Smart Agriculture:

Can Technology Help Feed a Growing Population?

By AI TV INFO | Global Intelligence — Special Report

A race against time

By 2050, the world could be home to almost 10 billion people. Feeding that population will require more than simply planting more fields. Farmers are already facing water shortages, soil degradation, extreme weather, rising input costs and labour shortages.

According to the Food and Agriculture Organization of the United Nations (FAO), the world may need to produce around 50% more food, feed and fibre by 2050 compared with 2012.

The question is increasingly urgent: Can technology help agriculture produce more food while using fewer resources?

The answer appears to be yes—but with important limits.

The farm is becoming digital

Across the world, agriculture is moving into an era of sensors, satellites, artificial intelligence, drones and autonomous machines.

Instead of treating an entire field in the same way, precision agriculture allows farmers to identify differences within individual areas of a field. Soil sensors can measure moisture and nutrients. Satellites and drones can detect crop stress. GPS-guided machinery can apply seeds, fertilizer and pesticides precisely where they are needed.

Artificial intelligence can then bring these different sources of information together.

The goal is simple: give the crop exactly what it needs, at the right place and at the right time.

Water: perhaps the biggest test

Water is one of agriculture’s greatest constraints.

Agriculture accounts for roughly 70–72% of global freshwater withdrawals, according to FAO estimates. At the same time, around 1.2 billion people live in agricultural areas facing severe water constraints.

Smart irrigation could make a significant difference.

IoT systems can combine soil-moisture sensors, weather information and automated valves to decide when crops actually need water. A 2026 systematic review of 50 studies reported water savings ranging from approximately 9% to 50% across different IoT-based irrigation systems.

Other research has reported even larger savings in particular circumstances. A review of soil-moisture sensor systems found reported water reductions ranging from 20% to 92%, although results varied considerably depending on the crop, climate and irrigation system.

These figures should not be interpreted as a universal guarantee. A 90% saving in one experiment does not mean every farm can cut its water use by 90%.

But the message is clear: measuring water needs can be far more efficient than simply irrigating on a fixed schedule.

Artificial intelligence enters the field

AI is increasingly being used as a kind of digital agricultural adviser.

Machine-learning systems can analyse satellite images, weather forecasts, soil measurements and historical crop data to identify potential diseases, predict yields and optimize irrigation or fertilizer application.

A 2025 meta-analysis of AI-enabled irrigation research reported potential water savings of around 30–50%, alongside productivity improvements of approximately 20–30% in the studies examined.

In another field experiment, researchers using AI and radar-based information for soybean irrigation reported a 30.8% higher yield than a conventional subsurface drip-irrigation treatment, while also reducing irrigation requirements.

The technology does not magically make plants grow faster. Its advantage comes from better decisions: knowing when to irrigate, where to apply nutrients and when a crop is beginning to suffer from stress.

Drones: eyes above the crops

A farmer walking across hundreds of hectares cannot inspect every plant. A drone can cover large areas in minutes.

Equipped with ordinary or multispectral cameras, agricultural drones can identify differences in plant colour, temperature and vegetation health. This can reveal areas affected by drought, disease, pests or nutrient deficiencies before the problem becomes obvious to the human eye.

Drones can also support targeted spraying.

Instead of applying chemicals uniformly across an entire field, precision systems can identify problem areas and treat them selectively. Reviews of UAV-based smart-farming applications have reported fertilizer reductions of up to 40% in some applications.

The potential is particularly important because unnecessary chemical application costs farmers money while increasing the environmental burden of agriculture.

Robots and the changing agricultural workforce

Technology is also moving from observation to action.

Agricultural robots are being developed for tasks including weeding, harvesting, planting and crop monitoring. Autonomous machines can operate for long periods and perform repetitive work that is increasingly difficult to staff in some farming regions.

AI-powered “see-and-spray” systems, for example, use cameras and machine-learning algorithms to distinguish crops from weeds before applying herbicide.

Some studies and commercial field trials have reported herbicide reductions of around 70–80% in targeted spraying applications.

Robotics could therefore address two problems simultaneously: labour shortages and excessive chemical use.

But autonomous farming remains expensive, and sophisticated machinery is much easier for a large commercial farm to purchase than for a smallholder farmer.

More food from less land?

Controlled-environment agriculture offers another technological approach.

Hydroponic and vertical farming systems grow crops in carefully controlled environments where temperature, light, nutrients and water can be precisely managed.

Some systems can use far less water than conventional agriculture, with certain vertical-farming models reporting reductions of up to 90–95% in water use.

The attraction is obvious: food can potentially be produced close to cities, throughout the year and with very little land.

But there is a catch.

Vertical farms require electricity, sophisticated equipment and significant investment. They are particularly suited to certain high-value crops such as leafy greens and herbs—not necessarily staple crops such as wheat, rice or maize.

In other words, vertical farming is not a replacement for conventional agriculture. It is another tool in the agricultural toolbox.

Technology can also fight food waste

Producing more food is only half the challenge. The world also loses enormous quantities of food before it reaches consumers.

FAO data indicate that approximately 13.3% of food was lost globally between harvest and retail in 2023.

Fruit and vegetables are particularly vulnerable, with losses estimated at around 25.4% in 2023.

Technology can help monitor temperature and humidity during storage and transport, predict demand, improve logistics and identify products approaching spoilage.

At the consumer and retail level, the United Nations Environment Programme estimated that approximately 1.05 billion tonnes of food were wasted in 2022, equivalent to around 19% of food available to consumers.

That means feeding the future is not simply about producing more.

It is also about losing less.

But who gets access to smart farming?

The technological revolution has a serious weakness: not every farmer can afford it.

Sensors, drones, autonomous machinery and AI platforms require investment. Rural areas may lack reliable internet, electricity or digital infrastructure. Farmers may also need training to interpret and use the information generated by these systems.

FAO has identified cost, digital skills, connectivity and infrastructure among the important barriers to digital agricultural technology adoption.

There is therefore a danger that technology could create a two-speed agricultural system: highly automated farms on one side and farmers without access to digital tools on the other.

For smallholder farmers, the most useful technology may not be an expensive autonomous tractor. It could be something much simpler—a mobile phone providing weather forecasts, a low-cost soil-moisture sensor or an affordable irrigation controller.

So, can technology feed 10 billion people?

Smart agriculture is not a magic solution.

Technology cannot solve poverty, unequal food distribution, conflict, land ownership problems or food waste by itself. Nor can AI replace farmers’ knowledge of their soil, climate and crops.

But the numbers suggest that technology can make a meaningful contribution.

If agriculture must produce roughly 50% more food by 2050, while water resources are under increasing pressure, farmers will need to become more precise and efficient.

The future may therefore look less like a traditional farm and more like a connected ecosystem:

Sensors collect data.
Satellites and drones observe crops.
AI analyses the information.
Smart irrigation delivers water.
Robots perform targeted tasks.
Farmers make the final decisions.

The real agricultural revolution may not be about replacing the farmer with a machine.

It may be about giving the farmer better information and better tools to produce more with less.

The AI TV INFO’s bottom line

Smart agriculture can help feed a growing population—but technology alone cannot do it.

The biggest opportunity lies in combining digital tools with sustainable farming, resilient crops, efficient irrigation, better infrastructure, farmer education and policies that make technology accessible to small and large farms alike.

The challenge for the coming decades is not simply to ask:

“How can we grow more food?”

It is to ask a more difficult question: