Agriculture is ready for AI, but its data isn’t

The potential of artificial intelligence in agriculture is huge, with promising use cases that could help farmers navigate challenges like volatile fertilizer costs and unpredictable weather. However, industry leaders need to address the current lack of quality data before fully committing to AI solutions. Without robust, reliable data, AI models can't deliver the accuracy needed for effective decision-making, which could undermine the technology's potential benefits. This gap in data infrastructure could slow the integration of AI in farming, despite its clear advantages in optimizing crop yields and resource use.