Practical Applications of AI In Agriculture

Kalyani Tangadpally
4 min readJul 22, 2022


Agriculture involves a series of processes and stages, most of which are manual. By complementing adopted technologies, AI can make the most complex and routine tasks easier. It can collect and process big data on a digital platform, propose the best course of action, and even initiate that action when combined with other technology.

Why adopting AI is such a challenge for farmers
Farmers tend to perceive AI as something that applies only to the digital world. They may not see how it can help them to work the physical land. This is not because they are conservative or distrustful of the unknown. Their resistance stems from a lack of understanding of the practical application of AI tools.

New technologies often seem confusing and unreasonably expensive because AgriTech providers don’t clearly explain why their solutions are useful and exactly how they should be implemented. This is what happens with artificial intelligence in agriculture. Although AI can be useful, technology providers still have a lot of work to do to help farmers implement it the right way.

Analysis of market demand.
AI can simplify crop selection and help farmers identify which products will be most profitable.

Risk management
Farmers can use forecasting and predictive analytics to reduce errors in business processes and minimize the risk of crop failure.

Breeding seeds
By collecting data on plant growth, AI can help produce crops that are less prone to disease and better adapted to climatic conditions.

Soil Health Monitoring
AI systems can perform chemical analyzes of the soil and provide accurate estimates of missing nutrients.

Crop protection
AI can monitor plant health to detect and even predict disease, identify and remove weeds, and recommend effective pest treatment.

Forage crops
AI is useful for identifying optimal irrigation patterns and nutrient application times and predicting the optimal mix of agronomic products.

With the help of AI, it is possible to automate the harvest and even predict the best time for it.

The digital farmer
The AI ​​revolution is transforming farming and agriculture, offering multiple pathways to bountiful harvests in every corner of the world. With such a transformation, digital farms require digital farmers. Amid these dramatic technological changes, farmers need to manage their farms in new ways. Based on traditional agricultural proverbs, viable strategies can be found:

“If you’re going to go where the corn grows, take a cutting tool with you.” Farm managers must use the right tools at their disposal. They need to quickly dive into the available technologies and be able to sensibly assess their benefits to the farm. Extensive technological knowledge is not necessary, but it is important to understand the basic principles and their operational implications. Through AI, farmer managers can have a better and deeper understanding of their farms. This increased cognitive ability gives new meaning to the saying “fields have eyes and forests have ears.”

“When you plan for a year, plant corn. When planning for a decade, plant trees. By planning for life, training and educating people.” The changing technological environment requires changes in the type of talent needed in the farm organization, as well as refinements in the organizational structure. Aside from typical agriculture roles, there is a need to hire employees with technological skills. The entire organization must be trained and educated to keep up with the AI ​​economy.

Read: Artificial intelligence in banking sector

“All the fruit is not found in one field.” There is value in stepping outside the comfort zone of the farm and exploring new opportunities for collaboration. Farm managers must partner with technology companies for unique, innovative and cutting-edge technologies that not only increase productivity but also help them gain a clear competitive advantage. Strategic partnerships with companies with unrivaled technologies can give farm managers an advantage.

“If the collective farm is rich, the farmer is happy.” Cost advantages and profit gains can be realized from economies of scale. Farm managers will benefit from finding strength in numbers. AI technology tools can be expensive and unsustainable for some farms, collaboration with other farmers, cooperatives, suppliers, government, universities and even the local community can help reduce investment costs.

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AI impact on manufacturing

“Work improves the harvest better than the field itself.” In farming, as in any other business, diligence and careful planning contribute to success. Farm managers must plan and prioritize their digital agenda. Optimizing farming operations and yield requires careful evaluation and strategic planning. It requires a thorough review of what needs to be resolved first, as well as a clear plan for implementation.



Kalyani Tangadpally

SEO Executive and a Content Writer interested to write on Artificial Intelligence, Mobile App development, Machine Learning, Deep Learning, HRM & tech Blogs