AI in Agriculture

Below is the criteria for Global AI Awards in Agriculture category:

1. Design (25%)

• Quality of solution design in addressing agricultural needs (crop management, soil health, irrigation, livestock care, etc.).
• Integration of AI into existing farming systems and practices without disrupting workflows.
• Accessibility for diverse users (smallholder farmers, large agribusinesses, cooperatives).
• Sustainability-focused design (energy-efficient, environmentally conscious).

2. Impact (35%)

• Measurable improvements in productivity, yield, or resource efficiency.
• Demonstrated contribution to food security, climate resilience, or sustainable farming.
• Economic impact for farmers and agricultural communities (cost reduction, profitability).
• Broader positive outcomes (reduced chemical use, improved soil/water management, biodiversity preservation).

3. Creativity (25%)

• Innovative and original applications of AI in solving agricultural challenges.
• New approaches to crop monitoring, pest management, predictive analytics, or precision farming.
• AI-driven insights that enable better decision-making in agriculture.
• Unique solutions that stand out from traditional agri-tech methods.

4. Ease of Use (15%)

• User-friendly interfaces for farmers with varying levels of digital literacy.
• Accessibility on common devices (e.g., mobile phones in rural areas).
• Low barriers to adoption (affordable, easy to implement, requires minimal technical expertise).
• Availability of training, support, or multilingual features for different regions.