AI in AG
(AI) can contribute to achieving these goals through several mechanisms:
Predictive Analytics
AI can analyse historical purchase data to forecast future buying patterns.This allows us to accurately predict volume commitments for the future and plan production schedules accordingly.
Supply Chain Optimisation
AI can be used to streamline supply chains by determining the optimal distribution of resources. It can analyse regional supply and demand patterns, helping to balance production volumes across different areas.
Anomaly Detection
AI can identify unusual patterns or outliers in purchasing data. This can provide early warnings of potential disruptions or changes in buying behaviour, enabling proactive adjustments to production plans.
Demand Forecasting
AI can model consumer behaviour and market trends, leading to more accurate demand forecasting. This ensures that production aligns with demand, reducing waste and improving the efficiency of the supply chain.
Sustainability Metrics
AI can track and calculate the environmental footprint of different farming practices. This can help incentivize sustainable practices and contribute to the goal of a more sustainable food system.
These AI-driven outcomes can collectively lead to a more efficient, sustainable, and equitable food system, aligning with Share Farm's overarching goals.