UN Agencies, India Call to Scale AI for Food & Climate Action

Dr V. Anantha Nageswaran, Chief Economic Advisor to the Government of India, highlighted the need for robust governance frameworks to ensure AI delivers public value.

Senior leaders from three Rome-based United Nations agencies joined India’s Chief Economic Advisor at the India AI Impact Summit 2026 to chart a path for transforming artificial intelligence from small pilot projects into scalable, sustainable solutions tackling food insecurity, climate shocks and humanitarian crises.

The 55-minute high-level session — titled “From Evidence to Scale: Testing, Financing and Operationalizing AI for Development and Humanitarian Action” — was jointly organised by the International Fund for Agricultural Development (IFAD), the Food and Agriculture Organization of the United Nations (FAO), and the World Food Programme (WFP).

The discussion focused on a central challenge confronting the development sector: how to move beyond experimentation and embed AI into national systems, governance frameworks and operational delivery at scale.

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From Pilot Projects to Systemic Change

Artificial intelligence is increasingly being deployed across agriculture, disaster response and climate adaptation. Yet many initiatives remain confined to pilot phases, lacking the financing, policy backing or digital infrastructure required for national impact.

Dr V. Anantha Nageswaran, Chief Economic Advisor to the Government of India, highlighted the need for robust governance frameworks to ensure AI delivers public value.

“The Government of India recognizes the critical importance of shaping effective policy to both regulate artificial intelligence and enable its adoption across the public sector,” he said.

“Robust frameworks are essential to harness AI's transformative potential for public good while ensuring responsible governance.”

India, home to one of the world’s largest digital public infrastructure ecosystems, is increasingly positioning itself as a global leader in responsible AI deployment.

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Financing the Foundations: Infrastructure and Inclusion

Brenda Gunde, Global Lead for ICT4D at IFAD, stressed that scaling AI in agriculture requires more than algorithms.

“As AI moves from pilot projects to a central driver of agricultural transformation, deliberate investment is essential,” she said.

Countries, she argued, must finance:

• Digital public infrastructure

• Governance systems

• Institutional capacity

• Inclusive access for smallholder farmers

“Investment must be inclusive and designed to reach smallholder farmers and rural communities,” Gunde added.

With more than 500 million smallholder farmers globally producing a significant share of the world’s food, inclusive AI deployment is seen as critical to strengthening food systems and rural livelihoods.

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Operationalizing AI in Humanitarian Response

At WFP, AI is already being deployed at operational scale. Chief Data Officer Magan Naidoo described how agentic AI systems and the organisation’s DEEP platform are reshaping humanitarian delivery.

“At the World Food Programme, we are harnessing the power of agentic AI and our DEEP platform to operationalize artificial intelligence for humanitarian response at scale,” Naidoo said.

Applications include:

• Automating complex logistics decisions

• Improving food assistance targeting

• Integrating real-time field data

• Enhancing coordination across agencies

These tools enable faster, evidence-based responses in crises affecting millions of vulnerable people worldwide.

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AI in Evaluation and Accountability

Indran Naidoo, Director of the Independent Office of Evaluation at IFAD, highlighted how AI is transforming not only operations but also oversight.

“Artificial intelligence is transforming how we collect and evaluate evidence,” he said.

AI-driven analytics are improving the ability to:

• Frame evaluation questions

• Structure and interrogate data

• Assess uncertainty

• Measure impact of AI-driven projects themselves

This focus on evidence ensures that scaling efforts are grounded in measurable outcomes.

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FAO’s Evidence-First Innovation Model

Vincent Martin, Director of FAO’s Office of Innovation, emphasised that AI must be problem-led, rigorously tested and responsibly governed.

“At FAO, we never begin with technology; we begin with the problem,” he said.

He cited LUMINA, an AI project incubated through FAO’s ELEVATE programme in South Sudan, as a model for responsible innovation. LUMINA uses AI to better understand and respond to acute child malnutrition in one of the world’s most fragile contexts.

The project was:

• Prototyped and validated using local data

• Strengthened through FAO’s innovation bootcamp

• Designed with a pathway toward scalable deployment

“This is responsible AI in practice—evidence-driven, user-centered, and backed by a pathway to scale,” Martin said.

“Responsible and ethical AI is not about hype. It is about proof, governance, and sustainable financing.”

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A Credible Voice on Responsible AI for Development

Collectively, the Rome-Based Agencies bring decades of experience in rural operations, climate resilience, digital public goods and partnerships in emerging economies.

Their joint message at the Summit was clear: scaling AI for development requires coordinated policy, strong governance, sustainable financing and alignment with national digital ecosystems.

As climate change intensifies, food insecurity rises, and humanitarian needs expand globally, leaders at the Summit argued that AI — if responsibly deployed — can move from isolated pilots to transformative, system-wide solutions.