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AI-driven process redesign

This research aims to transform how organisations improve business processes by integrating artificial intelligence with real-time data. Existing process redesign approaches are often static, retrospective, and reliant on manual analysis. While process mining is commonly used to extract insights from historical data, these methods rarely incorporate AI models to support continuous, real-time process adaptation. As a result, they fall short of enabling intelligent, self-adaptive process management.This research addresses these limitations by proposing an AI-assisted, self-adaptive framework that combines historical and …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems

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