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The integration of artificial intelligence (AI) into businesses in Sabah presents a unique opportunity to drive innovation and competitiveness across diverse sectors such as agriculture, tourism, and natural resources. However, a critical challenge lies in developing and implementing AI solutions that are tailored to Sabah specific needs and constraints, particularly concerning the availability of relevant and high-quality data for training AI models. This study aims to address this challenge by proposing a framework for integrating local knowledge and domain expertise into the data collection and curation process, enhancing the quality and relevance of data used for training AI models in Sabah's businesses.The research objectives focus on identifying key sources of local knowledge and domain expertise relevant to Sabah's industries, designing methodologies for systematically capturing and integrating this knowledge into data collection processes, investigating techniques for validating and enriching collected data through collaborative efforts, and evaluating the impact of leveraging local knowledge on AI model accuracy, robustness, and applicability. Through achieving these objectives, actionable insights and guidelines will be provided to businesses in Sabah, enabling them to effectively harness local expertise to optimize their AI initiatives and drive sustainable economic growth in the region.Theoretical frameworks such as Resource-Based View (RBV), Dynamic Capabilities Theory, KnowledgeBased View (KBV), and Institutional Theory are explored in the literature review, providing valuable perspectives on leveraging local knowledge for competitive advantage and ethical AI deployment. Recommendations include adopting collaborative data collection approaches, developing contextaware data integration frameworks, investing in local talent development, and prioritizing ethical AI governance to ensure alignment with Sabah's cultural and regulatory norms.In conclusion, this research underscores the transformative potential of integrating local knowledge and domain expertise into AI strategies for Sabah's businesses. By embracing theoretical insights and practical strategies, businesses can navigate the complexities of AI adoption in a manner that fosters inclusive growth and societal well-being. The recommendations and future research agenda outlinedprovide a road map for advancing AI-driven entrepreneurship and economic development in Sabah's dynamic economic landscape, positioning the region as a hub for innovative and sustainable AI solutions tailored to local needs and constraints. Future research efforts will focus on implementing these recommendations to address evolving challenges and opportunities in the intersection of AI and business in Sabah
Eunora (Wed,) studied this question.