AI in agriculture needs strong policy backing to deliver at scale: Primus partners

New Delhi: India's agriculture sector stands at a critical juncture where Artificial Intelligence (AI) can help address persistent challenges ranging from climate risks to low farm productivity, but achieving meaningful impact will require targeted policy interventions, according to a report by consulting firm Primus Partners.

The report argues that while AI technologies have demonstrated significant potential in crop monitoring, precision farming, weather forecasting and market intelligence, adoption across Indian agriculture remains uneven and limited, particularly among smallholder farmers who constitute the majority of the country's farming community.

AI's Promise Beyond Precision Farming

AI is increasingly being viewed as a transformative tool capable of improving decision-making across the agricultural value chain. From predicting pest attacks and crop diseases to optimizing irrigation schedules and input application, AI-based systems can help farmers reduce costs while improving productivity.

"Artificial Intelligence has the potential to become a force multiplier for Indian agriculture by enabling data-driven farming practices, improving resource-use efficiency and strengthening climate resilience," the report noted.

Experts believe AI applications can also support policymakers through better crop forecasting, acreage estimation and food supply assessments, helping governments respond more effectively to production and market fluctuations.

Adoption Barriers Remain Significant

Despite growing interest from agritech startups, research institutions and technology providers, several structural barriers continue to slow adoption.

The report identifies limited digital infrastructure in rural areas, fragmented agricultural data, inadequate digital literacy and affordability concerns as key constraints.

India generates large volumes of agricultural data through government schemes, satellite observations, weather systems and research institutions. However, the absence of standardized, interoperable and easily accessible datasets often limits the development and deployment of scalable AI solutions.

"Data remains the foundation of any successful AI ecosystem. Without reliable, high-quality and interoperable agricultural datasets, the full benefits of AI cannot be realized," the report said.

Building a Digital Public Infrastructure for Agriculture

A central recommendation of the report is the creation of stronger digital public infrastructure to support AI-enabled agriculture.

The firm has called for enhanced rural broadband connectivity, improved access to digital services and the development of robust agricultural data platforms that can facilitate secure data sharing among stakeholders.

According to the report, integrating AI applications with initiatives such as the Digital Agriculture Mission can accelerate innovation while ensuring that technology solutions remain aligned with national agricultural priorities.

Industry observers note that India's experience with digital public infrastructure in sectors such as finance demonstrates the potential of large-scale digital ecosystems to drive inclusion and innovation.

Focus on Farmer-Centric Solutions

The report emphasizes that technology adoption will ultimately depend on its relevance and accessibility to farmers.

AI tools must be designed to deliver localized advisories that account for region-specific conditions, crop patterns and weather variability. Delivering recommendations in local languages and through user-friendly interfaces will be essential for wider acceptance.

The report also stresses the importance of strengthening extension systems to bridge the gap between technological innovation and on-ground implementation.

"Farmer awareness and capacity building should be treated as core components of any AI adoption strategy rather than as supplementary activities," it noted.

Regulatory Clarity Needed

As AI applications become more widespread, the report highlights the need for a clear regulatory framework governing data ownership, privacy, consent and accountability.

A transparent policy environment, it argues, would help build trust among farmers while encouraging greater investment from private-sector participants.

Experts believe that balancing innovation with safeguards will be crucial as AI systems increasingly influence farm-level decisions and agricultural markets.

Public-Private Collaboration Key to Scale

The report also advocates stronger collaboration between government agencies, research institutions, startups and private enterprises.

Targeted incentives, pilot projects and innovation-focused funding mechanisms could accelerate the development of AI solutions tailored to India's diverse agricultural landscape.

Agritech startups have already begun deploying AI-driven tools for crop diagnostics, farm advisory services, yield prediction and supply-chain management. However, scaling these solutions nationally will require coordinated support from both policymakers and industry stakeholders.

The Road Ahead

With climate change, resource constraints and evolving food security concerns placing increasing pressure on agriculture, AI is emerging as a strategic tool for the sector's future.

The report concludes that India possesses many of the building blocks needed to become a global leader in AI-driven agriculture. However, realizing that potential will depend on creating a supportive ecosystem built on digital infrastructure, data governance, farmer inclusion and collaborative innovation.

As policymakers intensify efforts to modernize agriculture, the debate is shifting from whether AI should be adopted to how quickly it can be deployed at scale and made accessible to millions of farmers across the country.