| AI Use Case | Description |
| Managing risk | Farmers can use forecasting and predictive analytics to reduce errors in business processes and minimize the risk of crop failures. |
| Breeding seeds | By collecting data on plant growth, AI can help produce crops that are less prone to disease and better adapted to weather conditions. |
| Monitoring soil health | AI systems can conduct chemical soil analyses and provide accurate estimates of missing nutrients. |
| Protecting crops | AI can monitor the state of plants to spot and even predict diseases, identify and remove weeds, and recommend effective treatment of pests. |
| Feeding crops | AI is useful for identifying optimal irrigation patterns and nutrient application times and predicting the optimal mix of agronomic products. |
| Harvesting | With the help of AI, it’s possible to automate harvesting and even predict the best time for it. |