The rise of Industry 4.0 has introduced significant transformations in business operations, with Artificial Intelligence (AI) playing a central role in automating processes, enhancing decision-making, and improving efficiency. However, despite its potential, many organizations face critical challenges in implementing AI, particularly in terms of technological infrastructure readiness, workforce capabilities, and ethical considerations. This research aims to identify the challenges and propose effective strategies for AI implementation in business processes, particularly within the context of Industry 4.0. A systematic literature review (SLR) was employed to analyze peer-reviewed studies that discuss AI integration across various industrial sectors. The findings indicate that the primary challenges include the integration of AI with existing legacy systems, data privacy concerns, and employee resistance due to the perceived threat of automation. Additionally, the lack of adequate training and infrastructure investment further hampers AI adoption. In response, the research highlights strategies such as upgrading technological infrastructure, continuous employee training, and the development of clear ethical guidelines to address these challenges. The research contributes by providing a comprehensive framework for businesses to successfully navigate AI implementation, offering a novel perspective on balancing technological advancements with human resource development and ethical concerns, essential for long-term business sustainability in the digital era