AI in Agriculture: 3 Ways AI Is Boosting Farming Efficiency and Reducing Costs

AI is transforming the field—quite literally. 

Predicting the perfect time to plant seeds, knowing precisely when to water crops, harvesting only the ripest crops with AI robots, spotting potential diseases before they take hold……While this might seem like something straight out of a sci-fi movie, it’s already the reality for many farmers and agribusinesses today.

The use of artificial intelligence (AI) in agriculture is booming. By 2032, the market for AI in agriculture is projected to reach a staggering US$5.27 billion as farmers globally embrace technology to boost their productivity and sustainability. These smart agricultural technology solutions are addressing major global challenges, such as climate change, food security and the conservation of resources. They prove that technology really can nurture nature. 

As we dive deeper into this agricultural revolution, we see how AI is not only changing farming methods but also making them more efficient and earth-friendly.

1. AI-powered soil analysis: A game changer for farmers

Image from Freepik

Soil is the foundation of agriculture. It holds nutrients and provides a crucial support system for plants. Yet, farmers often grapple with issues like nutrient depletion and soil contamination, which can jeopardize both crop health and their livelihoods

Traditionally, checking soil health has been a tedious affair involving sieving, sedimentation and chemical analysis. These methods are slow, sometimes inaccurate, and more expensive due to the need for specialized expertise.

In the battle for better soil, AI can become a powerful ally. Innovative platforms like Microsoft’s FarmBeats—now a part of Azure Data Manager for Agriculture—and the Brazilian agrotech startup InCeres are leveraging AI to transform soil analysis. These technologies allow farmers to easily capture field images with smartphones and gather soil data using smart sensors. AI then processes this information to precisely identify and remedy soil issues, significantly boosting both crop quality and yield.

InCeres, for example, uses AI to predict soil quality by analyzing data like weather conditions and satellite imagery. This AI-driven method is also remarkably cost-effective. Whereas traditional soil testing could cost up to BRL200 (about US$36.21) per hectare, InCeres slashes these costs by 80%, to just BRL40 (around US$7.24) per hectare. This dramatic cost reduction can make sustainable farming practices more accessible to farmers everywhere.

Image from InCeres’s website

2. Smarter pest and disease control

Image from Freepik

According to the Food and Agriculture Organization of the United Nations, farmers lose between 20% to 40% of their crops to pests—including insects, birds and rodents—annually. That’s a big chunk of the world’s food supply, not to mention a heavy hit to the economy—plant diseases alone cost us about US$220 billion and invasive insects another US$70 billion annually. And pests don’t just eat away at crops; they can also damage farm equipment and infrastructure.

For a long time, the go-to solution was to treat fields with pesticides. While it works, it isn’t great for the planet or for our health. Now, AI is paving the way for a smarter and safer approach to handling pests. For example, BASF’s Xarvio™ uses advanced algorithms to detect and manage field issues before they spiral out of control. Besides identifying pests and diseases, it also monitors weather conditions to predict future outbreaks, helping farmers make quick, informed decisions.

Xarvio™ is also part of a bigger move towards digital farming, automating how farmers manage data and making those tedious tasks like identifying weeds easier. One of its intriguing features is its SMART SPRAYING technology, developed with Bosch, which uses smart camera sensors to differentiate between crops and weeds. It sprays just the right amount of herbicide where needed, cutting down on waste and costs. Moreover, farmers get access to digital tools offering customized advice and detailed field maps, streamlining farm management and boosting efficiency.

3. Standardizing harvest quality

Image from Freepik

Ever struggled to pick the perfect apple at the grocery store? We all have our eyes peeled for that spotless, tasty fruit. But think about the suppliers and farmers who need to ensure every piece of fruit meets those high standards consistently. It’s a huge challenge that directly affects their earnings. After all, consumers expect the best produce, with no blemishes or signs of overripeness.

Traditionally, the quality control process has relied heavily on the human eye. Workers manually inspect each fruit and vegetable, a method that’s naturally prone to mistakes. But what if technology could help speed up this process?

India-based IntelloLabs, founded in 2016, is tackling this issue on a large scale by using AI to standardize the quality of agricultural produce. Using AI tools like computer vision and deep learning, IntelloLabs analyzes photos taken with simple smartphones to assess and grade the quality of various crops. This method ensures that only the best products reach consumers, reducing food wastage and helping farmers get fair prices for their goods.

The future of farming with AI

The integration of AI into agriculture is proving to be a boon for farmers and consumers alike. AI is bringing precision, efficiency, and sustainability to the table, helping tackle some of the biggest challenges the agricultural sector faces today.

However, it’s important to recognize that the road to AI integration isn’t without its bumps, especially for small-scale farmers. Many find it tough to tap into these technologies. They’re up against things like not enough data, poor infrastructure, a general mistrust of new tech and a lack of supportive regulations.

To really open up the benefits of AI to everyone in agriculture, it is important to make AI more more user-friendly and affordable. Developing solutions such as data-sharing platforms, low-cost devices, human-centered design and responsible governance are key to ensuring that AI transforms agriculture in a way that uplifts and empowers farmers of all sizes.

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Header Image from Freepik


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