Harnessing AI to combat hunger: Bridging innovation and real-world needs

Many perceive hunger as an abstract issue, but for millions, it is a daily struggle. A staggering 757 million people experience chronic hunger daily, a crisis worsened by conflict, natural disasters, and economic instability. AI has the potential to revolutionize the fight against hunger and offer innovative solutions if its implementation is guided by practical needs, particularly in underserved areas.

An article by the Diplomatic Courier has shed light on why AI must address these real and immediate challenges, particularly for those without access to economic opportunities.

The author points out that AI-powered precision agriculture, for instance, can help smallholder farmers in remote regions optimize resources like water, fertilizers, and seeds, increasing food production while reducing waste. AI-driven supply chain systems can enhance food distribution, cutting transport costs and minimizing food loss. However, these innovations will only succeed if they incorporate local knowledge and on-the-ground realities.

A warning put forward in the article entails that the technology must be deployed with a clear humanitarian purpose. Many smallholder farmers, who are critical to global food production, lack even basic technologies. AI for its own sake does not solve hunger; instead, public-private partnerships are necessary to bridge gaps in technology and knowledge. The WFP Innovation Accelerator, for example, connects impactful AI-driven solutions with WFP’s global network across 120 countries, ensuring real-world application.

The importance of data in the Global South

AI relies on high-quality data, yet many hunger-affected regions suffer from a lack of reliable information. Hunger hotspots are often "data deserts," where traditional data models overlook the unique challenges faced by these communities. To make AI meaningful, humanitarian organizations, governments, and private companies must collaborate to build robust datasets that accurately reflect local conditions.

AI can also play a pivotal role in forecasting crises. The article clarifies that AI-powered early warning systems can predict food shortages, extreme weather events, or resource gaps, enabling proactive interventions before disasters escalate. However, these systems are only as effective as the data that informs them. Without accurate and timely data, even the most advanced AI models will fail to address the needs of vulnerable populations.

To maximize AI’s impact, scaling efforts must focus on areas that provide tangible benefits. Instead of chatbots, AI applications in precision agriculture, personalized nutrition, and farm-to-fork digitization via blockchain can significantly enhance food security. These solutions can increase food availability, improve nutritional outcomes, and reduce costs simultaneously.

However, scaling AI is not just about funding—it requires proof of effectiveness. Humanitarian organizations need rigorous testing and real-world validation to demonstrate AI’s impact. Building trust through tangible results will unlock further investment and accelerate the adoption of AI solutions in food security.

For AI to succeed in the fight against hunger, collaboration is essential. Humanitarian organizations, private companies, startups, and local stakeholders must work together to build trust in AI-driven solutions. Public-private partnerships can ensure that AI benefits are democratized, providing equitable access to vulnerable communities.

By Nazrin Sadigova