According to the World Economic Forum (WEF), more than 1.2 billion people rely on the global agrifood sector for their livelihoods. Yet feeding a projected 9.1 billion people by 2050 will require a 70 percent increase in food production and roughly $83 billion in annual agricultural investment across developing countries. Thus, increasing the efficiency of agricultural systems is necessary. Without accounting for sustainability, the benefits of efficiency will be short-lived. Hence, innovations in agritech are essential to improving productivity through sustainable pathways.
At the heart of this innovation is precision agriculture, which integrates data to inform optimal agricultural practices to farmers. This approach leverages AI-powered analytics, remote sensing, and the Internet of Things (IoT) to help farmers make informed decisions. One standout case study is the Saagu Baagu initiative in the south Indian state of Telangana. The project aimed to improve both income and agricultural productivity of smallholder chilli farmers by providing them with AI-based advising, soil testing and digital market linkages. From May 2022 to March 2023, an initial pilot involving over 7,000 chili farmers achieved remarkable outcomes. Farmers saw their incomes double and yields increased by 21 percent per acre. At the same time, they reduced use of chemical fertilizer and pesticides by 5-9 percent.
Building on these advancements, intelligent crop planning techniques are transforming on-farm decision-making and resource management. These techniques include gene-edited seeds, real-time soil testing, AI-optimized sowing recommendations, and augmented-reality tools for crop planning. Using AI-assisted gene editing enables seeds that require fewer inputs while producing higher yields. Similarly, AI tools such as sensors and spectroscopy-based soil testing kits help test soil in near real time and increase yields. Crop planning using augmented reality also helps visualize and optimize field layouts before planting. A B2B crop intelligence platform, Pakistan’s Farmdar initiative utilizes satellite imagery and AI models, achieving 95 percent accuracy in crop intelligence, thereby strengthening supply chain and procurement decisions in agriculture.
Smart farming combines both AI and AR technology to manage crops, control pests, address plant diseases, and enhance yields. Using imaging and built-in Light Detection and Ranging (LiDAR), as well as machine learning apps, farmers can use visualization on the ground to make stronger decisions regarding plant health and yield predictions. The latter leverages data analytics and machine learning including the adoption of neural networks to predict agricultural yields. Furthermore, the adoption of robots and drones play a pivotal role in farm mechanization and automation. This helps address any labor shortages and reduces cultivation costs. In Brazil, the government utilized AI-powered weather predictions, precision farming using machine learning, AI-driven advisory services and smart irrigation systems using sensors and AI to optimize water usage. These changes led to a 12 percent increase in crop production in 2022, the highest agricultural growth rate Brazil had seen in a decade. In Pakistan, the RemoteWell initiative uses Internet of Things (IoT) enabled irrigation systems to help farmers control and monitor tubewells remotely by reducing costs and improving water use efficiency. These examples illustrate how both governments and innovators are driving a global shift towards technologically integrated agricultural systems.
Controlled Environment Agriculture (CEA) represents another significant innovation, shifting farming from outdoor fields to managed indoor ecosystems. This approach reduces weather dependence and pest exposure. South Korea and Japan have already adopted smart greenhouses which utilize ICT (Information and Communications Technology) to regulate temperature and humidity. Taiwan is considered a global leader in vertical farming, where crops are cultivated in vertical layers without soil. In Taipei, a vertical farm has been established inside a metro station. This method produces pest-free yields and transforms unused urban spaces into productive agriculture areas.
These initiatives highlight how agritech is sparking a new green revolution. While innovation holds immense potential in the agricultural sector, it also faces considerable challenges. For example, high upfront costs of technology such as AI-powered sensors and drones often make them unaffordable for smallholder farmers. Moreover, agritech requires both technical training and reliable internet access. Developing and least-developed countries face digital infrastructure gaps in rural areas, without which sophisticated technical devices are ineffective. As automation becomes widely adopted, this also increases the risk of job displacement for manual agricultural laborers, potentially leading to increased income inequality in agrarian communities. Agritech can help reshape the future of farming, but closing gaps in access, affordability, and digital infrastructure is essential to ensure this new green revolution is both inclusive and sustainable.