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AI's application in developing countries hinges on statistical methods to identify patterns and propose solutions. The fragmented political and economic environments complicate the effective use of AI, as decision-makers often lack accountability. Corruption and bureaucratic structures further hinder the establishment of efficient data pipelines necessary for AI adoption.
Data fragmentation poses a significant challenge, as companies often possess valuable data but lack the means to utilize it effectively. The case of Brazil illustrates how disorganized data within young associations limits progress. Despite these hurdles, innovative approaches and community cooperation can lead to impactful solutions, particularly in agricultural sectors.
• AI can solve significant problems through statistical methods and innovation.
• Data fragmentation in developing countries limits effective AI application.
Data pipelines are essential for collecting and processing data to generate AI solutions.
Data fragmentation occurs when valuable data is dispersed and uncoordinated across organizations.
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