Future Farming in India A Playbook for Scaling Artificial Intelligence in Agriculture 2025

Contents Foreword 3 Executive summary 4 Introduction 7 The potential of AI in agriculture 8 The need for an AI playbook 9 1 Understanding stakeholders’ AI aspirations at first hand 10 2 Exploring promising AI applications for agriculture 14 2.1 Potential use cases 15 2.1.1 AI-enabled crop planning 16 2.1.2 AI-enabled rapid soil-health analysis 18 2.1.3 AI-enabled pest prediction and control 21 2.1.4 AI-enabled smart marketplaces 24 2.2 Lessons learned from AI use cases 27 3 Framework for developing AI ecosystems 28 3.1 Introducing the IMPACT AI framework 29 3.2 Objectives of the framework 29 3.3 Principles of the IMPACT AI framework 30 3.4 Pillars of the framework 30 Pillar 1 Enable 32 Pillar 2 Create 33 Pillar 3 Deliver 34 Conclusion and call to action 35 Next steps – models and templates 37 Appendix 1: The Agriculture Expert Group 39 Appendix 2: AI for India 2030 Advisory Council 41 Appendix 3: The stakeholders matrix 44 Appendix 4: A repository of AI use cases in agriculture 45 Appendix 5: An assessment of critical datasets for AI in agriculture 50 Contributors 52 Endnotes 53Images: Adobe Stock Generated with AI, Getty Disclaimer This document is published by the World Economic Forum as a contribution to a project, insight area or interaction. The findings, interpretations and conclusions expressed herein are a result of a collaborative process facilitated and endorsed by the World Economic Forum but whose results do not necessarily represent the views of the World Economic Forum, nor the entirety of its Members, Partners or other stakeholders. © 2025 World Economic Forum. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, including photocopying and recording, or by any information storage and retrieval system. Future Farming in India 2