in terms of food accessibility it can work well,

I believe Sharma is asking if AI can save the planet's natural environments while providing enough food for an ever growing population. It's possible, but unlikely. If the AI entity could be given dictator status over the world, yes. But the chances of that are very slim. The non dictator version could offer some plans, but individual humans would have their own agendas. Individual farmers might use AI on their own farms to improve food production, and, as shown with recycling, a sense of guilt might be developed when expanding the farm into the surrounding forest. South America strikes me as a place that could use some big picture, long-term planning, and AI might help.

No, AI cannot "beat" sustainable agriculture in the near future. In fact, AI can be a valuable tool in advancing sustainable agriculture practices and addressing the challenges faced by the agricultural industry. Here's how AI can contribute to sustainable agriculture:

1. Precision Farming: AI technologies such as machine learning, drones, and sensors can gather data about soil composition, weather patterns, crop health, and nutrient levels. This data can be used to optimize irrigation, fertilization, and pesticide use, reducing resource waste and minimizing the environmental impact.

2. Crop Monitoring and Disease Detection: AI can help monitor crops by analyzing images or data collected from sensors to detect early signs of plant diseases, pests, or nutrient deficiencies. By identifying issues early, farmers can take targeted actions, reducing the need for excessive pesticide use and preventing crop losses.

3. Smart Irrigation Systems: AI can optimize irrigation systems by analyzing real-time data, including soil moisture levels, weather conditions, and plant requirements. By using AI-powered algorithms, farmers can minimize water usage, conserve resources, and maintain optimal soil moisture for crops.

4. Crop Yield Prediction: AI can analyze historical and real-time data, including weather patterns, soil conditions, and crop characteristics, to predict crop yields. Accurate yield predictions help farmers optimize their harvesting and logistics processes, reduce food waste, and plan for market demand.

5. Sustainable Pest Management: AI can aid in developing and implementing sustainable pest management strategies. By analyzing data on pest behavior, crop growth patterns, and environmental factors, AI can help farmers adopt integrated pest management techniques, reducing the reliance on chemical pesticides and promoting eco-friendly alternatives.

6. Supply Chain Optimization: AI can optimize the agricultural supply chain by analyzing data on transportation routes, storage conditions, and market demand. By optimizing logistics, farmers can reduce food waste, minimize carbon emissions, and improve overall efficiency.

It's important to note that while AI can enhance sustainable agriculture practices, it should be seen as a tool to support human decision-making rather than a replacement for sustainable farming practices. The collaboration between AI and sustainable agriculture practices can lead to more efficient, environmentally friendly, and productive agricultural systems.