AI could boost agricultural sector’s contribution to India’s GDP: WEF report

The global AI market, valued at $136 billion in 2022, is projected to grow over 13 times to $1.8 trillion by 2030. If implemented at scale, AI could be a critical tool to boost India’s agricultural sector’s contribution to GDP, which is currently at 18% while employing close to 46% of the country’s population, according to a new report by the World Economic Forum’s (WEF) latest collaboration with the central government and BCG.

Key findings of the WEF report:

The report cites a recent pilot project in Telangana (Saagu Bagu), conducted in collaboration with the WEF and Telangana, which provided four AI-enabled applications to around 7,000 chilli-growing smallholder farmers. “After just one season, the farmers reported a 21% improvement in yields, an 11% increase in the unit prices their produce commanded and a 9% reduction in the fertilisers and pesticides they needed to use,” says the report. 

The data showed that consequently, these farmers were able to significantly boost profits, earning an average of $800 more per acre per crop season – a significant increase considering Indian farmers’ average annual income is less than $1,500.

The report says AI-based sowing advice has proven transformative in Andhra Pradesh as well, helping farmers boost yields by up to 30%. Similarly, AI-enabled pest-detection models have empowered around 3,000 farmers in the state to forecast and address pest infestations proactively, the report shows.

By delivering data-driven predictions and augmenting traditional farming, AI creates opportunities for farmers to enhance their resilience, productivity and profitability, it says. “For instance, precision agricultural solutions address farmers’ resource constraints by offering best practices to maximise output with optimised input.”

Similarly, predictive analytics reduce climate vulnerability by providing weather forecasts and helping to manage pest infestations before they scale. “Furthermore, AI-enabled market intelligence systems help alleviate the economic pressures faced by farmers, such as rising input costs or fluctuating market prices, by bridging information gaps and providing timely, data-driven insights for better decision-making.” 

Additionally, at a macro level, the WEF report says AI has the potential to curb emissions from the agricultural sector by optimising resource use to allow economies to reach their net-zero goals, while also enhancing agricultural GDP. “In the Indian context, use cases for AI in agriculture can help address systemic challenges in agriculture such as lower productivity in certain crops compared to global averages, restricted finance for smallholder farmers, increasing soil degradation and high pre- and post-harvest losses.” 

WEF on the need for an AI playbook

The WEF report says AI’s potential to tackle agriculture’s complex challenges, combined with the many obstacles in deploying the technology together, underscores the need for a clear and well-defined framework to develop an AI ecosystem for agriculture. 

It says the AI for agriculture playbook has three purposes: 

1. To provide an overview of potential AI use cases for agriculture that can be operationalised 

2. To illustrate a structured framework on the critical pillars (enable, create and deliver) with clear actions and guidelines for stakeholders 

3. To lead the way to a call for action and provide a dynamic platform to explore what’s next. The playbook’s primary target audience is policymakers, but it will help other stakeholders as well. 

Hurdles in implementing AI in agriculture   

While the AI-driven transformation of agriculture may have begun, deploying technology at scale is not easy, the report finds. Its use is still limited in agriculture: according to experts, fewer than 20% of Indian farmers use digital technologies, which are a superset of AI-enabled solutions. There are several reasons for this low rate of adoption. For instance, the low income of Indian farmers (around $1,500 annually) restricts both their ability and willingness to pay for AI solutions. 

Without financing support, technology interventions are perceived to be an added burden, given the already increasing cost of cultivation. Additionally, close to 85% of India’s 150 million farmers are smallholders, and the Indian farmer’s average landholding is just 1.08 hectares (about 2.67 acres). “With such small landholdings, which are often fragmented, the cost of delivering AI solutions in rural settings increases tremendously,” says the report.

On the supply side, the development and use of AI solutions rely on the collection of large volumes of data, often in real time, which requires investment in infrastructure and resources, and this drives up the cost of AI development. “This indirectly increases the cost of services, further affecting their affordability.”

Additionally, there are very limited institutional mechanisms for validating technology before it is deployed, increasing the perceived risk of adoption.