AI disrupts agriculture but demographic crisis looms over farming

The value of artificial intelligence in agriculture is projected to grow from $1.7 billion in 2023 to $4.7 billion by 2028, according to the World Economic Forum.

From soil health monitoring and weed detection, to weather forecasting and seed selection, AI is enabling farmers to track improvements and detect issues with unprecedented accuracy.

One such example is hydroponic cultivators Terragrow which runs management software that helps farmers with administrative tasks.

Twenty-two-year-old farmer Charles Terrey spotted an opportunity and launched the company - with AI at the core of his project.

He is exhibiting the software at the Paris Agriculture Show, running from February 22 to March 2. The show is an annual ten-day-long extravaganza of cows, sheep, pigs, tractors, and French produce - from wheat and mushrooms to bananas and wine.

"If the farmer asks the software to fill in a paper, so an administrative task, it will do it and the farmers will gain a huge amount of time each week," Terrey told CGTN.

"Also the farmer can ask questions about his data, so this way he will have some advice seven days a week and 24 hours a day."

Agriculture is well suited for disruption by artificial intelligence. It relies on physical laborers, and there are complex supply-chain logistics.

Implementing regenerative and precision agriculture may boost farmers' incomes; some studies suggest profits could grow as much as 120 per cent.

Job losses and fewer farmers

But there are also possible downsides.

Self-driving tractors, automated milking parlours, and seeding machines that can work day and night are all a risk to jobs in the farming sector.

As well as AI impacting the farming labor force, agriculture faces another jobs issue: a demographic crisis. 

Figures show that just 12 percent of European farms are run by people under the age of 40. One in two French farmers will have reached retirement age by 2030. 

Managing agribusinesses

By 2050, the world needs to produce 60 percent more produce to feed what would be a global population of more than 9 billion people, according to the Food and Agriculture Organization.

Machine-learning models can help maintain agricultural productivity, for example, in managing pest invasions and assessing the best time to harvest.

X-Farm is a tech company that aims to digitalize the agribusiness sector.

Thomas Collet, an agronomist promoting X-Farm at the show, told CGTN: "With the satellite solutions we could provide, we can detect problems in the crop, we can also provide some irrigation maps and advice, and we can also develop yield prediction," said Collet.

Integrating AI in agriculture is reshaping current practices for one of the most important jobs anywhere in the world - rearing livestock and growing crops to feed a nation.