Global IndiaAI Summit 2024

Introduction

As part of India’s leadership of the Global Partnership on Artificial Intelligence (GPAI) in 2024, a dedicated session on Sustainable Agriculture was convened during the IndiaAI & GPAI Mid-Year Summit. This session followed the global virtual convening held in April 2024 and built further momentum around the emerging theme of AI for Sustainable Agriculture, which was formally accepted into GPAI’s mandate in December 2023.

The session brought together policymakers, researchers, start-ups, technologists, non-profits, and private sector actors to reflect on current progress, present AI-driven solutions, and discuss concrete pathways for collaborative action to accelerate AI adoption in agriculture.

Session Objectives

• To deepen the discourse on sustainable agriculture through the lens of AI applications.
• To showcase case studies highlighting AI's transformative role across various agricultural domains.
• To co-create actionable strategies for GPAI and member countries to advance the theme.
• To identify collaboration opportunities across public, private, and research sectors.

Thematic Focus Areas and Presentations

The session was structured around three thematic pillars, each featuring presentations of real-world innovations:

A. Crop Advisory

Presenter: Mohammad Salman, Wadhwani AI

Wadhwani AI showcased its AI-based pest and disease detection system that enables early identification and targeted advisories for farmers. Through partnerships with state governments and NGOs, the system scaled from 800 to over 116,000 farmers in three years, significantly reducing pesticide overuse and soil degradation.

Key Takeaways:

• Importance of simple, offline-capable tech for rural deployment.
• Integration into state and national agriculture surveillance systems is underway.

B. Market Access and Financial Inclusion

Presenter: Sanjay Uppal, CEO, FinBotsAI

FinBotsAI demonstrated the use of AI in credit scoring and risk assessment to enable financial inclusion for farmers. Their tools, deployed across 13 countries, have improved loan approvals and reduced credit loss by integrating remote sensing and financial data.

Key Takeaways:

• AI can bridge the gap in agri-finance, which currently meets only one-third of farmers' credit needs.
• Enhanced data models can support scale and risk reduction.

C. Climate-Resilient Farming

Presenter: Praveen Pankajakshan, VP of Data Science and AI, Cropin

Cropin presented geospatial AI tools for dynamic land mapping and crop forecasting, focusing on climate-resilience. Their open-source language model “Aksara” delivers climate-smart advisories tailored for the Global South.

Key Takeaways:

• AI models can effectively monitor climate shifts and inform adaptation strategies.
• Collaborative data validation with governments strengthens model accuracy.

Keynote Reflections

Rajiv Chawla, Chief Knowledge Officer, Ministry of Agriculture, outlined the vision of AgriStack—a national digital agriculture initiative to consolidate farmer, land, and crop data through a consent-based, interoperable framework.

Inma Martinez, Chair of GPAI’s Multi-stakeholder Expert Group, stressed the importance of robust data governance, inclusivity in tech design, and cooperation with international bodies to develop shared AI tools and standards

Panel Discussion Highlights

Moderated by IndiaAI representatives, the panel addressed:

• Opportunities for integrating AI into national agri-infrastructure.
• The need for skilling programs in AI and agriculture.
• Challenges of fragmented agri-data ecosystems.
• Social equity and inclusivity in technology roll-out.

Panelists emphasised the role of public-private partnerships and academic collaboration in developing scalable, farmer-centric AI solutions.

Actionable Outcomes and Recommendations

1. Agri Data Governance and Interoperability

• Establish a national agri-data exchange with clear privacy norms and sharing mechanisms.
• Develop standard taxonomies and ontologies for agri data (e.g., crop IDs, soil types).

2. Research and Capacity Building

• Launch multidisciplinary programs combining agri sciences and digital technologies.
• Build AI capabilities among agri-university students and extension officers.

3. International Collaboration

• Enable cross-country case study sharing and research pilots via GPAI.
• Create sandbox environments for start-ups to co-develop and test AI tools.

4. Farmer-Centric Innovation

• Invest in tools with offline capability and multilingual access.
• Ensure inclusivity for marginalised groups including women and landless workers.

5. Dietary and Environmental Adaptation

• Use AI to support shifts toward high-protein, plant-based diets.
• Support sustainable practices like regenerative and natural farming.

Conclusion

The Sustainable Agriculture session at the IndiaAI & GPAI Summit 2024 affirmed India’s leadership in using AI to address agricultural challenges while promoting equity, climate resilience, and collaboration. The session provided a platform to align national innovation efforts with global AI-for-good objectives, and it laid the groundwork for deeper engagement across the GPAI ecosystem in the run-up to 2025.

This event output report will be added to the Knowledge Exchange section of The Agri Collaboratory website to continue fostering transparent, cross-sector learning.