AI and Agriculture – What are the issues?

Artificial intelligence has the potential to increase productivity, reduce costs, minimize environmental impact, and improve sustainability in the agricultural sector. However, it is crucial to address the downsides and challenges associated with AI in agriculture to ensure equitable access, promote sustainable practices, and protect the interests of farmers.


There has been much discussion recently on the economic and social implications of AI (Artificial Intelligence). AI is likely to impact many industries and farming is no exception. For example, in 2022 Google announced a $10 billion investment in agriculture and AI-powered machine learning for crop research. Google plans to use technology to improve yield and cut costs for farmers around the world. Monsanto has also been working on a project called CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats).  CRISPR uses AI and RNA sequencing technology to create specific strains of crops with increased yields.

What is AI or Artificial Intelligence?
Farming could be revolutionized by AI, but there are downsides.

AI is typically defined as an autonomous and self-learning agency with the ability to perform cognitive functions. AI processes large quantities of data, interpreting patterns, and then translates these interpretations into actions that resemble those of a human being.  This is in contrast to the natural intelligence displayed by humans, such as learning from experience and reasoning.

What are the benefits of using AI in agriculture?

AI has the potential to revolutionize and advance farming in many ways.

Precision farming

Precision agriculture uses data from various sources satellite imagery, drones and sensors which can be analyzed by AI. This data can be used to monitor and optimize crop health, soil conditions, water usage, and pest management. Farmers can make data-driven decisions to apply fertilizers, pesticides, and water precisely where and when they are needed, reducing waste and improving crop yields.

Crop monitoring and disease detection

Image recognition and machine learning powered by AI can analyse crop images to detect diseases, nutrient deficiencies, and other issues. Thus creating an early warning system to allow farmers to take prompt action to prevent crop losses.

Robotics and Autonomous farming equipment

Combining AI and robotics will help develop autonomous farming equipment, such as tractors and harvesters. These machines can operate with minimal human intervention, improving efficiency and reducing labour costs. They can also work continuously, enabling 24/7 operations. Agricultural robots can identify and respond to pests and diseases in crops, improve yield, and automate repetitive and manually intensive tasks on farms.

Agricultural drones

Drones equipped with AI technology can survey large areas of farmland quickly and efficiently. They can collect data on soil conditions, plant health, and irrigation needs, allowing farmers to make targeted interventions and optimize resource usage.

Predictive analytics and forecasting

AI algorithms can analyse historical data, weather patterns, and other factors to generate predictions and forecasts. Farmers can use this information to plan planting and harvesting schedules, optimize resource allocation, and manage supply chains more effectively.

Livestock MONITORING and management

AI-powered systems can monitor and analyze data from sensors placed on livestock. This data can provide insights into animal health, behaviour, and nutrition, allowing farmers to detect diseases, optimize feeding strategies, and improve overall animal welfare.

Supply chain efficiency

AI can optimize the agricultural supply chain by analyzing market data, transportation routes, and demand patterns. It can help farmers and agribusinesses make informed decisions about storage, transportation, pricing, and distribution, reducing waste and ensuring timely delivery.

Advice and recommendations

Chatbots are being used to help farmers. Chatbots help answer a variety of questions and provide advice and recommendations on specific farm problems. 

What are the downsides and risks of AI?

AI could bring significant benefits to farmers, however, there are also potential downsides and challenges:

Data privacy and security

AI systems rely on collecting and analyzing large amounts of data. Farmers may have concerns about the privacy and security of their data, especially if it is stored in the cloud or shared with third-party providers. Ensuring data security will be critical to gaining acceptance for the technology. There is currently no specific legislation covering the ownership and use of AI-generated farm data. This situation hinders gaining trust and acceptance of many within the farming community, 


As farmers rely on AI-driven systems, there is a risk of becoming overly dependent on technology. Malfunctions, system failures, or disruptions in connectivity can lead to significant disruptions in farm operations. It’s important to have contingency plans and backup systems in place to mitigate such risks.

Lack of human expertise

AI can automate certain tasks and provide valuable insights, but cannot replace the knowledge and experience of farmers. Overreliance on AI may result in a decrease in practical skills and the ability to make independent decisions based on field observations. Balancing the use of AI with human expertise will be critical in exploiting the technology.


AI raises ethical concerns related to data privacy, algorithmic biases, and the potential for displacing human workers. There is a need to ensure that AI systems are developed and deployed in a way that respects human rights, and promotes fairness, and the well-being of farmers and farmworkers. The American Farm Bureau Federation estimate that the number of people employed in the U.S. agriculture industry will drop by half by the year 2028. 

THE learning curve

Introducing AI technology requires farmers to adapt to new practices and acquire new skills. This is a challenge, particularly for older or less tech-savvy farmers who may require training and support to effectively utilise AI tools.

Consolidation of power

The adoption of AI in agriculture may lead to the increased concentration of power for large agribusinesses or technology companies. This could negatively affect smaller farmers, limiting their choices, bargaining power, and access to AI-driven solutions.

Misuse by criminals and terrorists

AI may be used by criminals, terrorists and rogue states to disrupt the food system. For example, thieves are already targeting farm equipment using drones.

The Environmental Impact

There are also environmental consequences. AI needs a lot of energy to process data. Data storage and processing centres providing digital services like entertainment and cloud computing are already responsible for two percent of global greenhouse gas emissions. This is a number comparable to the overall percentage of pollution contributed by the aviation industry. 

What are the long-term implications of AI for agriculture?

AI has the potential to increase productivity, reduce costs, and improve sustainability in the agricultural sector. Harvard University says that AI could spur more efficient methods of farming which could help in the fight against climate change. However, legislation is needed to help farmers and others overcome their mistrust of AI. The deployment of AI in agriculture must be done responsibly and ethically to address any potential concerns and ensure equitable access for all farmers. 

If you would like to know more about AI and its potential impact on your business please contact us to discuss your needs.

Leave a Reply

Your email address will not be published. Required fields are marked *