UAE sets global benchmark with AI certification in agriculture
ADAFSA leads the way in AI-driven agriculture with ISO 42001:2023 certification
Abu Dhabi: The Abu Dhabi Agriculture and Food Safety Authority (ADAFSA) has become the first entity in the global agriculture and food safety sector to receive the ISO 42001:2023 certification for Artificial Intelligence Management Systems. This also marks the first time a UAE government body has achieved this milestone. The certification solidifies the UAE's role as a leader in developing and adopting international standards and best practices, particularly in responsible AI.
Omar Sultan Al Olama, Minister of State for Artificial Intelligence, Digital Economy, and Remote Work Applications, highlighted that this achievement is another step in the UAE's efforts to leverage AI to boost the efficiency of key sectors, including agriculture and food security. He commended ADAFSA for its contribution to digital transformation and food security, praising the leadership’s commitment to building a sustainable and innovative future.
Dr. Tariq Al Ameri, Acting Director General of ADAFSA, noted that the certification aligns with both Abu Dhabi’s vision and the UAE AI Strategy 2031. He explained that this achievement will support ADAFSA’s mission to promote agricultural sustainability, food security, and digital transformation through advanced AI solutions.
AI's role in modern agriculture
Artificial intelligence is rapidly transforming the agriculture industry, enhancing productivity and efficiency while reducing costs and risks. AI applications in this sector are diverse and powerful.
Precision agriculture: Using data from sensors and drones, AI determines the exact amount of water, fertilisers, and pesticides needed for crops. This approach minimises waste and maximizes production efficiency.
Irrigation management: Smart irrigation systems use AI to calculate the optimal water requirements for specific agricultural zones, factoring in the type of crop, soil condition, and weather.
AI is making a significant impact across the entire food and agricultural production chain. The technology is used to:
Develop climate-resilient rice varieties.
Provide detailed soil data.
Guide drones for precise application of pesticides and fertilizers.
Sort, inspect, and grade crops.
7 key uses of AI in agriculture
Monitoring crop and soil health: Drones capture and analyze aerial imagery to assess the condition and growth stages of crops and soil.
Pest and disease detection: AI algorithms can identify pests and diseases early, enabling timely interventions to minimize crop damage.
Livestock health monitoring: Sensors track livestock health, helping farmers detect early signs of illness and take preventive measures.
Smart pesticide spraying: AI-powered sprayers use computer vision to apply pesticides only where needed, reducing chemical overuse.
Automated weed removal: Robots identify and remove weeds from fields, lessening the need for herbicides and manual labor.
Aerial surveying and imaging: Drones and remote sensing systems create detailed maps of fields, showing crop health, soil moisture, and other critical growth factors.
Product sorting and grading: AI algorithms classify and sort agricultural products by quality and size, reducing waste and ensuring premium products reach the market.
This integration of AI, along with technologies like automation and the Internet of Things (IoT), is part of a broader movement known as smart farming or precision agriculture. The goal is to use data-driven technologies to optimise agricultural productivity and sustainability.
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