Africa’s supply chains have similar challenges to many faced globally, however, the lack of infrastructure, connectivity, and reliable supply presents unique challenges, from fragmented logistics networks to unpredictable demand and environmental pressures.
These hurdles often lead to inefficiencies and often increased costs, while delays such as recent port congestion and poor cargo management technology in South African ports that can hinder economic growth, chasing away potential investors.
However, artificial intelligence (AI) is emerging as a transformative tool to optimise supply chain management, offering solutions tailored to Africa’s complex landscape. By leveraging AI’s predictive analytics, automation, and real-time data processing, businesses across the continent are overcoming longstanding barriers and achieving greater efficiency and sustainability.
Africa’s Supply Chain Challenges
Africa’s supply chains are often hampered by structural and environmental factors. Poor road and rail networks, coupled with unreliable port operations, create bottlenecks in transportation.
For instance, moving goods across borders in the African Continental Free Trade Area (AfCFTA) can be delayed by bureaucratic customs processes and inconsistent regulations. Additionally, rural areas, where much of Africa’s agricultural production occurs, lack robust last-mile delivery systems, leading to post-harvest losses estimated at 30–40% for some crops.
Demand volatility, driven by seasonality and economic fluctuations, further complicates inventory management. Climate conditions often exacerbate these issues, with droughts and floods disrupting agricultural supply chains. These challenges demand innovative solutions that can enhance visibility, agility, and cost-effectiveness.
The Role of AI in Supply Chain Optimisation
AI addresses these challenges by enabling data-driven decision-making and automation. Predictive analytics, powered by machine learning (ML), improves demand forecasting by analysing historical sales, market trends, and external variables like weather patterns.
This allows businesses to optimise inventory, reducing overstocking or shortages.
AI-driven logistics tools optimise routing and scheduling, minimising transportation costs and delays. Additionally, AI enhances supply chain visibility through real-time tracking and digital twins—virtual replicas of supply chain processes that simulate scenarios to mitigate disruptions.
In Africa, where data is often siloed or incomplete, AI’s ability to process unstructured data, such as invoices or customs documents, streamlines operations and improves compliance.
Recent Examples of AI in African Supply Chains
TradeDepot: Sustainable Sourcing and Waste Reduction
TradeDepot, a Nigeria-based B2B e-commerce platform, is leveraging AI to transform supply chains for consumer goods across Africa. Operating in countries like Nigeria, Ghana, and South Africa, TradeDepot uses AI-based analytics to optimise sourcing and distribution for retailers and manufacturers.
The platform’s AI tools analyse data from diverse markets to identify opportunities for onshoring production, reducing carbon footprints by minimising long-distance imports. For example, TradeDepot’s AI-enabled sourcing systems track product origins to ensure ethical and sustainable practices, aligning with global standards.
Additionally, AI-driven lifecycle analysis tools monitor product lifecycles, promoting recycling and reducing waste. These efforts have lowered operational costs and enhanced sustainability, with TradeDepot reporting improved efficiency in serving Africa’s growing consumer base.
Twiga Foods: Connecting Farmers to Markets
In Tanzania and Kenya, Twiga Foods uses an AI-powered platform to connect smallholder farmers with buyers, addressing last-mile delivery challenges. The platform employs AI to analyse demand for agricultural products, such as bananas and tomatoes, across AfCFTA markets.
By reducing reliance on middlemen, Twiga ensures farmers receive fair prices while retailers benefit from a consistent supply. AI also streamlines compliance with cross-border trade regulations, such as rules of origin, cutting delays at borders.
In 2024, Twiga’s AI-driven logistics optimised delivery routes, reducing transportation costs by 20% and improving delivery times for perishable goods, thus minimising post-harvest losses.
Zimbabwe’s AI-Powered Grain Silos
In May 2025, Zimbabwe launched AI-powered grain silos in Kwekwe with a 56,000-tonne capacity, designed to enhance food security. These silos integrate AI and Internet of Things (IoT) technologies to monitor storage conditions, such as temperature and humidity, in real time. By predicting spoilage risks, the AI system has reduced post-harvest losses by an estimated 15%, a significant improvement for a country prone to drought-induced food shortages.
The silos also use AI to optimise inventory allocation, ensuring efficient distribution to areas of high demand. Despite challenges like high setup costs, this initiative demonstrates AI’s potential to bolster agricultural supply chains in Africa.
Sanofi’s Inventory Risk Management
Global pharmaceutical company Sanofi has implemented AI to manage its supply chain in Africa, particularly in Nigeria and Kenya. Facing volatile demand for medicines, Sanofi’s AI tools predict inventory risks with 80% accuracy, avoiding €300 million in potential revenue losses.
By analysing real-time data on disease outbreaks and healthcare needs, the AI system adjusts inventory levels to prevent shortages or overstocking. This has improved service levels by 65%, ensuring the timely delivery of critical drugs. Sanofi’s success highlights how AI can enhance resilience in Africa’s healthcare supply chains, where disruptions can have life-or-death consequences.
Challenges and Opportunities
While AI offers immense potential, its adoption in Africa faces hurdles. Limited digital infrastructure, such as unreliable internet connectivity, hampers real-time data collection. Data availability is another issue, as many businesses lack comprehensive datasets to train AI models. Additionally, a shortage of skilled AI professionals slows implementation. However, these challenges present opportunities for innovation.
Partnerships between governments, tech firms, and universities can bridge skill gaps, while investments in 5G and IoT infrastructure can enhance connectivity. Initiatives like TradeDepot’s collaboration with local producers show how public-private partnerships can scale AI solutions.
An AI Path Forward
AI is proving to be a game-changer for Africa’s supply chains, addressing inefficiencies and fostering sustainability.
As Africa aims to integrate into global trade networks through AfCFTA, AI can provide the tools to compete in a complex marketplace. By investing in infrastructure, talent, and collaborative ecosystems, African businesses can harness AI to build resilient, efficient, and sustainable supply chains, driving economic growth and environmental stewardship hand in hand.
