technologies remains low. This study examines the current state of AI and IoT adoption in Zimbabwe's food manufacturing sector, identifies key barriers hindering their implementation, and proposes scalable solutions. Using a mixed-methods approach that combines descriptive and explanatory designs, this research collected data through a semi-structured survey and analysed it using descriptive statistics, binomial logistic regression and exploratory factor analysis (EFA) in R (R Core Team, 2023). The study found that AI and IoT adoption in food manufacturing was 16.7% (95% Confidence Interval [CI]: 9.0% - 28.3%). These findings also revealed that company size is not a significant predictor of AI adoption, indicating that other factors are more influential. Key barriers identified were categorised into organisational and data challenges, technical and financial challenges, and leadership and regulation challenges. The most significant obstacles are insufficient data for training, lack of key skills, high costs of implementation, and infrastructural deficiencies. The study proposes a multifaceted strategy to scale AI and IoT adoption, such as integration of the technologies into industry certifications, public-private partnerships with the government on policy development, and developing adaptable technology solutions. The study also emphasises leveraging industry expertise, fostering organisational buy-in, and providing comprehensive employee training to overcome barriers. It also highlights the need for ongoing investment, research and innovation to address the complexities of adopting scalable technology solutions tailored to local needs.