Shaping the Deep Tech Revolution in Agriculture 2025

Introduction Over the past decade, there has been significant innovation in the technologies for the agriculture (or agritech) sector, creating impact at both farm and systemic levels. Farmers have used agritech to reduce cultivation costs, improve yields, secure better prices and enhance resilience.1 Agribusinesses have drawn on agritech for efficient sourcing, and to streamline farmer management, ensure compliance (e.g. with the European Union Deforestation Regulation [EUDR]), map supply chain risks and transition to carbon neutrality. With a growing population and shrinking resources, agritech could play a keystone role in food security and rural livelihoods. Yet several barriers remain such as low adoption, limited contextual data for developing solutions, high capital expenditure (capex) for certain use cases and rising data silos. To address these challenges, the World Economic Forum launched the Artificial Intelligence for Agriculture Innovation (AI4AI) initiative in 2021. AI4AI aims to scale agritech through an ecosystem approach that encompasses public–private partnerships, the development of digital public infrastructure and agritech policies. A key component of AI4AI is to drive thought leadership on agritech. In 2021, the initiative launched a community paper that documented promising use cases of agritech and presented a roadmap for scaling them.2 The second insight report presented an overview of the next wave of agritech solutions, especially those relevant to emerging economies.3 Acknowledging the rapid pace of technology development, this edition of the report pivots towards the deep-tech revolution in agriculture. The learnings are based on more than 75 community consultations (as a part of AI4AI’s programmes), agritech convenings organized by the initiative and multiple on-the-ground pilots facilitated by community members. The insights are further enriched through structured interviews with around 20 deep-tech experts. The report identifies technology domains that may currently be at an early stage but have the potential to address converging challenges in agriculture. It details seven of these domains and several convergent use cases. Further, the report highlights mechanisms for developing robust systems for seeding, de-risking and commercializing agri deep tech.Globally, agritech is increasingly being accepted as a key lever to drive inclusivity, sustainability and efficiency in supply chains. Since 2021, the AI4AI initiative has unlocked commitments to provide digital technologies to more than 895,000 farmers in India. AI4AI has promoted multistakeholder partnerships including among governments, the private sector, academia, start-ups and civil society to generate evidence on the transformational impact of tech in agriculture. Its work includes a value chain transformation project in Telangana impacting 50,000 farmers (including more than 30% women), almost doubling their incomes, establishing India’s first Agriculture Data Exchange (in partnership with the Government of Telangana) and supporting agritech and agri data management policies in three states. Building on lessons learned in India, AI4AI has supported the conceptualization of similar initiatives in the Kingdom of Saudi Arabia, Colombia and Brazil. Shaping the Deep-Tech Revolution in Agriculture 5