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This study explores the development of strategic roadmaps for advancing sustainable and AI-integrated manufacturing systems in the context of rapid digital transformation and increasing sustainability pressures. The purpose of the research was to understand how artificial intelligence can be systematically aligned with sustainability goals through structured planning approaches in manufacturing environments. A qualitative research design was employed using document-based analysis of relevant scholarly literature, and thematic analysis was applied to identify key patterns and relationships across technological, organizational, and sustainability dimensions. The findings reveal that AI integration significantly enhances manufacturing performance through predictive maintenance, supply chain optimization, energy efficiency, and real-time decision-making. However, the effectiveness of these outcomes depends on the presence of strong digital infrastructure, workforce readiness, ethical governance, and coherent strategic roadmap design. The study also found that sustainability outcomes are maximized when AI systems are embedded within circular economy models and long-term strategic planning frameworks. The implications suggest that manufacturing organizations must adopt integrated and adaptive roadmap strategies that align technological innovation with environmental and social responsibility. Policymakers should support digital infrastructure development and workforce upskilling, while industry leaders must prioritize ethical and sustainable AI deployment to ensure long-term industrial resilience and competitiveness.