Empowering Food Security Through the Implementation of Artificial Intelligence
Monday, 26 May 2025
Jakarta Investment Centre
5 days
Food security has emerged as one of the most critical global challenges. As the world’s population continues to rise, the demand for food also increases significantly. The Food and Agriculture Organization (FAO) reported that, as of 2024, between 713 and 757 million people faced hunger globally, with a mid-range estimate of 733 million individuals affected (Food and Agriculture Organization, 2024). This highlights the issue's urgency, particularly as global food demand is projected to rise by 35% to 56% between 2010 and 2050 (Van Dijk et al., 2021). These challenges are further compounded by climate change, land degradation, rapid urbanization, and escalating geopolitical tension, which continue to disrupt food supply chains and increase the strain on global food resilience. Similarly, Southeast Asia is also vulnerable to the impacts of climate change. According to Ludher and Leng (2024), the production of commodities such as rice, corn, and wheat is projected to decline by 7% to 9% by 2050. Amid these challenges, Artificial Intelligence (AI) is emerging as a transformative tool to help tackle these challenges and support a sustainable and resilient food system. This article explores the role of AI in supporting sustainable food security globally, and the opportunities for its application in Jakarta as part of efforts to build a resilient city capable of addressing future food security challenges.
Global Implementation of AI in Agriculture and Food Security
Amid increasing global challenges in food production and distribution, the adoption of AI has expanded across multiple areas, enhancing overall efficiency and productivity. These innovations have been driven by the growing need to boost agricultural output in a way that is environmentally responsible and efficient, while also ensuring fair access to food for all segments of society. This effectiveness is reflected in the agricultural sector, where AI has been shown to increase crop yields by up to 20% (Geopard Agriculture, 2023).
Following its proven potential to enhance productivity, AI can also enhance crop management. In India, Microsoft and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) collaborate on analyzing 30 years of climate data to optimize planting schedules. This approach allows the farmers to adapt to increasingly erratic wind and monsoon patterns due to climate change. As a result, farmers using the system reported an average increase in peanut yields of 30% per hectare (Microsoft, 2018).
The impact of AI in agriculture is not limited to on-farm activities, contributing significantly to food distribution and efforts to reduce inefficiencies across the supply chain. Through AI-driven predictive analytics, businesses can anticipate demand and allocate resources more effectively. This agility enables distributors to scale without massive, time-consuming adjustments to labor and workflow (Li, 2024). Moreover, the HungerMap Live platform by the World Food Programme (WFP) applies big data and AI to monitor food security conditions in over 90 countries in real-time. The system processes data on food prices, weather patterns, and socio-economic conditions to generate nowcasts, which help WFP identify food-insecure areas and enable the more effective allocation of humanitarian resources (Ong, 2020). Another platform by WFP is the Food Price Monitoring and Analysis (FPMA), which tracks food prices and detects unusual price changes, providing early warnings to relevant authorities to support evidence-based decision-making.
The expanding role of AI in addressing food security and agricultural challenges also extends to weather forecasting, where it contributes to more informed decision-making in the agricultural sector. AI’s ability to analyze vast amounts of climate data in real time enables more precise anticipation of extreme weather events that could disrupt food production and distribution. In West Africa, AI provides accurate rainfall forecasts to help smallholder farmers make more informed decisions (UN World Food Programme, 2025). In addition, Google is also developing a system that can predict rainfall patterns every 15 minutes, up to 12 hours in advance, within a 5km radius (Brempong, 2025). These technologies support farmers in determining optimal times for planting and harvesting and make better informed decisions.
While AI has been applied to forecast weather conditions, it is also used to help farmers detect pests and diseases earlier, allowing them to act before serious damage occurs. One implementation of this involves a digital tool that uses AI to identify hundreds of disease symptoms across various crop types, simply by analyzing images of leaves or fruits uploaded by farmers (Chassin, 2025). This application has the potential to reduce pesticide use and minimize yield losses, especially for smallholder farmers, while also contributing to more sustainable agricultural practices.
These various applications highlight how AI is transforming agriculture across the entire global food chain, from production to distribution. By enabling more precise and data-driven decision making, reducing resource inefficiencies, and supporting early detection of pests and diseases, AI contributes to a more productive, efficient, and resilient food system from farm to fork.
The Future Potential of AI for Jakarta’s Food Security
These global developments demonstrate what is possible, but also point to even greater potential for AI to be further implemented in improving agricultural productivity and strengthening food security systems. In this context, Jakarta faces limited agricultural space and relies on food supply chains from other regions for up to 98% of its needs (Hamasy, 2024). Jakarta’s high dependence on external food supply chains demonstrates the importance of ensuring food security and market stability. Disruptions in these supply chains, whether caused by crop failures or logistical challenges, may disrupt price stability and affect the reliability of supply. The impact of this vulnerability became evident in 2024, when premium rice prices in Jakarta increased by 22.9% due to reduced national rice production caused by the El Niño phenomenon (GovMedia, 2024).
Recognizing these vulnerabilities, the Jakarta Provincial Government has begun exploring ways to enhance food security by providing daily commodity price data from local markets across all regions of Jakarta. Supported by the city’s existing digital infrastructure, the integration of AI has the potential to strengthen Jakarta’s food security by enabling more comprehensive monitoring, preventing abnormal price spikes, and improving the government's responsiveness in anticipating potential challenges and maintaining market stability. This approach aligns with the World Food Programme’s Food Price Monitoring and Analysis platform, which supports governments and stakeholders in making more proactive, evidence-based decisions in managing food markets.
As part of a more comprehensive approach to food security, Jakarta has begun promoting the smart farming system to improve the effectiveness of farmland in Ragunan (Putri, 2023). This system allows for the remote monitoring and control of agricultural variables such as temperature, air humidity, crop watering schedules, and even livestock and fishery operations, reducing the need for constant on-site supervision. Smart farming holds significant potential for Jakarta, not only in improving efficiency but also in supporting precision agriculture. By automatically analyzing environmental factors such as soil moisture, temperature, and weather conditions, the system can provide optimized recommendations for planting and irrigation based on real-time crop development and climate data.
Addressing Jakarta’s food security challenges, particularly its dependence on external food supplies and limited land availability for agriculture, requires strategic innovation through the optimization of AI. Applications such as AI-based agricultural monitoring and the integration of environmental data offer a forward-looking approach to strengthening food security in Jakarta.
Conclusion
Food security remains a critical challenge at both global and urban levels, and the integration of AI presents a powerful and scalable solution. Its application extends across the food system from farm to fork, enhancing supply chain responsiveness, enabling precise forecasting, and early detection of risks such as pests and diseases. In Jakarta, where land availability is limited and reliance on external food sources remains high, AI-based solutions offer a practical approach to supporting a more secure and responsive food ecosystem. With continued efforts to enhance Jakarta’s existing digital infrastructure, the city is taking meaningful steps toward a more informed, efficient, and sustainable food ecosystem that encourages collaboration and supports long-term urban resilience.
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