Deep technology revolution in modern agriculture

This article was first published in The Edge Malaysia Weekly from June 1, 2026 to June 7, 2026.

For generations, agricultural technology has been ruled by intuition. Farmers have relied on historical weather patterns and the “skilled human eye” to grow life from the soil. But today, that intuition is colliding with harsh mathematical reality.

According to the Food and Agriculture Organization of the United Nations, the world’s population will reach 9.1 billion by 2050, requiring a massive 70% increase in global food production. We are already behind. The Global Report on Food Crisis 2026 (GRFC) reveals that approximately 266 million people in 47 countries face high levels of severe food insecurity due to a combination of systemic shocks such as extreme weather events and supply chain disruptions.

The crisis here in Malaysia is a sovereign crisis. Our country’s food imports continue to approach a staggering RM80 billion annually, exposing the domestic economy to severe currency fluctuations. This deficit is caused by a significant imbalance in land use. Despite the abundance of arable land, less than 10% of the land is devoted to food crops, and more than 90% is devoted to industrial cash crops such as oil palm and rubber.

To survive the coming demographic and climate cliff, the agriculture sector must urgently move from reactive, intuition-based practices to a proactive, data-driven ecosystem. We must move towards Agriculture 5.0, leveraging the deep technologies of the Fourth Industrial Revolution (IR4.0) to unlock both unprecedented business success and true environmental, social, and governance (ESG) leadership.

Agriculture has always been a battle against the weather. For generations, the stakes have been calculated. Farmers read the seasons, trusted the soil, and planned based on relatively consistent weather patterns from year to year. Climate change has completely broken that deal. Droughts come without warning, pest migration accelerates, and by the time someone notices something is wrong, the damage has already been done.

There is another issue that is rarely talked about. The problem is that modern farms are so large that it’s impossible to closely monitor them. Human scouts roam the area. But what’s going on in the middle of a 200-hectare farm? No one really knows until it’s too late.

Deep tech AI solution

This is where the convergence of satellite imagery, multispectral drones, and machine learning starts to feel more like a superpower than a technology. Rather than waiting for yellowing leaves to signal distress, artificial intelligence (AI) systems can now detect early signs of stress, water deprivation, and fungal infections in plants at the cellular level. It takes a full 10 to 14 days before it becomes detectable to the human eye. The system does this by continuously synthesizing data from soil chemistry, hyperlocal weather feeds, and drone-captured imagery processed through a normalized difference-in-vegetation (NDVI) algorithm. It essentially gives farmers a window into the future.

Results are measurable. Farms using these predictive models consistently see marketable yield increases of 5% to 10%. It’s not about farming more land, it’s about farming smarter within the same land.

In Malaysia, this has already gone beyond a pilot project. Agritix deploys satellite and multispectral imagery to provide real-time warnings of plantation anomalies. Bit Group’s AI engine combines weather and soil data with real-time yield predictions and disease warnings. Additionally, the government-backed MyAgriTECH initiative is systematically deploying AI-powered environmental analytics across the sector and reports more than 90% efficiency gains in resource management.

2. The true cost of “spray and pray”

Agriculture is secretly the world’s largest consumer of water. And for decades, the standard approach to protecting crops has been to blanket-spray the entire field with fertilizers and pesticides, regardless of whether every nook and cranny is actually needed. It is expensive, environmentally destructive, and increasingly at odds with the ESG expectations currently placed on the sector.

Deeper damage is less obvious, but just as serious. This type of indiscriminate spraying destroys the soil microbiome that keeps farmland fertile over the long term. The spilled chemicals contaminate the surrounding waterways. And as input costs continue to rise, farms that double down on this approach are essentially paying more to cause more damage, reducing their profits with each step.

Deep tech AI solution

A smarter approach is to use exactly what you need, where you need it, rather than guessing and using less.

Internet of Things (IoT) sensor networks can now achieve that precision at scale. These low-cost sensors are embedded throughout the farm and feed continuous readings of soil moisture, pH, and nutrient levels into the AI, which responds in real-time. Once a particular zone is empty, the system calculates the exact amount of water required and opens the appropriate valve. No human judgment is required and no water is wasted elsewhere.

Pest control is becoming more sophisticated. We deploy reconnaissance drones equipped with multispectral sensors to fly over fields to identify signs of cellular stress due to pest activity long before visible damage appears. Once a hotspot is flagged, AI processes the image and uses convolutional neural networks to diagnose the exact pest species and generate an accurate “prescription map.” A heavy-spraying drone then flies autonomously through those coordinates and opens its nozzles only on zones where problems are identified.

The results speak for themselves. Compared to traditional methods, pesticide usage is reduced by 35% to 60% and water usage is reduced by up to 90%. This is not only good for the environment, but also directly reduces input costs and strengthens the farm’s sustainability credentials.

Locally, Terra Drone Agri is expanding its smart plantation operations through advanced aerial mapping. iTani’s AI-powered laser recognition system has helped orchard farmers reduce pesticide use by as much as 90%. The blanket spray hybrid drone effectively replaced 20 manual workers with a two-person team while achieving 100% spray accuracy.

3: Who will plow the field tomorrow?

There are some disturbing statistics at the heart of world agriculture. The average age of Japanese farmers is 67.6 years old. The United States secretly imports nearly 500,000 temporary workers each year just to prevent crop failure. The workforce responsible for weeding, maintaining and harvesting is aging faster than it can be replaced, and the food systems built around it are now truly vulnerable.

This vulnerability runs deeper than just numbers. When harvesting is almost entirely done by humans, any disruption, such as a pandemic, changes in border policy, or unusually hot weather, can lead to a breakdown in the food supply. The margin of error is shrinking year by year.

Deep tech AI solution

Robots don’t get tired and don’t age. Drone swarms with three to five fully autonomous units working together for mapping and dispersal are now a reality. Smart Ground Rover navigates crop rows with machine vision that is precise enough to identify and target individual weeds in milliseconds, reducing chemical use by up to 90%. Additionally, a robotic arm with a soft gripper and deep learning model can now visually assess the ripeness of fruit before harvesting. Something that seemed like science fiction not too long ago.

Malaysia is one of the countries that is moving most deliberately to close this gap. The Harvest-Mate robot applies machine learning and a mechanical arm to oil palm harvesting, increasing productivity by more than 120% compared to manual methods. Poladrone deploys autonomous drones for targeted weed spraying, eliminating not only the labor force but also the real danger of workers carrying backpacks of heavy chemicals over dense, uneven terrain.

This change will not replace farmers. The goal is to ensure that the fields do not remain untouched even if the people who once tended them disappear.

The transition to Agriculture 5.0 requires not only available technology, but also a coordinated national ecosystem that bridges the gap between deep tech developers and traditional farmers. The most important breakthrough for the everyday farmer is the Drone-as-a-Service (DaaS) model. Small-scale farmers do not need to purchase expensive spraying drones. Instead, we hire local drone operators for a flat fee, completely removing capital investment (Capex) barriers and democratizing access to precision agriculture. Platforms like Agrimor SuperApp are already connecting farmers to on-demand drone services, increasing crop yields by up to 67% and reducing food production costs by 50%.

In Malaysia, this mission is actively promoted by the Malaysian Technology Innovation Research Accelerator (MRANTI). Recognizing that national food security cannot rely solely on large corporate wealth, MRANTI focuses on the digital inclusion of smallholder farmers.

For commercial farmers and technology entrepreneurs, deep technology is only possible if the math works. Hesitancy to adopt Agriculture 5.0 often stems from the perceived cost of entry, but separating capital and operational expenditures reveals a very lucrative reality.

Data reveals a different reality. For commercial farms in Malaysia, an upfront investment of RM50,000 to RM100,000 in a drone ecosystem and AI sensors is not a sunk cost, but a quick-return asset. The technology generates break-even within just one or two harvest cycles by reducing volatile input costs, reducing fertilizer waste by 20% and reducing pesticide use by up to 50%.

The transition to Agriculture 5.0 is no longer an imported futuristic concept. MRANTI coordinates scalable solutions to address workforce and yield challenges through the Malaysia Drone Technology Action Plan 2022-2030. They provide important physical testbeds like Area 57, a drone technology center of excellence where AI obstacle avoidance and swarms of drones stress test the drones before deployment.

For modern agricultural entrepreneurs, upfront investments in drones, AI, and IoT are not sunk costs, but assets with immediate returns. Moving from intuition-based agriculture to data-driven ecosystems is no longer just an environmental imperative, but the most logical business decision we can make to secure our food supply and lead the future of global agriculture.

Akhil Gupta is the Vice-Chairman of the AI ​​Chapter and Chairman of the AI ​​Academy at PIKOM (National Tech Association of Malaysia). He is Group CEO of Talbotiq Technologies and Total IT Global.

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