AI technology is transforming the agricultural industry, changing how the outside world views farming and creating a data-driven system that ensures precision and maximises yields.

Imagine a world where technology tells you remotely how many nutrients are lacking and how plants are showing signs of stress and so on. It’s a beautiful experience, not science fiction like many thought. It’s a reality being practised by some big farms around the globe.

Ways in which AI is transforming agriculture

• AI makes caring for every plant and animal less laborious

For centuries, farmers have relied on just walking around the farm field to take records of animal and plant performance. Oftentimes, it is extremely challenging to manually care for every single plant and animal, especially for commercial farmers. Data and images of farm activities are seamlessly fed into AI systems via drones, satellites, and ground sensors. Making it much easier for farmers to remotely spot problems that the human eye could struggle with. For example, early disease detection, nutrient shortages and water stress control. In fact, it’s like having a health app that swiftly informs you before trouble spreads. 

• AI helps farmers to know when and how much to feed and water plants and animals

As important as water, feed, supplements, and fertilizers are, excessive application can cause other problems. AI-powered soil sensors, weather data, and smart irrigation and feeding systems can help farmers figure out how much each part of the field needs (either plant or animal) and when they need it. Typically, this helps farmers to save money by controlling waste of resources. 

• AI helps farmers to solve the weather and planting season puzzle

Accurate weather prediction has been a long-standing issue for farmers. AI can turn farmers’ “gut feeling” into accurate predictions on when to plant, what kind of crop to plant, reveal dry and rainy seasons and lot more. Over the years, making predictions has been a struggling art for farmers, but AI makes it seamless as it digests years of weather records, market trends, and soil data to give farmers a clearer recommendation. Of course, this technology is not at its perfect state yet, but it’s a huge step-up in agriculture.

• AI takes away the back-breaking tasks from farmers’ shoulders

For decades, farmers have been relying on human labour for tasks like weeding, planting and harvesting. Typically, these tasks are super stressful, back-breaking, and even expensive. However, well-designed technological farm tools like robotic weeders, autonomous tractors, smart harvesters, and so on that are guided by artificial intelligence (AI) fill the gap. They work longer hours without getting tired. Large farms that are short on labour can leverage it for their seasonal operations.

Also Read: Why Southeast Asian agritech must build for acquisitions, not IPOs

Core challenges to look out for

The promise of this technology is very real and enticing: better yields, much less waste, making smarter decisions and a lot more, but the everyday realities of farmers make it uncertain and a lot more challenging for many farmers to align with it. Here are major relatable hurdles to look out for;

• High initial investment cost and uncertain ROI

According to Mckinsey’s Global Farmers Insight in 2024, one of the major barriers to agricultural technology is high cost. This research revealed that European and North American countries are leading in global agricultural technology adoption. Meanwhile, about 52% of North American and 48% of European Farmers cited “huge costs” as the biggest challenge of adopting agtech; and about 40% of North Americans also reported that “unclear ROI” stands as a huge barrier to adoption.

Compared to large agribusiness farmers operating in millions of hectares, small and mid-size farms feel this the most. It’s very difficult for small or mid-sized farms to spend thousands of dollars on drones, sensors, software subscriptions, and a lot more with uncertain ROI. In fact, most of these farmers need clearer proof that their investments would pay off before investing in any seasonal budget. 

• Displacement of human labourers

In rural and regional communities where farms have adopted AI automation, the displacement of human labour will be high because the machine can run human operations for hours without getting tired, and as such, there won’t be a need for extra labour to attract extra cost. However, there is a growing need to have skilled personnel to operate those machines excellently.

• Network, power and connectivity barrier in rural areas

Here is another crucial barrier to look out for. From all indications, almost every AI-powered tool needs a stable network supply to enhance seamless data communication. And all devices need electricity to operate efficiently.

This is a roadblock for rural and regional farmers where the network is completely unreliable. Without a stable network, soil sensors can’t communicate to the cloud, apps wouldn’t be able to pull weather models, and even cameras won’t be able to spot pests in real time.

• Operational knowledge complexity

Farmers who are not familiar with sophisticated devices would find it daunting to operate AI tools. The language barrier ( to read through the manual), the huge numbers of low literacy within those regions and the limited number of training they might receive make it very challenging to adopt.

• Data privacy and trust struggle

Here is another barrier you can’t ignore, as the success of AI tools depends on their ability to learn from large numbers of datasets accumulated from the farm. But the big worry is always where this data is stored, how accessible the data is to farmers and a lot more. Meanwhile, there are farmers who are intimately accustomed to their farms such that they feel it’s unsafe to share sensitive data with AI. Imagine a device telling you when to irrigate, feed or apply fertiliser without explaining why; this makes some farmers feel like they are handing control to strangers.

Also Read: Agritech’s next business model may not charge the farmer

AI advancement in technology and how it’s helping farmers today

According to futurist Jim Carroll, AI advancement in agriculture offers many promising pathways in both crop and animal production. It’s already delivering exciting benefits like boosting yields, reducing waste, and improving animal welfare. Moreover, fascinating agricultural technology companies are tirelessly working to improve farming across the globe. Here are a few;

• Inventions towards targeted weed control/precision spraying with strong global recognition are John Deere See & Spray and Carbon Robotics LaserWeeder: They are advanced computer-vision and machine learning precision agricultural AI systems that can swiftly identify the target(weed) in real time and spray only them, not the entire field
• Invention towards crop monitoring, disease and pest detection: Taranis and Plantix are high-tech inventions that are AI-powered for early detection of pests and diseases, nutrient deficiencies and more.
• Invention towards advisory chatbots and smallholder tools: Farmer.Chat and Kisan e-Mitra are AI chatbots that help farmers access information on schemes, weather, pest and disease management, and more. They are often used in Africa.

In conclusion, AI is already being used on real farms, and it’s transforming farm activities from constant worries to something smart. While its primary goal is to help farmers grow more food with less waste, fewer chemicals, and almost no guesswork, it doesn’t mean farming suddenly becomes easy.

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