The use of Precision Agriculture (PA) and Artificial Intelligence (AI) in agriculture is akin to being stuck on a journey with an unlabelled map or a GPS missing its coordinates. It can provide you with information, however without context you can quickly lose yourself in the data and end up way off-course. The research is scarce, both from a qualitative perspective but more so on the quantitative side. This paper examines the research available on the impact of these technologies on Small-Scale Farmers (SSF) in Sub-Saharan Africa (SSA).

The introduction of PA and AI research in agriculture is growing, and the challenge (for me at least) when reviewing agricultural economic research is looking for studies that demonstrate a cohesive central idea. In this article the study focuses on the different studies that examine the impact of AI and PA on African agriculture using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) – a mouthful indeed.

The researchers of this study applied a systematic approach using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines to investigate the adoption of precision agriculture and its socio-economic implications for small-scale farmers in South Africa (Siregar et al., 2022).

In their analysis they have combed through 182 entires for this investigation using bibliometrics. The bibliometric R-application refers to a methodological approach in research evaluation and analysis using bibliometric data (such as publications, citations, or patents) applied to study patterns and trends in research and development (R&D), including agricultural R&D.

Bibliometric methods can be used in agricultural R&D to:

• Assess the impact of research outputs.
• Understand collaboration networks among researchers or institutions.
• Evaluate trends in scientific productivity or technology development.
• Measure the influence of agricultural R&D on productivity growth in a sector, such as those seen in sub-Saharan African agricultural productivity studies​

R in this context points to the software – in this case R (a statistical computing environment) – used for bibliometric analysis. With tools and libraries like bibliometrix, researchers can quantitatively analyze large bibliographic datasets and visualize trends, such as the impact of agricultural R&D on productivity, innovation adoption, or regional differences in research emphasis​.

The research finds that from the initial 608 publications identified 182 were selected for the study. This selection is based on the criteria put in-place by the researchers. While there is a mix of publication formats what is interesting the is body of available knowledge.  The researchers have a specific goal and it is understandable to assume that an elimination process is applied to try and achieve a result that can explain the research objective initially set.

This is interesting because it demonstrates the findings of the studied analyses in a different light. One of the main findings of any technological application on African agriculture is the “promise” it finds “if” the technology is applied and the barriers the continent face when attempting to improve the livelihood of its inhabitants.

African agricultural economic research is dominated with global views on local issues. Any well-read – anyone that can read above a grade 6 level – can reach the conclusion that using technology in certain areas can improve the outcome of the process it is used for, and agriculture is not different.

PA and AI can provide the promise of improved productivity and societal welfare. It is necessary to ask then why is research scarce? if collectively we assign Millennial Development Goals to fulfill as a species, why are we not focusing on directing the resources appropriately towards the areas that would make the most impact on welfare?

I am of the opinion that is is not commercially viable.

It is not commercially viable to focus in developing improved PA and AI technologies with an SSA context because the return on investment would not recoup the costs of this research. It is a easy conclusion to reach without the study of research funding, the direction of FDI (Foreign Direct Investments) and many other economic variables can help us understand the context through which Africa as a continent can improve its societal welfare and agricultural productivity.

Research and development is the conduit through which many of the luxuries we afford today come into being. Many of the technologies and tools be it digital or analogue are a direct product of people directing resources towards a specific problem. Albeit there is inquiry into many problems, and we as a species have no shortage of problems to tackle, it does raise the question, when will the world view Africa as an economically viable endeavour for the betterment of humanity more than a resource supermarket where the global north use it to improve their well being and leave the scraps for the rest?

Research and Development of agricultural technology in Africa is funded by many well-intended individuals and institutions given the availability of all the necessary ingredients. My take is a more self directed criticism of the academic corpus as a whole. Would the commercialization of research findings increase the likelihood of Africa receiving more funding? Would the inclusion of the African citizen from all regions of Africa be worthy of inquiry if they had the financial ability – among others – to contribute to the commercialization of the findings and their propagation through markets, consumption, and the normal lifecycle of product creation and creative innovation and destruction? I wonder.