How African farmers are utilizing AI and drones to reimagine what’s doable

It’s early morning in Accra, Ghana. Darlington Akogo stands on the fringe of a 20-hectare cashew farm with a drone controller in hand and eyes mounted on the digital chook slicing throughout the sky, scouting for bother. In a couple of minutes, the drone will ship again megabytes of images—leaf textures, cover well being, chlorophyll patterns—searching for indicators of illness, poor progress, or nutrient deficiency.

However the true magic begins after the flight ends. That’s when Akogo’s agritech startup, KaraAgroAI, goes to work. “This tree is diseased,” he says, pointing to a purple circle on his pill. “And these rows right here want extra nitrogen.”

A number of years in the past, a analysis like this is able to’ve taken weeks—if it occurred in any respect. Now, in a matter of hours, farmers in Ghana, Nigeria, and throughout the continent are getting one thing as soon as unimaginable: instantaneous, personalised, and predictive farm intelligence.

An agronomist with AI in its mind

KaraAgro AI was born from a easy however cussed drawback: Africa’s farmers are surrounded by knowledge—soil, solar, rainfall, yield—however disconnected from perception. The startup, based in Ghana, got down to bridge this hole. 

When the startup launched, the crew constructed a cellular app that permit farmers take pictures of their crops so the app may detect ailments. However the method was restricted. It nonetheless relied on farmers bodily strolling to affected crops, recognizing issues manually.

KaraAgro pivoted to drone-based scanning, layering AI on prime to automate illness detection, observe maturity ranges, detect water stress, and establish areas that require fertilisation. “The bottleneck is expert labour,” stated Akogo. “So that you both have to coach sufficient people, otherwise you create an AI system that comprises this information and make it low-cost, accessible to farmers.”

Now, KaraAgro’s instruments are being utilized by Ghana’s Ministry of Meals and Agriculture, in addition to the German improvement company GIZ. In a single challenge, their crew travelled throughout all of the nation’s cashew-growing areas, coaching extension officers to fly drones and use KaraAgro’s software program to interpret the info. “The farmer doesn’t must be the person of the AI system,” Akogo defined. “They’re the beneficiaries of the insights.”

KaraAgro’s AI instruments are additionally serving to plant breeders create higher-yielding, disease-resistant seed varieties. “We’ve completed this for cowpea, soybeans, and maize,” stated the founder, describing how their drones scan experimental plots containing hundreds of seed varieties. The AI then analyses these plots, serving to breeders establish which of them carry out finest beneath native circumstances.

On farms throughout the continent, Synthetic Intelligence and drone expertise like KaraAgro’s have gotten important for farmers to diagnose crop ailments, estimate yields, and scale back fertiliser waste. These instruments should not solely serving to farmers change into extra productive, however they’re additionally filling a essential hole in agricultural experience on the continent.

In Nigeria, Built-in Aerial Precision (IAP) affords drone-enabled precision agriculture to everybody from Dangote Sugar to smallholder cassava farmers in Oyo State. With customized drones and AI-powered flight planning, the startup doesn’t simply detect ailments, it treats them. Its drones can spray pesticides, broadcast seeds, and unfold fertiliser with surgical precision. “We’ve seen farmers reduce enter prices by 30% whereas rising yields,” stated a spokesperson.

The place KaraAgro focuses on analytics and plant breeding help, IAP is constructing an end-to-end aerial farming system, from {hardware} gross sales to pilot coaching and AI-powered post-flight evaluation. In areas with low connectivity, the system runs offline. AI fashions are compressed, quantised, and deployed through edge computing, making high-tech accessible even in areas with out web.

Each corporations are tackling a essential scarcity of expert labour and know‑how amongst farmers throughout the continent. 

Agriculture stays a cornerstone of the continent’s economies, accounting for about 16% of GDP on common and instantly using over 60% of the labour power. In a number of nations, this reliance is much more pronounced; as an illustration, agriculture contributes practically 36% of Ethiopia’s GDP and employs 73% of its workforce.

But most of Africa’s farming continues to be carried out utilizing rudimentary strategies. Smallholder farmers, who usually domesticate plots smaller than two hectares and produce as much as 80% of the continent’s meals, usually battle with low productiveness, restricted entry to trendy instruments, and a extreme lack of extension companies and technical help. These constraints have made it practically unimaginable for farmers to attain the complete potential of their land.

By integrating AI and drone applied sciences, KaraAgro, IAP, and different startups are working to fill that hole. Their instruments diagnose crop issues and embed agronomic experience instantly into the sphere, providing scalable, tech‑enabled surrogates for labour that merely don’t exist.

“You want agronomists, soil scientists, plant pathologists,” Akogo defined. “However we are able to’t practice sufficient of them quick sufficient. So as an alternative, we’re constructing an AI system that encodes their information and makes it accessible at scale.” 

This reality is just not misplaced on governments throughout Africa. In June 2025, the Kenyan authorities introduced a curriculum overhaul on the Kenya Faculty of Agriculture to incorporate AI, drones, and Huge Information, a strategic step to modernise agricultural training and enhance tech fluency amongst future agronomists. In Nigeria, the nation’s apex IT company, the Nationwide Data Know-how Growth Company (NITDA), can be trying to incorporate AI and drone expertise, amongst different Fourth Industrial Revolution (4IR) applied sciences, to reinforce meals safety. 

The flight isn’t frictionless

However even for innovators, flight isn’t frictionless. A latest report by the GSM Affiliation discovered that almost all use circumstances of AI in Kenya, Nigeria and South Africa have been in agriculture and meals safety. The report additionally famous that for the expertise to ship sturdy socioeconomic progress on the continent, there must be extra efforts in tackling digital abilities shortages and getting extra smartphones in folks’s fingers. 

For KaraAgro and IAP, low digital literacy amongst farmers has confirmed to be one of many largest challenges. To resolve this, each corporations depend on human discipline brokers to deploy drones and collect knowledge.

Sooner or later, Akogo sees a workaround the place farmers don’t want smartphones, apps, and even digital literacy to learn from AI. As a substitute, they’ll carry a small system with simply two buttons. “You press one to gather the info, and the opposite to ship it,” he explains. “Even when the AI works, it means little if farmers can’t function it. 

Past digital literacy, lack of funding is one other hurdle for farmers in accessing AI and drone expertise. Nearly all of African farmers are smallholder farmers and lack the dimensions or assets to afford the companies of AI and drone expertise corporations like IAP and KaraAgro. The truth is, each corporations primarily serve center to large-scale farmers. 

For smallholder farmers, KaraAgro often affords companies at subsidised prices, usually with help from improvement businesses. “We group farmers in clusters primarily based on proximity to one another and crop sort in order that they’ll entry our companies collectively at a diminished price,” stated an IAP spokesperson. “ We additionally work with farmer associations and different companions that may subsidise these companies for smallholders.”Whereas challenges are presently aplenty, each corporations agree: that is only the start. In a couple of years, AI will probably be totally built-in throughout all the farming cycle, from seed choice and land preparation to reap forecasts and market pricing. “The actual purpose,” in accordance with Akogo’s dream, “is a system that may detect an issue and repair it routinely. That’s the place we’re going.”

Akogo’s dream is a light-weight robotic left on the farm that scans crops, identifies points, and treats all of them with out human intervention. 

This report was produced with help from the Centre for Journalism Innovation and Growth (CJID) and Luminate.

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