Artificial Intelligence a key in realizing India’s Agri growth

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New Delhi: Artificial Intelligence (AI) will be the focal point in realizing India’s agriculture growth revealed a new report from India’s top IT trade body Nasscom.

The National Association of Software and Services Companies (NASSCOM), in association with Ernst & Young (EY) has unveiled the findings of India’s Agritech sector 2021, in its report titled, Leveraging AI to maximize India’s agriculture output.

With increased government support, growing AgriTech providers, burgeoning startup ecosystem and rising Artificial Intelligence (AI) adoption among the rural farming population, a strong transformation impetus is underway.

Data consolidation (both at macro and real-time farm-level), lack of infrastructure awareness in data processing and its availability have been some of the key challenges faced by the sector today.

In addition to this, lack of awareness on agricultural inputs specific to the produce, access to quality seeds, lack of adequate mechanization and irrigation infrastructure, scarcity of farmer capital, frequent disease outbreak, and Inadequate storage facilities are the other value chain challenges faced by the sector.

AI has the potential to play a key role in relieving the sector from most of its stressful input conditions, catalyzing a shift towards data-driven farming. Leveraging macro as well as farm-level data collected through sensors will help maximize yields and optimize the use of available resources.

Several AI-led use cases, such as precision agriculture and farm management, agricultural robots, automated weeding, crop quality and readiness identification, pest prediction and prevention, livestock monitoring and management, crop yield estimation, etc can solve improving farm productivity and empower farmers in improving operational efficiency through unified supply chains and intelligent farm operations.
 
According to Nasscom President Debjani Ghosh, the Indian agriculture sector can utilize the potential of AI’s transformative capabilities through effective data practices. The Netherlands is a stellar example of effective AI adoption in agriculture. With just a small arable land the country has become the world’s 2nd largest exporter of agricultural products by value leveraging technology and AI.

“For India to realize the full potential of AI a coalition of government, industries, and start-ups in providing necessary infrastructure and policy support, enabling AI innovation across sectors, and mentoring and providing financial support to startups is imperative,” said Ghosh.

The Government of India is playing a leading role in making technology adoption in the sector, an imperative. Both government and private players are focusing on driving better farm output through mechanization and digitization efforts paving the way for tech-enabled solutions.

Several AI-led startups are developing innovative Artificial Intelligence led solutions, targeting specific challenges in the value chain. Precision farming, crop disease management and produce sorting and grading are top focus areas for startups.

Leading technology companies are entering into multi-year partnerships with agribusiness companies and Agritech startups for solution developments, leading investments into research programs, and creating incubator programs dedicated to startups.

Government entities are partnering with technology companies and agritech startups for driving AI initiatives, providing necessary support, mentorship and intellectual property commercialization to startups through various incubator programs.

To gauge the evolution of agricultural enterprises, and where they are in the AI journey, NASSCOM had conducted a survey targeting CXOs working with Indian enterprises, GCCs and large startups.

As per the survey findings, with ‘Trust in AI’ as the key lynchpin, revenue growth, innovation and farmer/end-customer experience are priority areas for AI in agriculture enterprises. Additionally, companies are looking at a dedicated AI strategy and budget as a key imperative to scale AI initiatives enterprise-wide post-COVID-19.

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