India AI Impact Summit 2026

agri-ai-advancing-responsible-ai-for-agriculture

7 min read

TRACK:Economic Growth and Social Good
SPEAKERS
  • Dr Mukesh Kestwal, IIT Ropar – Technology & Innovation Foundation
  • Dr. Gal Zohar, Israeli Public Employment Service
  • Dr. Pushpendra P. Singh, ANNAM.AI and iHub - AWaDH
  • Dr. Radhika Trikha, IIT Ropar – Technology & Innovation Foundation
  • Mr. Mayuresh Raut, Seafund
  • Ms. Maya Serman, Embassy of Israel in India
  • Ms. Nemesisa Ujjain, The Circle FC
  • Ms. Sarit Felber, Israeli Ministry of Justice
  • Ms. Urmi Tat, Salesforce
  • Prof. Dov Greenbaum, Zvi Meitar Institute
  • Prof. Victor Alchanatis, Institute of Agricultural and Biosystems Engineering
SESSION OVERVIEW

This session brings together leading stakeholders from governments, civil society and academia to advance responsible AI for agriculture. The session features inaugural addresses, keynote insights and cross-border panels on scaling AI for public good. With participation from policymakers, researchers, investors and innovators, the program highlights international collaboration, startup recognition and actionable dialogue to strengthen inclusive, impact-driven AI ecosystems for sustainable agricultural development.

VIDEO RECORDING

Agri AI: Advancing Responsible AI for Agriculture

Abstract

The session opened with IIT Ropar’s Dr Mukesh Kestwal outlining the home‑grown Agri‑LLM platform and a low‑cost, high‑accuracy weather‑station network to empower Indian farmers with real‑time agronomic data. This was followed by Dr Gal Zohar’s presentation on the Indo‑Israeli partnership, highlighting the N‑DRIP irrigation system and nine demonstration plots across Punjab, Haryana and Maharashtra. Professors Dov Greenbaum and Victor Alchanatis broadened the conversation to labour‑force automation, AI‑driven biotech governance, and the ethical challenges of genome‑refactoring. The later half of the session shifted to an investment round‑table moderated by Ms Maya Serman, where representatives from Salesforce, The Circle FC, and Seafund discussed trust, capital deployment, and policy frameworks required to scale responsible AI solutions for the country’s half‑billion‑strong farming community. The session closed with a joint Indian‑Israeli pledge to place farmers at the centre of AI‑driven transformation.

Detailed Summary

Speaker: Dr Mukesh Kestwal (IIT Ropar)

  • Agri‑LLM Initiative – IIT Ropar is developing a large‑language model, Agri‑LLM, designed to answer farmers’ queries in vernacular languages and provide context‑aware agronomic advice.
  • End‑to‑End Hardware Production – All electronics for the system—including sensors, micro‑controllers, and communication modules—are manufactured in‑house at IIT Ropar; no third‑party assembly is used.
  • Weather‑Station Network
    • Deployed across Uttar Pradesh, Punjab, Haryana, Andhra Pradesh, Jammu & Kashmir, and other states.
    • Accuracy: 99 % (validated by the India Meteorological Department, Pune).
    • Cost: ~ ₹15,000 per station – positioned as an affordable, scalable solution.
    • Data Capture: Rainfall, solar radiation, wind speed, soil temperature, and soil humidity—providing a “multi‑dimensional” micro‑climate profile for each gram‑panchayat.
  • Field Partnerships – Direct engagement with Farmer Producer Organizations (FPOs) in Punjab, Andhra Pradesh, and Uttar Pradesh; progressive farmer groups are already testing the platform.
  • Vision – High‑resolution data → responsible AI models → increased productivity, pest‑control, and crop‑damage mitigation via farmer‑facing mobile apps.
  • Strategic Note – Emphasis on the “data‑is‑oil” analogy, referencing an Indian minister’s remark, and the intention to leverage India’s massive agricultural data trove for responsible AI development.

2. Indo‑Israeli Collaboration – From Demonstration Plots to Nationwide Roll‑Out

Speaker: Dr Gal Zohar (Israeli Public Employment Service)

  • Policy Context – The Indian government has invested USD 3–4 million per Center of Excellence across 34 locations, equipping them with modern irrigation, subsidised seed nurseries, and now AI‑enabled decision tools.
  • N‑DRIP Technology
    • Low‑energy, gravity‑driven irrigation chips that require near‑zero pressure.
    • Cost: ≈ USD 2,000 per system, with multi‑year lifespan.
    • Integrated soil‑sensor suite streams data to a central AI hub that offers planting, fertilisation, and harvesting recommendations.
  • Pilot Programme – Nine demonstration plots in Punjab, Haryana, and Maharashtra (including a recent field near Agra, Uttar Pradesh).
  • Scaling Outlook – Pending evaluation by the Ministry of Agriculture, the expectation is nation‑wide adoption following successful pilot outcomes.
  • Joint Research – Ongoing collaboration with IIT Ropar and other Indian research institutes; mutual goal of “AI for every farmer” via mobile‑first knowledge delivery.

3. Labour Shortage & AI Democratisation – The Israeli Perspective

Speaker: Prof Dov Greenbaum (Zvi Meitar Institute)

  • Current Labour Crisis – Israel faces a severe shortage of agricultural workers; traditional solutions (higher wages, migrant labour) are unsustainable.
  • Automation & Gen‑AI – Emphasis on generative‑AI and large‑language models to enable any individual to become a “citizen developer” of agricultural applications.
  • Skill Development – Israeli Employment Service programmes pair employers with skill‑training on AI tools, ranging from basic usage to custom app development.
  • Strategic Benefit – Democratising AI is positioned as a quantum leap in productivity, allowing small‑holder farmers to co‑create solutions rather than remain passive recipients.

4. Governance of AI‑Driven Genome Refactoring – Emerging Risks & Policy Gaps

Speaker: Prof Victor Alchanatis (Institute of Agricultural and Biosystems Engineering)

  • Scientific Background – DNA comprises four nucleotides forming 64 codons; redundancy allows genome refactoring (editing codons without altering amino‑acid output).
  • AI‑Enabled Bio‑Engineering – AI can optimise codon usage, insert non‑organic components, and generate novel proteins, opening pathways for high‑yield, climate‑resilient crops.
  • Governance Challenges
    • Intellectual‑property & patent ownership of AI‑generated genetic constructs.
    • Definition – Whether such crops count as GMOs under existing regulations.
    • Weaponisation – Risk of malicious actors creating undetectable, engineered crops.
    • Regulatory Pace – AI’s rapid advancement outstrips current biosafety frameworks.
  • Bio‑Hackers – Lowered barriers enable garage‑level genome editing, raising questions about monitoring, licensing, and liability.
  • Consolidation Concerns – Potential for large corporations to monopolise biotechnological outputs, threatening farmer autonomy.

5. Panel Transition – Setting the Stage for Investment & Scaling

  • Moderator: Ms Maya Serman (Embassy of Israel) introduced the next segment, framing it as a discussion on bridging nascent AI ideas to large‑scale public‑good impact.

  • IIT Ropar Investment Snapshot (presented by Dr Mukesh Kestwal):

    • Portfolio: > 250 agri‑tech startups.
    • Funding Provided: ₹ 17 crore over 2.5 years.
    • External VC Capital Raised by Portfolio: ₹ 120 crore.
    • Ecosystem Support: Collaboration with ANNAM.AI, iHub‑AWaDH, Startup India, and various Ministries.

6. Responsible AI & Trust – Salesforce Perspective

Speaker: Ms Urmi Tat (Salesforce)

  • AI Agents for Public Good – Salesforce is experimenting with AI‑driven agents in healthcare, finance, and other sensitive domains.
  • Core Challenge – Institutional Trust
    • Data Security & Privacy – Farmers must feel confident that their farm data is protected.
    • Explainability – Clear, understandable rationale behind AI recommendations.
  • Adoption Barriers – Need for education, ecosystem support, and long‑term reliability to move beyond pilot projects.

7. Venture‑Capital View – The Circle FC (Cross‑Border Funding)

Speaker: Ms Nemesisa Ujjain (The Circle FC)

  • Market Size: Agriculture employs ≈ 50 % of India’s workforce but contributes < 15 % to GDP.
  • Startup Landscape: Out of ≈ 200 k Indian startups, ≈ 1.5‑2 k focus on agri‑tech.
  • Investment Thesis:
    • Cross‑border programmes (e.g., Israel‑India corridors) accelerate market entry and scaling.
    • Pilot‑ready environments and government sandboxes lower risk for investors.
  • Strategic Advantage – India’s digital public infrastructure (DPIs) offers a fertile testing ground for AI solutions that can later be exported regionally.

8. Deep‑Tech Funding – Seafund’s Outlook

Speaker: Mr Mayuresh Raut (Seafund)

  • India’s AI Mission – A USD 12.5 billion program akin to DARPA/NSF in the U.S., targeting semiconductors, quantum, defense, and AI.
  • Funding Gap – Traditional VC capital is insufficient for lab‑stage, high‑risk agritech that requires longer development cycles.
  • Dual‑Use Opportunities – Some agri‑tech startups leverage defence‑grade sensors or satellite imagery, unlocking additional revenue streams.
  • Barriers to Adoption:
    • Fragmented land holdings and data silos impede model generalisation.
    • Cost‑sensitivity of Indian farmers demands sub‑₹ 1,000 cost‑per‑service solutions.

9. Closing Remarks – Joint Vision for Farmers

  • Prof Ajeev Ahuja (Chief Patron) reiterated the importance of co‑creation, capacity‑building, and explainability.
  • Consensus among panelists: trust, local intermediaries, post‑deployment support, and transparent AI decision pathways are essential for farmer uptake.

10. Ceremonial Closure & Group Photo

  • The session concluded with formal felicitations of the chief patron and key speakers, followed by a group photograph of Indian and Israeli participants.

Key Takeaways

  • Integrated Data Infrastructure: IIT Ropar’s low‑cost, 99 % accurate weather‑station network (≈ ₹15k per unit) is the backbone for responsible Agri‑AI models.
  • Indo‑Israeli Pilot Success: Nine N‑DRIP demonstration plots showcase a gravity‑driven, energy‑free irrigation system costing ≈ USD 2k, with AI‑driven soil analytics, poised for national scaling.
  • AI Democratization: Israel’s labor shortage is driving a citizen‑developer model where farmers can build their own AI tools, leveraging generative models and low‑code platforms.
  • Governance Gaps: AI‑enabled genome refactoring raises IP, biosafety, and weaponisation concerns; current regulatory frameworks lag behind technological capabilities.
  • Trust as a Pillar: Salesforce stresses that data security, explainability, and sustained support are non‑negotiable for farmer adoption of AI agents.
  • Funding Landscape:
    • IIT Ropar’s agri‑tech portfolio (250+ startups, ₹ 17 cr internal, ₹ 120 cr external) shows active capital deployment.
    • The USD 12.5 billion Indian AI mission provides a DARPA‑style research engine for deep‑tech, including agri‑AI.
    • The Circle FC and Seafund highlight cross‑border corridors (India‑Israel, India‑ASEAN) and dual‑use business models as growth levers.
  • Barriers to Scale: Fragmented land holdings, inconsistent data standards, and cost sensitivity (sub‑₹ 1,000 per service) remain the biggest hurdles.
  • Strategic Recommendations:
    1. Co‑creation with farmer‑level intermediaries to embed trust.
    2. Explainable AI that surfaces the decision logic to end‑users.
    3. Standardised data formats and public data repositories (e.g., AI‑KOSH) to enable model generalisation.
    4. Regulatory foresight for biotech AI to pre‑empt misuse.
  • Vision Statement: The joint India‑Israel agenda aims to place farmers at the centre of AI‑driven transformation, guaranteeing that advanced technologies are affordable, trustworthy, and locally relevant.

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