Online Reporter
Engineer Tapuwa Justice Mashangwa
Technology will forever be evolving and changing and for agriculture, Artificial Intelligence (AI), has opened the doors to a novus mundus (new world). As 2025 comes to an end it is important to note that sub-Saharan Africa (SSA) has not been left behind and is leveraging AI to transform its agricultural sector, enhancing productivity, sustainability and food security. With the region’s population projected to double by 2050, exceeding 2.5 billion people, AI-driven technologies can help address pressing challenges such as food insecurity, environmental degradation and economic inequality.
The AI conversation in the agricultural sector began with questions like: What is AI? How can we apply it to farming and agribusinesses? What software and hardware does it need? What are the energy requirements for its exploitation? To what extent can it be utilised? Is it secure? Which companies can help us integrate it at farm and at agribusiness level? Where can employees be trained on its use? Are there lecturers qualified at university level? Etcetera. In essence AI has brought to the agricultural sector a conversation no one anticipated, but a dialogue necessary.
The utilisation of AI is in the areas of precision farming, crop disease detection and pest management, yield prediction and forecasting, soil analysis and management, automated irrigation systems and smart greenhouses.
AI-powered precision optimises farming resources for optimum crop yields and reduces environmental impacts. Technologies like satellite imagery, drones and geographic information systems monitor crop health, soil moisture and nutrient levels in real-time. AI-driven systems help detect crop diseases and pests, enabling targeted interventions thus reducing crop losses. For instance, the Pest Monitoring and Surveillance of Tomato Tool (PeMOST) uses satellite images and AI algorithms to provide early warnings for tomato farmers.
In the field of yield prediction and forecasting AI-powered systems can analyse and provide data regarding crop yields, empowering farmers to plan fertiliser and water usage more effectively which significantly aids in resource allocation planning which reduces waste and improves decision-making. Insights on soil health can be made enabling farmers to make informed decisions about fertilisation, irrigation and crop selection. Furthermore, the soil moisture content can also be analysed allowing the collaboration of moisture sensors with automated irrigation systems (AIS), which minimises water waste and increases water-use efficiency. These automated systems have led to smart open-field and greenhouse farming. AI-driven sensors optimise environmental parameters like humidity, light levels and temperature in greenhouses, which improves crop growth as all crop requirements are met. Smart farming also reduces energy consumption.
All these benefits contribute to more sustainable agricultural practices, reduced negative environmental agribusiness impacts and conserves natural resources.
In most of its application AI provides quantitative and qualitative production and processing data when it comes to value addition industry its use limits resource wastage, provides actionable insights, enabling farmers to make informed decisions whilst also automating tasks, reducing labour costs and progressing operational efficiency.
The AI enable yield prediction allows farmers and agribusiness to use AI to plan harvesting and improve marketing strategy implementation, execution, management and new policy adaptation. An area the agribusiness sector in SSA many are not yet aware will change dramatically with the increasing investment in the energy sector specifically hydroelectric projects and solar farms is with the utilisation of automated farm machinery. AI-powered tractors and drones can perform tasks like planting, spraying and harvesting with precision and efficiency.
Supply chain management with AI backing can track produce quality (size, humidity, ripeness, rot, diseases etc.), permitting more transparent and efficient supply chain management. This in turn will optimise the value addition process leading to greater produce supply consistency and quality.
AI-driven market platforms can connect farmers to buyers, providing real-time market data, price updates and logistical support. This supports farmers and agribusiness to make informed decisions, reduce post-harvest losses, and increase profitability.
Some success stories of AI in SSA include Aerobotics, a South African company that uses drones equipped with AI-powered cameras to monitor crop health, detect pest infestations and optimise irrigation schedules. A Kenyan company, Apollo Agriculture, employs machine learning algorithms to assess creditworthiness, aiding farmers to secure financing for seeds and fertilisers. Fermeta uses AI-powered cameras and sensors to monitor crops for disease and pests, reducing crop losses and pesticide usage.
Constraints SSA faces when it comes to AI require can be mitigated through: expanded digital infrastructure; affordable, high-quality and accessible data internet and subsidised data plans. Another way to fast-track growth and use of AI is through training farmers, agricultural professionals and agricultural government and private sector personnel in AI-driven technologies.
As always availability of sustainable funding is also necessary to support the development and adoption of AI-driven agricultural technologies.
Once SSA farmers and agribusiness use AI our deficiencies regarding food security, sustainability, and economic growth will improve substantially.
Eleanor Roosevelt once said, “The future belongs to those who believe in the beauty of their dreams”. AI is an African dream tool at our fingertips.
The writer is Eng. Tapuwa Justice Mashangwa, GCEO Emerald Investments, CEO DataFarm, CEO Emerald Agribusiness and CEO TranslateZW. He can be contacted on +263771641714 and email: [email protected] or [email protected].
