How AI Could Transform Agriculture in Ghana — The $100m Degas Bet, the FarmSense Soil Revolution, and the Race to Feed a Continent

How AI Could Transform Agriculture in Ghana — $100 million from Degas is scaling AI‑driven satellite monitoring across 122,000 acres, boosting smallholder farmer incomes with a 95% repayment rate. FarmSense AI soil analysis delivers up to 60% yield increases. Darli AI provides regenerative farming advice in 27 languages to 110,000 farmers. Our deep‑dive analysis reveals the technologies, startups, investments and policy framework driving Ghana’s AI‑powered agricultural transformation — and three scenarios for the future of the sector that feeds the nation.

Executive Introduction

How AI Could Transform Agriculture in Ghana — The $100m Degas Bet, the FarmSense Soil Revolution, and the Race to Feed a Continent

The hoe and cutlass have been the symbols of Ghanaian agriculture for generations. They represent a sector that employs the majority of the workforce, contributes significantly to GDP, and sustains millions of livelihoods. Yet they also represent a sector trapped in a low‑productivity equilibrium — where yields lag behind global averages, post‑harvest losses eat into profits, and smallholder farmers remain locked out of formal finance.

Artificial intelligence is beginning to change that. Across Ghana, a new generation of agritech startups is deploying AI‑powered tools that are already delivering measurable results. Soil intelligence platforms are boosting yields by up to 60 per cent while reducing fertiliser waste. Autonomous robots are planting seeds and applying fertiliser without human intervention. Satellite monitoring systems are scanning thousands of acres from space, predicting crop health and identifying pest outbreaks before they become visible on the ground.

The investments are significant. In August 2025, President John Dramani Mahama secured a $100 million commitment from Japanese firm Degas Ltd to scale AI‑driven satellite monitoring and precision agriculture techniques, with the goal of making Ghana Africa’s first AI‑powered agricultural hub. Already, Degas has financed more than 86,000 smallholder farmers across 122,000 acres of farmland, helping to double farmer incomes with a 95 per cent repayment rate. Later that year, Google announced a $37 million investment across Africa, part of which includes its first AI Community Centre in Accra focused on developing AI‑driven tools to improve hunger forecasting, enhance crop resilience, and support smallholder farmers.

The policy environment is aligning. Ghana’s National AI Strategy, launched on 24 April 2026, explicitly identifies agriculture as one of eight priority sectors for AI adoption, with the goal of developing AI tools trained on Ghanaian soil, rainfall and crop cycles. The strategy targets AI’s contribution to reach 500 billion Ghanaian cedis (approximately $45 billion) to GDP by 2035.

This profile examines how AI could transform agriculture in Ghana. It analyses the specific technologies — soil intelligence, autonomous robotics, pest detection, satellite monitoring, and blockchain traceability — that are already being deployed. It profiles the startups and investors driving the transformation. It assesses the policy and infrastructure gaps that remain. And it maps three scenarios for the future of AI in Ghanaian agriculture. For the millions of smallholder farmers who sustain the nation, AI is not a distant promise. It is a tool that is already boosting yields, cutting costs and opening access to markets and finance. The question is not whether AI will transform agriculture in Ghana. It is how fast that transformation will reach the farmers who need it most.

The Soil Intelligence Revolution — FarmSense and the 60 per cent Yield Boost

The foundation of any farm is the soil. Yet for most smallholder farmers in Ghana, understanding soil health has been a matter of guesswork. Expensive laboratory tests are inaccessible, fertiliser recommendations are generic, and the result is either under‑fertilisation that limits yields or over‑fertilisation that wastes money and harms the environment.

FarmSense, an AI‑powered soil intelligence platform developed by Ghanaian startup Sesi Technologies in partnership with KNUST’s DIPPER Lab, is solving this problem. Launched in October 2025, FarmSense combines hardware, software and machine learning to deliver real‑time soil analysis, crop recommendations and nutrient planning directly to farmers. The device measures key soil parameters, including pH, electrical conductivity, moisture and temperature, and processes that data through AI models trained on local conditions.

The results have been striking. FarmSense has been proven to boost yields by up to 60 per cent while supporting climate‑smart agriculture by optimising fertiliser use and reducing emissions. At its launch, Deputy Minister of Food and Agriculture John Matthew Kofi Setor Dumelo, speaking on behalf of the sector minister, said the ministry was committed to making FarmSense accessible to farmers across the country. The platform has received backing from the UK’s Research and Innovation for Sustainable Agriculture (RISA) Fund, which supports AI innovation for smallholder farmers.

Isaac Sesi, CEO of Sesi Technologies, has taken FarmSense through rigorous field validation, working with partner institutions to ensure the AI models are trained on localised data. The project is part of the Africa Agri‑Tech Knowledge Transfer Partnership (KTP), designed to support smallholder farmers with tools that are both scientifically robust and practically accessible.

The potential for scale is significant. FarmSense is now being rolled out across additional regions, with partnerships including an MoU with Agrinvest to transform youth agriculture through soil intelligence. Training programmes on soil health management, data collection and productivity improvement are being delivered to farmers across the country. For the smallholder who has never known the precise pH of their soil, FarmSense offers not just data but a pathway to higher yields, lower costs and sustainable farming.

The table below summarises key AI soil intelligence and crop monitoring platforms operating in Ghana.

Platform /Developer /Core AI Function/ Yield Impact

• FarmSense Sesi Technologies (Ghana), Real‑time soil analysis, crop recommendations, nutrient planning Up to 60 per cent increase
• AyaGrow Aya Data (Ghana), AI‑powered advisory for smallholder and commercial farmers Productivity and risk management
• 3Farmate FAMA 3Farmate (Ghana), Autonomous planting, fertilising, weeding and spraying Reduction in manual labour, precision application

The Robot That Plants Its Own Seeds — 3Farmate’s Autonomous Agricultural Robotics

If soil intelligence represents the software of AI agriculture, autonomous robotics represents the hardware. Ghanaian startup 3Farmate, founded in a university dorm room by Clinton Anani and Elijah Ocupualor, has built what it calls FAMA — an AI‑powered autonomous robot capable of planting seeds, applying fertiliser, weeding and spraying crops across real farm environments.

Unlike many agricultural robots that rely on GPS for navigation — a technology that can be unreliable in remote areas with poor satellite coverage — FAMA navigates using a vision‑based AI system. This means the robot can see its environment, identify rows of crops, and navigate between them without pre‑programmed routes. The result is a machine that makes farming processes simpler by planting seeds and applying fertiliser, weed, and spray – all without human intervention.

The innovation has attracted significant attention. In April 2026, the Ministry of Food and Agriculture publicly endorsed the shift from the “hoe and cutlass” era to modern technology, citing 3Farmate as a leading example. The company has been featured in multiple outlets as a symbol of what Ghanaian youth can achieve when AI and agricultural expertise converge.

The economic implications are substantial. Smallholder farmers in Ghana spend countless hours manually planting, weeding and applying fertiliser. The labour constraints are especially acute during peak planting seasons when labour is scarce and expensive. By automating these tasks, FAMA not only reduces labour costs but also ensures precision — fertiliser is applied exactly where needed, seeds are planted at optimal depth and spacing, and weeding is done without damaging crops.

The broader vision, articulated by the founders, is to democratise access to agricultural robotics. Rather than each farmer owning an expensive robot — an impossibility for smallholders — 3Farmate envisions a service model where robots are deployed on a pay‑per‑use basis, bringing autonomous precision agriculture within reach of the farmers who need it most.

Pest Detection and Disease Management — AI That Sees What Humans Cannot

Pests and diseases are among the most devastating threats to Ghanaian agriculture. The fall armyworm, for example, has decimated maize fields across the country, with farmers often only detecting the infestation after significant damage has already occurred. By then, it is often too late for effective intervention.

AI is changing this calculus. Drones and satellites provide high‑resolution imagery that reveals early disease signs invisible to humans, while AI algorithms trained on subtle visual cues can flag problem areas before ground symptoms emerge. In the cocoa‑growing Ashanti Region, drone flyovers scan hundreds of trees simultaneously, detecting pod lesions or leaf discoloration faster than human scouts could ever manage.

Pezego, an AI‑powered pest management platform targeting Ghanaian maize farmers, provides real‑time pest detection, highlights current infestation thresholds, estimates economic thresholds, and offers actionable, localised pest management advice. The platform is designed to enhance farmers’ resilience to climate variability and market fluctuations.

Research on using Convolutional Neural Networks (CNNs) for pest and disease detection in Ghanaian cocoa plants has demonstrated the power of AI to identify cocoa plant diseases and pests with high accuracy. This research was strategically focused on practical applications, avoiding overly technical dissections of AI mechanisms while delivering actionable insights for farmers.

Farmerline’s Mergdata platform, which already serves over 2.2 million farmers across 48 countries, is scaling AI within its ecosystem. The platform uses AI to detect diseases, identify illegal mining activities, and provide real‑time data to close the access gap for smallholder farmers. With over 80 per cent of Ghanaian farmers being smallholders, the mission is to scale meaningful solutions, tailor support, and use real‑time data to close the access gap.

The benefits extend beyond crop health. Early detection of pests and diseases reduces the need for blanket pesticide applications, lowering costs for farmers and reducing environmental harm. For export crops such as cocoa, early disease detection can also protect international market access, as European Union regulations increasingly require proof of sustainable, pest‑free production.

Satellite Monitoring and Precision Agriculture — Farming from Space

The most ambitious AI agricultural interventions in Ghana are happening not on the ground but from space. Satellite monitoring systems, combined with AI analytics, can scan thousands of acres at once, providing insights that would be impossible to gather manually.

Japanese firm Degas Ltd has been the pioneer in this space. The company’s platform combines AI‑driven satellite monitoring with precision agriculture techniques to support smallholder farmers. Already, Degas has financed more than 86,000 smallholder farmers across 122,000 acres of farmland, helping to double farmer incomes with a 95 per cent repayment rate. At the ninth Tokyo International Conference on African Development (TICAD 9) in Yokohama, Japan, President Mahama secured a $100 million commitment from Degas over four years to scale these operations.

Degas CEO Makiura stated, “Ghana has shown that when technology meets a clear national vision, smallholder farmers can thrive. Our $100 million commitment will scale AI‑driven satellite monitoring and precision agriculture techniques so farmers can boost yields, reduce risk, and access fairly priced finance.” The funding will support the expansion of Degas’ farmer financing schemes, satellite‑enabled crop monitoring, and precision agronomy services, while deepening partnerships across input supply, logistics, and offtake to strengthen local value chains.

The satellite monitoring capability is transformative. Farmers can receive regular updates on crop health, soil moisture and predicted yields without ever leaving their farms. Lenders can use satellite data to verify crop conditions before approving loans. Insurance companies can trigger automatic payouts when satellite imagery confirms drought conditions. The entire agricultural value chain becomes more transparent, efficient and data‑driven.

President Mahama, announcing the investment, said, “With AI‑driven satellite monitoring and precision agriculture, we will strengthen value chains from inputs to markets, improve food security, and create more jobs for our youth.” The investment positions Ghana as a potential leader in AI‑powered agriculture on the continent.

AI and Cocoa — Blockchain Traceability and Climate Resilience

Cocoa is Ghana’s most important agricultural export, generating billions in foreign exchange and supporting hundreds of thousands of farming families. Yet the sector faces persistent challenges: low productivity, deforestation, child labour concerns, and increasingly stringent international regulations.

AI is being deployed across the cocoa value chain to address these challenges. In the Ashanti Region, drone flyovers equipped with AI image recognition scan hundreds of cocoa trees simultaneously, detecting pod lesions, leaf discoloration and other early signs of disease. Satellite farm monitoring systems provide regular updates on cocoa farm conditions, enabling COCOBOD to track farm health across the entire sector.

Perhaps the most significant innovation is blockchain traceability. Digital traceability platforms are driving the transformation of Ghana’s cocoa supply chain, bridging traceability gaps, improving transparency, and enabling compliance with international sustainability standards such as the EU Deforestation Regulation (EUDR). These platforms integrate AI and blockchain to provide a traceable fingerprint from producer to consumer, ensuring that every cocoa bean can be traced back to its farm of origin.

The implications for Ghanaian cocoa farmers are profound. Full GPS traceability is now a requirement for cocoa, coffee and palm oil imports into the European Union by December 2025. By deploying AI‑powered traceability systems, Ghana can maintain its position as a premium cocoa supplier while protecting farmers from market exclusion. Farmers who can prove their cocoa is sustainably produced can access premium prices and direct market linkages.

AI also supports climate resilience in cocoa farming. Predictive models trained on historical weather data, soil conditions and disease patterns can help farmers plan planting schedules, anticipate pest outbreaks and optimise fertiliser use. For a crop that is highly sensitive to climate variability, these tools are not luxuries — they are survival mechanisms.

Digital Advisory Services — Darli AI and the Democratisation of Agricultural Knowledge

The most profound constraint on smallholder farmer productivity is not access to technology — it is access to knowledge. Farmers know their land, but they often lack access to expert advice on regenerative practices, pest management and climate adaptation.

Farmerline’s Darli AI is addressing this gap. Darli AI is a platform that serves as a regenerative farming mentor for smallholder farmers globally, using AI to translate local languages through a chatbot and provide instant, actionable solutions. The platform works across 27 languages, including Twi, Swahili, Yoruba and others, ensuring that language is not a barrier to accessing expert agricultural advice.

Darli AI teaches regenerative farming practices, enhancing yields while protecting the environment. It tracks knowledge transfer to ensure farmers effectively apply key insights. It monitors and measures impact by capturing data on yield improvements and carbon sequestering. To date, about 110,000 farmers in 27 languages have benefited from Darli AI.

The innovation has received global recognition. Time Magazine named Darli AI one of the Best Inventions of 2024. Farmerline operates in 48 countries and works with 2.2 million farmers, aiming to scale AI within its Mergdata platform to increase farmers’ incomes, provide inputs and assets, and connect them to global markets.

The beauty of Darli AI, as described by its creators, is that it amplifies existing knowledge, making indigenous agricultural wisdom accessible across language barriers while preserving the cultural context that makes this knowledge so valuable. For the Ghanaian farmer who speaks only Twi and has never used a smartphone, Darli AI represents a bridge between traditional knowledge and cutting‑edge AI.

Policy and Investment — The National AI Strategy and the $100m Degas Commitment

The transformation of Ghanaian agriculture through AI is not happening in a policy vacuum. The government has made AI a national priority, with agriculture explicitly identified as one of eight target sectors for AI adoption under the National AI Strategy (2025‑2035), launched on 24 April 2026.

The strategy envisions AI tools trained on Ghanaian soil, rainfall and crop cycles, rather than imported models built for foreign climates. It commits to precision agriculture that can lift yields, cut waste and give smallholder farmers the confidence to plan. Eight priority sectors include agriculture, healthcare, transportation, energy, financial services, culture, lands and natural resources, and the environment and circular economy.

Cabinet has approved a $250 million AI computing centre to provide the processing power needed for advanced agricultural AI applications, alongside a $20 million implementation fund and a National AI Fund that will launch with GH¢5 billion from 2025 to 2030, scaling to GH¢15 billion by 2035. The government has also signed a $1 billion strategic partnership with the United Arab Emirates to develop Africa’s largest integrated innovation and AI hub in Ningo‑Prampram.

Private investment is complementing public commitment. Beyond the $100 million Degas investment, Google has committed $37 million to AI development across Africa, with its first AI Community Centre in Accra focused in part on agricultural applications. MTN Group is actively seeking partners to co‑develop large‑scale data centres in Ghana, providing the infrastructure that AI‑powered agricultural platforms require.

Financial Inclusion — AI as the Key to Unlocking Agricultural Credit

One of the most transformative applications of AI in Ghanaian agriculture is not on the farm itself but in the financial system that serves it. Smallholder farmers have historically been excluded from formal credit because banks lack reliable data on farm productivity, crop health and repayment capacity. Without collateral or credit history, farmers are deemed too risky to lend to.

AI is changing this. Satellite monitoring data can verify crop conditions, enabling lenders to assess risk remotely. Yield prediction models can estimate harvest volumes, providing confidence in repayment capacity. Digital platforms that track farmer transactions and input purchases create alternative credit histories.

The Degas model integrates farmer financing directly with AI‑driven monitoring. By providing satellite‑enabled crop monitoring and precision agronomy services alongside financing, Degas reduces its risk while helping farmers improve yields and repay loans. The 95 per cent repayment rate among Degas‑financed farmers demonstrates that smallholder agriculture is not inherently risky — it is simply under‑monitored.

KNUST students have developed an AI‑powered digital platform that creates a “digital twin” of farms, a virtual representation that provides lenders and other stakeholders with real‑time visibility into farming activities, crop types and risk levels. This platform was developed to address the real‑life problems faced by smallholder farmers and agribusinesses across Ghana. By providing verified farm data, it enables lenders to make informed decisions, unlocking credit that was previously inaccessible.

The One Million Coders Programme, which aims to equip one million Ghanaians with digital and AI skills, has direct relevance to agriculture. President Mahama has outlined that coding skills would enable the nation’s youth to develop digital solutions to local problems, whether in agriculture, healthcare, education, or governance. By building a generation of AI‑literate agricultural entrepreneurs, the programme could accelerate the adoption of AI across the sector.

Challenges and Constraints

For all the promise of AI in Ghanaian agriculture, significant barriers remain.

The first is connectivity. AI applications require reliable internet access to transmit data, receive updates and access cloud‑based models. Rural Ghana, where the majority of farmers live and work, remains under‑connected. While mobile money has achieved near‑universal penetration, high‑speed data coverage is still patchy outside urban centres. Satellite‑based solutions such as Degas’s platform can bypass terrestrial connectivity gaps, but they require compatible devices that many farmers do not yet possess.

The second is device affordability. AI‑powered agricultural tools often require smartphones, sensors or drones. The upfront cost of these devices is prohibitive for many smallholder farmers. The service model — where farmers pay per use or access tools through cooperatives — offers a potential pathway, but scaling such models requires patient capital and effective distribution.

The third is data localisation. AI models trained on foreign data often perform poorly when applied to Ghanaian conditions. The National AI Strategy explicitly calls for models trained on Ghanaian soil, rainfall and crop cycles, but building these models requires extensive local data collection. Initiatives such as FarmSense and Darli AI are actively collecting local data, but the process is slow and expensive.

The fourth is trust and adoption. Farmers who have used the same methods for generations are understandably cautious about new technologies. AI tools must demonstrate clear, immediate benefits before farmers will change their practices. The 60 per cent yield increase from FarmSense and the 30 per cent reduction in crop losses from early pest detection are compelling evidence, but scaling adoption requires sustained extension services and farmer training.

Future Outlook — Three Scenarios for AI in Ghanaian Agriculture

The trajectory of AI adoption in Ghanaian agriculture will be shaped by three variables: the pace of rural connectivity expansion, the effectiveness of farmer training programmes, and the continued flow of investment into agritech startups.

Scenario One — Gradual, Concentrated Adoption (65 per cent probability).

In this base case, AI adoption in agriculture proceeds steadily but unevenly. Large‑scale commercial farms and export‑oriented crops such as cocoa adopt AI tools most rapidly, driven by regulatory requirements for traceability and sustainability certification. Smallholder farmers adopt AI more slowly, with adoption concentrated in regions with better connectivity and active extension services. FarmSense and similar soil intelligence platforms scale to reach 500,000‑1,000,000 farmers by 2030. Autonomous robotics remains niche, limited to commercial farms. Satellite monitoring becomes standard for cocoa and other export crops but less common for food crops. AI contributes significantly to productivity gains but does not fundamentally reshape the structure of smallholder agriculture.

Scenario Two — Accelerated Breakthrough (25 per cent probability).

The $250 million AI computing centre becomes operational by 2028, providing the processing power needed for advanced agricultural AI models. The National AI Strategy’s agricultural pillar is implemented effectively, with extension services integrating AI tools into standard farmer training. Connectivity gaps are addressed through a combination of mobile network expansion and satellite‑based solutions. The service model for agricultural robotics and AI tools scales successfully, making them accessible to smallholder farmers on a pay‑per‑use basis. AI‑powered credit scoring unlocks significant new financing for smallholder agriculture. By 2035, AI tools are used by the majority of Ghanaian farmers, contributing to a 30‑50 per cent increase in agricultural productivity and a significant reduction in post‑harvest losses.

Scenario Three — Stagnation and Fragmentation (10 per cent probability).

Infrastructure investments are delayed. The computing centre faces technical and financial challenges, and its operational timeline slips. Connectivity gaps remain unaddressed. The One Million Coders Programme produces graduates who lack the agricultural domain expertise needed to build effective tools. Farmer training programmes are underfunded. AI adoption stalls, with tools remaining concentrated in a few pilot regions. Ghana falls behind regional peers such as Kenya and Rwanda in agricultural AI adoption. The productivity gap between Ghanaian agriculture and global benchmarks widens.

The most likely path is Scenario One: gradual, concentrated adoption, with AI transforming export crops and commercial farms but reaching smallholder food crop farmers more slowly. The GH¢500 billion GDP target for AI by 2035 is unlikely to be achieved without accelerated progress on connectivity, training and farmer adoption.

Conclusion

The hoe and cutlass have served Ghanaian farmers for generations. They will not disappear overnight. But they are being joined — and in some cases replaced — by AI‑powered tools that are already delivering measurable results. FarmSense is boosting yields by up to 60 per cent. Degas satellite monitoring is helping double farmer incomes across 122,000 acres. Darli AI is providing regenerative farming advice in 27 languages to over 110,000 farmers. Autonomous robots are planting seeds and applying fertiliser without human intervention.

The investments are significant. $100 million from Degas. $37 million from Google. $250 million for a national AI computing centre. A National AI Strategy that places agriculture at the centre of Ghana’s AI ambitions. Private sector innovation from startups such as 3Farmate, Farmerline, Sesi Technologies and Aya Data. The building blocks of an AI‑powered agricultural transformation are being put in place.

Yet the distance between these impressive pilots and nationwide transformation remains vast. Connectivity gaps keep rural farmers offline. Device costs keep AI tools out of reach. Data localisation requires patient investment in local model training. Trust must be earned through demonstrable results delivered at scale.

The question is not whether AI will transform agriculture in Ghana. It is already doing so. The question is how fast that transformation will reach the millions of smallholder farmers who constitute the majority of Ghana’s agricultural workforce. The technology is ready. The policy framework is in place. The capital is being committed. The missing ingredient is the sustained, coordinated effort to bridge the last mile — to bring connectivity, training and affordable AI tools to every farmer who needs them.

Agriculture is Ghana’s most important industry, its largest employer and its most direct pathway to inclusive growth. AI is the most powerful tool available to unlock that potential. The hoe and cutlass are not obsolete. But they are no longer enough. The algorithm is already in the field. The question is whether Ghana’s farmers will be equipped to use it.

Frequently Asked Questions (FAQ)

Q1: How is AI being used in Ghanaian agriculture today?

AI is being deployed across multiple applications including soil intelligence (FarmSense), autonomous robotics (3Farmate), pest and disease detection (Pezego, drone‑based monitoring), satellite‑powered precision agriculture (Degas), digital advisory services (Darli AI), and blockchain traceability for cocoa exports. These tools help farmers boost yields, reduce input costs, detect pests early and access financing.

Q2: What is FarmSense and how much can it increase yields?

FarmSense is an AI‑powered soil intelligence platform developed by Ghanaian startup Sesi Technologies in partnership with KNUST’s DIPPER Lab. It combines hardware, software and machine learning to deliver real‑time soil analysis, crop recommendations and nutrient planning. FarmSense has been proven to boost yields by up to 60 per cent while optimising fertiliser use and reducing environmental impact.

Q3: What is the Degas investment in Ghanaian agriculture?

Japanese firm Degas Ltd has committed $100 million over four years to scale AI‑driven satellite monitoring and precision agriculture techniques in Ghana. The company has already financed more than 86,000 smallholder farmers across 122,000 acres of farmland, helping to double farmer incomes with a 95 per cent repayment rate. President Mahama announced the investment at TICAD 9 in Yokohama, Japan, in August 2025.

Q4: What is 3Farmate and how does its autonomous robot work?

3Farmate is a Ghanaian startup founded by university students Clinton Anani and Elijah Ocupualor. Its robot, FAMA, is an AI‑powered autonomous machine capable of planting seeds, applying fertiliser, weeding and spraying crops without human intervention. Unlike many agricultural robots that rely on GPS, FAMA navigates using a vision‑based AI system that can see its environment and navigate between rows of crops.

Q5: How does Darli AI help Ghanaian farmers?

Darli AI, developed by Farmerline, is a platform that serves as a regenerative farming mentor for smallholder farmers. It uses AI to translate local languages through a chatbot, providing instant, actionable advice on regenerative farming practices. To date, about 110,000 farmers in 27 languages have benefited from Darli AI. Time Magazine named Darli AI one of the Best Inventions of 2024.

Q6: What is the National AI Strategy and how does it address agriculture?

Launched on 24 April 2026, Ghana’s National AI Strategy (2025‑2035) projects that AI will contribute GH¢500 billion (approximately $45 billion) to GDP by 2035. Agriculture is one of eight priority sectors for AI adoption, with the goal of developing AI tools trained on Ghanaian soil, rainfall and crop cycles to lift yields, cut waste and give smallholder farmers the confidence to plan.

Q7: How is AI being used in Ghana’s cocoa sector?

AI is being deployed in Ghana’s cocoa sector for pest and disease detection via drone flyovers and satellite monitoring, and for blockchain traceability to comply with international sustainability standards such as the EU Deforestation Regulation (EUDR). Digital traceability platforms ensure that every cocoa bean can be traced back to its farm of origin, protecting market access and enabling premium pricing.

Q8: What is the role of satellite monitoring in Ghanaian agriculture?

Satellite monitoring systems, such as those deployed by Degas, use AI analytics to scan thousands of acres at once, providing insights on crop health, soil moisture and predicted yields. Farmers can receive regular updates without leaving their farms. Lenders and insurers use satellite data for risk assessment and automatic payouts. The technology enables precision agriculture at a scale that would be impossible to achieve manually.

Q9: How does AI help smallholder farmers access credit?

AI‑powered platforms create “digital twins” of farms, providing lenders with real‑time visibility into farming activities, crop types and risk levels. Satellite monitoring data can verify crop conditions, enabling remote risk assessment. Yield prediction models estimate harvest volumes, providing confidence in repayment capacity. The Degas model, which integrates farmer financing directly with AI‑driven monitoring, has achieved a 95 per cent repayment rate.

Q10: What are the main barriers to AI adoption in Ghanaian agriculture?

The primary barriers are connectivity gaps in rural areas, the affordability of smartphones and sensors for smallholder farmers, the need for AI models trained on local data (rather than foreign data), and farmer trust in new technologies. Addressing these barriers requires continued investment in rural connectivity, service models that lower upfront costs, local data collection, and sustained extension services.

Q11: What is the One Million Coders Programme and how does it relate to agriculture?

The One Million Coders Programme aims to equip one million Ghanaians with digital and AI skills, including coding, data analysis, cybersecurity and AI. President Mahama has stated that coding skills will enable youth to develop digital solutions to local problems, whether in agriculture, healthcare, education, or governance. By building a generation of AI‑literate agricultural entrepreneurs, the programme could accelerate AI adoption across the sector.

Q12: What is the future outlook for AI in Ghanaian agriculture?

The most likely scenario is gradual, concentrated adoption, with AI transforming export crops such as cocoa and large‑scale commercial farms first, while reaching smallholder food crop farmers more slowly. Soil intelligence platforms such as FarmSense are expected to scale to reach 500,000‑1,000,000 farmers by 2030. Satellite monitoring is likely to become standard for export crops. A genuine breakthrough — where AI tools are used by the majority of Ghanaian farmers — would require accelerated progress on rural connectivity, farmer training and the development of affordable, pay‑per‑use AI services.

Esther Aku-Sika

Esther Aku-Sika is a content writer and social media strategist who helps brands and startups grow through intentional storytelling and practical marketing strategies. With a keen eye for trends and audience behavior, she shares business insights, content strategies, and real-life lessons to help entrepreneurs build visibility and turn ideas into income. Through her writing, she simplifies complex concepts and equips readers with actionable steps to grow in today’s digital space.