AI Transforms Farming : As the global population heads toward 10 billion by 2050, the pressure on agriculture is mounting. This article explores how artificial intelligence (AI) is transforming farming, improving food security, and enhancing sustainability—while aiming to support farmers of every background, especially in developing regions like Central Asia.
Feeding the Future: How AI is Reshaping Agriculture and Food Security in Asia and the World
As the world’s population hurtles toward an estimated 10 billion by 2050, the problems of agriculture are indeed everyone’s problems, many experts believe, and the solutions will have to be both globally expansive and locally specific. And will our food systems be up to the coming demand? The solution already exists, and it may be burgeoning right in front of you: artificial intelligence (AI). Experts and leaders met at the Asian Development Bank’s (ADB) annual meeting in Milan this May to chart how AI can actually “power economies”. AI is proving to be an essential ally in the battle for food security with its ability to speed up germination of crops, enhance logistics and ensure agriculture is more inclusive and sustainable. The stories and insights that came out of the event created a powerful picture of what is possible – and what still needs to shift.
The Pressure to Feed a Growing World
The world’s food supply comes under increasing pressure. Feeding 10 billion people by 2050 will require not just all the food mankind has produced over the past 8,000 years, but the same amount again, according to estimates. AI is increasingly proving to be part of the solution to these issues, ADB officials said. It’s not about maximizing yields, it’s about building resilient, sustainable food systems that work for all.
“Agriculture is going through a major transformation,” said Jeff Rowe, CEO of Syngenta Group. Climate change-induced crop failure, once the work of years, will be diagnosed and addressed in months, by the intersecting vectors of machine learning and big data.
A Tale of AI and Brazil’s Farms
Rowe offered a vivid example from Brazil of what that looked like in practice for AI. A year and a half ago he visited a soybean farmer who had been devastated by drought. Ponds were dry, and a year’s worth of investment had vanished just before the harvest. But rather than throwing in the towel, Syngenta dispatched AI models to analyze tens of thousands of images to identify the kind of crop damage. Utilizing this approach, the company proposed specific solutions that were developed from established technologies.
“This would have taken years,” Rowe said. “Now it has taken a few months. And it altered even more lives on the ground.”
The capability to adjust quickly to the impacts of climate change is increasingly important as weather becomes more erratic. AI isn’t just about combating crop loss – it’s changing the way we develop crops, too.
Faster, Smarter Crop Breeding
New varieties by traditional breeding methods took about five years for commercialization. AI has accelerated that time frame dramatically. Drought-resistant strains, improved packaging and varieties that are pest resistant can now be introduced in much shorter cycles. In a time when extreme weather can devastate entire harvests, that speed is a game changer.
“Farmers really need to know what to expect from their various capital expenditures, and in a climate where everything is uncertain, they just have to figure out where the risk lies.”
Optimal Global Food Supply Chain
AI is transforming supply chains beyond the farm. It doesn’t matter whether it’s about shipping fertilizer to a remote village or moving fresh produce to urban supermarkets before it spoils, logistics matters. Tools that use artificial intelligence are starting to help companies cut down on the time it takes to develop products and their supply chains around the world.
Rowe also stressed the increasingly important role of AI in soil analysis – a sometimes sidelined but highly relevant aspect in agricultural efficiency. An AI model can help recommend precise, specific treatments at scale by analyzing thousands of soil samples at a time, improving soil health and increasing yields in a sustainable way.
The Outlier in Central Asia: AI for Conservation
In Milan, the conversation went beyond food production. ADB’s Director for Agriculture, Food, Nature, and Rural Development Ms. Yasmin Siddiqi cited an exciting model from Central Asia, in which AI was used to combine training and environment work.
In the area, windmills were being constructed in areas frequented by migrating birds and were threatening the endangered species, like bustards. But AI came in and saved the day. With advanced identification models that use AI, systems can now recognize incoming birds from kilometers away and shut the turbines down to prevent collisions.
“This process serves as a strong example of how technology can both serve nature and development,” Siddiqi said.
It’s a convincing illustration that AI is not just about efficiency, but can also help to preserve biodiversity, underscoring the role of agriculture in wider ecological sustainability.
Agriculture’s Gender Divide: Women Farmers Are Left Behind, Despite Successes
Yasmin Siddiqi also brought up a critical question that AI on its own couldn’t answer, though it could provide a framework to address: inclusivity.
“Women are also farmers in many of our countries,” she reminded the audience. But across the bulk of Central Asia – and indeed most other developing countries – women are being systematically excluded from the technological revolution that is changing the face of agriculture. Scarce mobile phone access, digital platforms or even literacy has left many female farmers unable to take advantage of tools like AI.
She drove the point home with a moving story about a Tajik farmer, Malika. Malika’s routine starts before sunrise – feeding her kids, working the fields, cooking, returning to the fields even under the scorching sun. Her situation is not uncommon, reflecting an invisible work force that supports agriculture around the world.
“Malika is my farmer,” said Siddiqi. “These are the kind of farmers that I am trying to work and support through the ADB.”
Architecting a Tech-Minded, Inclusive Food System
Siddiqi stressed that food systems are not sustainable unless they work for all people including women and marginalized groups. This may involve intentionally designing AI tools to accept a range of access and literacy. It also means having training programs and support present at the local level – for the actual situation on the ground.
“Not all women enjoy the same access to resources as men do,” Siddiqi said. “That’s why we need to have an inclusive space.”
Without this focus on equity AI could exacerbate already existing disparities between well-resourced farmers and those most at risk.
Conclusion: AI Transforms Farming
What the annual ADB meeting made clear is this – AI is revolutionizing agriculture in significant ways. Whether it’s combating climate impacts or shortening crop development and better managing logistics, technology is a driver of change. But it will achieve its true potential only if put to use in a manner that is equitable, ethical and both human- and planet-focused.
The challenge is vast – but so too is the opportunity. By drawing lessons from successes like the AI-brain rain response in Brazil, or the bird-protecting turbines of Central Asia, we can envisage a future where agriculture is not only more efficient, but more humane and sustainable.
It’s not just what we grow where the future of food is concerned. It’s a question, not just of what we eat, but of how we grow it, who profits and what kind of world we want to feed.
FAQs
- How is AI used in modern agriculture?
AI is used for crop monitoring, climate prediction, logistics optimization, soil analysis, and faster crop breeding processes. - Can AI help in environmental conservation?
Yes. For example, AI-powered systems can identify bird species and shut down wind turbines to prevent endangered species like bustards from colliding with blades. - What is the gender gap in agricultural AI access?
Many women farmers in developing nations lack access to mobile phones, training, or literacy required to use AI tools, limiting their participation in tech-driven agriculture. - What is the role of AI in food supply chain management?
AI helps streamline logistics, reduce product development times, and improve global distribution efficiency from farm to table. - Why is inclusivity important in agricultural innovation?
Without inclusivity, technological advancements can increase inequality. Inclusive systems ensure all farmers benefit from innovation regardless of gender or economic status.
Reference
AI in agriculture: how technology is already helping farmers || (asiaplustj.info)
