In the sun-drenched fields of Kenya, smallholder farms—plots often less than two hectares in size—have long faced an uphill battle against climate variability, pest pressures, and resource constraints.
Today, a convergence of drone technology and artificial intelligence (AI) is rewriting that story. AI-powered drones are no longer sci-fi; they’re practical tools helping Kenyan farmers monitor crop health, apply inputs more precisely, and forecast yields with unprecedented accuracy.
From flower estates in Naivasha to avocado orchards near Kericho, these “eyes in the sky” are empowering farmers to boost productivity, cut costs, and adapt to a changing climate—one flight at a time.
The Challenges of Smallholder Farming in Kenya
Approximately 73% of Kenyan farmers are small-scale producers, managing average plots of just 0.47 hectares and collectively producing roughly 78% of the country’s agricultural output.
Yet, they often lack access to timely information on soil health, pest outbreaks, and optimal use of inputs.
Climate change exacerbates these challenges: unpredictable rainfall, rising temperatures, and extreme weather events can wipe out entire seasons.
Traditional scouting methods—such as walking rows with a notebook—are time-consuming, subjective, and prone to human error. For farmers juggling multiple crops on fragmented plots, the result is wasted inputs, lower yields, and tighter margins.
What Are AI-Powered Drones?
At their core, AI-powered drones combine crewless aerial vehicles (UAVs) with advanced sensors (including RGB, multispectral, and thermal) and onboard or cloud-based AI algorithms.
When flown over fields, they capture high-resolution imagery that AI models analyse for indicators such as:
- Nutrient deficiencies (via multispectral indices)
- Early pest and disease symptoms (through computer vision)
- Canopy density and plant counts (using object detection)
These insights are delivered to farmers via mobile apps or dashboards, enabling targeted interventions—such as spot-spraying pesticides or applying fertiliser only where needed—rather than blanket treatments. The result is a more efficient use of inputs, reduced environmental impact, and better yields.
The global ag-drone market is projected to surge from USD 2.01 billion in 2024 to USD 8.03 billion by 2029, growing at a 32% CAGR, driven by the need for precision inputs and labour savings.
Lima Labs and the Rose Revolution
One of the most striking examples in Kenya comes from Lima Labs, a Nairobi-based startup founded in 2021 by Jasper Simpkin. Focused on the country’s billion-dollar floriculture industry, Lima employs drones equipped with high-resolution cameras to perform weekly “crop audits.”
Their AI-driven platform processes these images to forecast rose yields with 95% confidence, track stem density, and even predict upcoming pest pressures.
On a typical rose farm near Naivasha, Lima’s drone hovers above greenhouse rows, capturing gigabytes of imagery.
Back in the office, Machine Learning (ML) models integrate these data with on-farm weather sensors—measuring humidity, temperature, and solar radiation—to generate a 30-day production forecast.
Farmers receive email reports or app notifications detailing precisely which greenhouse zones need more water, where to expect bud break and even early warnings of Botrytis blight.
This level of predictive precision helps exporters meet strict EU quality standards, minimises post-harvest losses, and shores up farmers’ profits.
Spray Drones Transforming Crop Protection in Naivasha
Beyond predictive analytics, DJI Agras spray drones have begun appearing on farms around Naivasha—Kenya’s horticultural heartland.
A local agritech service provider recently introduced the Agras T50, a 50-litre-capacity octocopter capable of both liquid spraying and granular spreading. Operating at speeds up to 10 m/s, the drone covers up to 40 hectares per day, delivering pesticides or micronutrients with centimetre-level accuracy.
Smallholder farmers, who previously spent hours mixing chemicals and walking muddy fields, now schedule drone flights via a simple mobile interface.
The AI-driven system adjusts spray rates in real-time based on canopy density and wind conditions, ensuring uniform coverage and minimising off-target drift.
Early pilots report a 30% reduction in chemical use and a 15–20% bump in overall yield—savings and gains that can make the difference between profit and loss for a family-run plot.
Precision Crop Monitoring with Aerobotics’ Drone Scan
While Lima Labs focuses on flowers, South African agritech firm Aerobotics has extended its Drone Scan service—originally for orchards—to East Africa, including Kenyan avocado and macadamia growers.
Drone Scan flights collect multispectral and thermal imagery, which Aerobotics’ AI analyses to generate tree-level health maps, nutrient stress zones, and irrigation alerts.
For a smallholder avocado in Murang’a County, this means identifying underperforming trees before fruit drop occurs. The AI platform flags nitrogen-deficient zones, enabling spot fertilisation, and detects early signs of Phytophthora root rot, often invisible from the ground.
By linking these insights to a mobile dashboard, Aerobotics helps farmers reduce input costs, anticipate labour needs, and time harvests for peak market prices.
Integrating Drones into Digital Platforms: DigiFarm and Beyond
Tech giants and telecom companies are also integrating drones into broader digital agriculture ecosystems.
DigiFarm, powered by Safaricom, evolved from a mobile-based advisory platform into a holistic service that now incorporates drone and IoT data.
Smallholders sign up via USSD or a smartphone app to receive bundled services, including drone-captured field imagery, satellite-derived weather forecasts, soil-test kits, credit for inputs, and market linkages.
Farmers can top up airtime and pay for drone flights via M-Pesa, democratising access to aerial analytics. Pilot programs in Kisii and Homabay Counties have demonstrated that combining drone-derived insights with tangible financial options and agronomic advice increases adoption rates by over 50%, and average returns on investment exceed 2:1.
Training and Government Support for Drone Adoption
Recognising the potential, the Kenyan government is integrating AI and drones into agricultural education.
In June 2025, Cabinet Secretary Mutahi Kagwe announced upgrades to the Kenya School of Agriculture (KSA), which will equip 10 campuses with drone fleets, AI labs, and IoT infrastructure.
As reported, extension officers will learn to pilot UAVs, interpret AI-driven analytics, and guide farmers through drone-based interventions.
These efforts—coupled with short certified courses run in partnership with international agritech centres—aim to make drone literacy as common as tractor driving.
By empowering youth and county-level agripreneurs, the initiative seeks to accelerate ground-level adoption, ensuring that AI-powered drones reach even the most remote smallholder plots.
Environmental and Economic Impact
AI-powered drones help smallholders reduce their environmental footprint. Precision application slashes pesticide and fertiliser use by up to 40%, cutting input costs and limiting runoff into water bodies.
Early disease detection, achieved through targeted spot treatments, reduces reliance on broad-spectrum chemicals, thereby safeguarding pollinators and beneficial insects.
Economically, drone services—whether through cooperatives, agri-services startups, or DigiFarm bundles—offer cost-effective alternatives to manual scouting and blanket spraying.
With flight costs often subsidised by service providers or financed via microloans, farmers can access aerial insights for as little as USD 5 per hectare. Yield uplifts of 10–25% have been reported across pilot sites, translating into tangible income boosts for families living on less than USD 2 per day.
Challenges and the Road Ahead
Despite clear benefits, barriers remain. The high upfront costs of drones, batteries, and AI platforms can deter even the smallest farmers. Poor rural connectivity can hamper real-time data transfer.
Regulatory frameworks for UAV operations are still evolving, and limited local technical support poses maintenance hurdles. Weather constraints—such as heavy winds or rain—can ground drone flights at critical times.
To overcome these, Kenyan agritech stakeholders are exploring drone-as-a-service models, battery-swap kiosks, solar-powered charging hubs, and hybrid UAVs capable of low-altitude flights in gusty conditions.
Drone-as-a-Service (DaaS) models
Rather than buying expensive UAVs outright, many smallholders are tapping into “drone-as-a-service” offerings. Companies like Astral Aerial Solutions now run Kenya’s largest farm-focused drone spraying and mapping operation—farmers book flights by hectare, and Astral handles pilots, maintenance, and data analysis.
Likewise, Fahari Aviation (a Kenya Airways subsidiary) has added 14 Agras and Matrice drones to its fleet, leasing them to tea and horticulture growers who couldn’t afford their equipment. By sharing assets across cooperatives, these DaaS outfits spread costs, build local expertise, and ensure UAVs are flown by KCAA-licensed pilots.
Battery-swap kiosks
Continuous operations demand hot-swap batteries, but farms often lack reliable grid power. Kenyan innovators are borrowing from the booming e-motorcycle sector.
The SUN-RUN partnership launched the country’s first solar-powered battery charging and swapping hub at Dunga Beach, Kisumu County, in 2022, servicing motorcycles and small electric vehicles, and paving the way for drone-battery swaps as well.
Meanwhile, pan-African startup Kofa has secured funding to build a network of swap stations in Kenya by early 2026. Although initially designed for two-wheelers, these modular hubs can be easily configured to accommodate DJI and XAG drone batteries.
Solar-powered charging hubs
Beyond swapping, truly off-grid operation calls for in-field charging. The Kenya Climate Innovation Centre’s new DREEM Hub (launched on April 3, 2025) is deploying solar microgrids, cold rooms, and milk coolers across dairy and horticulture cooperatives—complete with a $460,000 revolving loan fund to make solar panels and batteries affordable.
Agritech providers can tap these same solar installations to power drone docks or even mobile charging trailers, ensuring UAVs stay aloft during critical spraying windows.
Hybrid VTOL UAVs for gusty, long-range work
When farmers require both endurance and vertical takeoff in windy, uneven terrain, hybrid fixed-wing/VTOL drones excel.
In late 2024, the Kenya Red Cross used Swiss-made Wingtra One tail-sitters to map the worst locust invasion in 70 years. Each flight lasted up to 55 minutes, covering tens of square kilometres, even in gusty conditions.
KCAA-licensed pilots now routinely fly a mix of DJI M300/M350 multirotor and fixed-wing VTOL platforms (Wingtra, SenseFly, DeltaQuad), giving service providers the flexibility to choose the best platform for each task.
As hybrid UAVs become more affordable and locally serviced, they’ll unlock large-scale crop mapping and field monitoring—even on the windiest Kenyan highlands.
Partnerships between government, research institutions, and private sector players are pushing for streamlined drone regulations and standardised data protocols, ensuring interoperability across platforms.
Conclusion
AI-powered drones are no longer futuristic novelties but practical allies for Kenya’s smallholder farmers. By delivering hyper-local insights on crop health, optimising input use, and forecasting yields, these technologies are tackling long-standing challenges—from erratic weather to pest outbreaks—head-on.
As government training ramps up, service models diversify, and costs continue to decline, the potential for smallholder productivity and resilience in Kenya is virtually limitless. Through every flight, these AI-driven machines are helping turn subsistence plots into data-driven enterprises—and that’s a revolution worth celebrating.
The founder of FanalMag. He writes about artificial intelligence, technology, and their impact on work, culture, and society. With a background in engineering and entrepreneurship, he brings a practical and forward-thinking perspective to how AI is shaping Africa and the world.
