These technologies, which also include computer vision, edge Internet of Things (IoT), CRISPR (clustered regularly spaced short palindromic repeats) and nanotechnology, will increase resilience and productivity while safeguarding rural livelihoods, the WEF said in a new report.
The report, titled ‘Shaping the Deep-Tech Revolution in Agriculture’ and developed in collaboration with stakeholders from both industry and academia, comes at a time when agriculture worldwide is facing a confluence of crises.
Increasing rural-to-urban migration, intensifying climate extremes and accelerating degradation of natural resources, especially soil and water, collectively threaten productivity and endanger livelihoods dependent on agriculture.
According to the Food and Agriculture Organization of the United Nations, the world would need to produce significantly more food to feed a growing population by 2050.
This will have to be achieved in the face of increasing pressures, with a third of the world’s soil degraded, 71 percent of aquifers depleted and the average farmer living to be around 60 years old.
The WEF said these seven technology domains have the potential to drive fundamental shifts in the way crops are grown, monitored, protected and distributed, improving productivity, sustainability and resilience in the sector.
The report also highlighted the potential of converging these technologies for high-impact use cases such as autonomous swarm robotics, precision agriculture management, agentic AI systems and carbon reporting.
It showcased use cases such as climate-resilient rice varieties that produce 20 percent fewer emissions, precision farming in sugarcane that has improved yields by 40 percent, and the use of remote sensing to predict supply chain risks and promote carbon finance for farmers.
The WEF called for greater efforts to scale up deep technological innovations that can help reshape agricultural systems and address pressures, and urged governments to adopt flexible policies and regulatory sandboxes to keep pace with technological advances.
The report was released by the WEF’s Artificial Intelligence for Agriculture Initiative (AI4AI).
Since 2021, the AI4AI initiative has made commitments to deliver digital technologies to over 8,95,000 farmers in India.
AI4AI has fostered multi-stakeholder partnerships, including between governments, the private sector, academia, start-ups and civil society, to build evidence on the transformative impact of technology in agriculture.
Building on lessons learned in India, AI4AI has supported the conceptualization of similar initiatives in the Kingdom of Saudi Arabia, Colombia and Brazil.
According to the WEF, irregular rainfall and rising temperatures have already led to losses of almost 65 percent in various horticultural crops.
It cited a case study on the Indian Council for Agricultural Research (ICAR) developing climate-resilient rice in the country.
Conventional crop improvement methods have long breeding cycles and limited precision, delaying the development of varieties suitable for dealing with emerging climate and disease pressures.
To overcome this, ICAR researchers used CRISPR-based genome editing to develop two rice varieties. The first, DRR 100, has improved tolerance to drought, salinity and climate stress. It could lead to a 19 percent increase in yields and a 20 percent decrease in greenhouse gas emissions.
The other variety, Pusa DST Rice 1, can increase yields by 9.66 percent to 30.4 percent on saline and alkaline soils, potentially leading to a 20 percent increase in production.
Another case study referred to remote sensing for efficient crop insurance under India’s Pradhan Mantri Fasal Bima Yojana (PMFBY).
Crop loss estimates for insurance have traditionally been based on manual crop-cutting experiments (CCEs), but this method is slow, often inaccurate and can lack transparency, delay claims settlements and cause disputes.
To solve this, PMFBY implemented a technology-driven solution focused on remote sensing. The system uses satellite imagery to monitor crop health, while high-resolution drones and a dedicated mobile app for geotagged, real-time data collection complement this.
This multi-layered approach replaces subjective manual assessments with objective, verifiable data, streamlining the entire loss estimation process.
The WEF says such a technological transformation could ensure faster and more accurate claims settlement, helping farmers receive crucial financial support when they need it most.
The use of objective satellite data increases transparency and builds trust, while the comprehensive crop health data also allows government and insurers to better manage agricultural risks and develop more effective insurance products.
Other case studies from India focused on local programs for developing nano-inputs to increase resilience, using satellite-based remote sensing for carbon monitoring, reporting and verification (MRV), and using digital public infrastructure to scale generative AI and natural language processing.
Launched under India’s National Language Translation Mission, Bhashini is an initiative led by the Indian government to develop a public digital infrastructure for language translation and speech technologies in Indian languages.
It provides open-source datasets, language models and APIs for automatic speech recognition, machine translation and text-to-speech systems.
For deep tech startups, Bhashini lowers the barriers to entry by enabling the integration of local voice and text interfaces into their use cases. This facilitates broader reach to non-English speaking users, supports regional deployment at scale, and reduces the cost of building multilingual digital tools.
Published on November 7, 2025
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