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Structural challenges continue to limit AI adoption in agriculture
AI adoption in agriculture remains constrained by cost, data gaps, and infrastructure limitations, slowing its ability to deliver scalable benefits to farmers.
Despite its potential, artificial intelligence adoption in agriculture faces significant challenges, including high costs, limited data availability, and lack of digital infrastructure. Farmers often struggle with access to reliable datasets and technical expertise needed to deploy AI solutions effectively. These constraints highlight the need for supportive policy frameworks, education, and affordable technology to make AI practical for the agriculture sector.