AI and ML integrations have rustled a new revolution in mechanical manufacturing, making the traditional systems intelligent, connected ecosystems in tune with Industry 4.0. This paper further extends the discussion to understand the paradigm shift focusing on Industry 5.0, which would lay more emphasis on human-AI collaboration, sustainability, and resilience. In fact, this provides insights into some critical gaps in research on socio-technical challenges related to integrating human expertise in AI-powered systems and embedding metrics of sustainability and resilience into the manufacturing framework through systematic, simulation-based experimentation and theoretical modeling. The listed findings are that the application of AI-enhanced predictive maintenance reduces downtime by 42%; defect detection systems attain accuracy rates of 98.7%, while material waste is reduced by 22%. The industry 5.0 framework depicts how jointly controlled human-AI decision-making could improve operator satisfaction by 35% and task efficiency by 45%. Sustainability and resilience are further advanced by energy optimization attaining a 15% reduction in carbon emissions, and adaptive capabilities-which improves the recovery rate upon disruption by 18%. This paper develops a holistic framework on collaboration between humans and AI in bridging the gaps between Industry 4.0 and 5.0, while the core drive is toward ethical AI design, cognitive augmentation, and circular economic principles. The present study underlines the big transformation possibility of AI in enabling human-centered sustainable and resilient mechanical manufacturing ecosystems. The basis of this work further initiates Industry 5.0 and thereby provides actionable insights for academia, industry, and policy makers in advancing innovation while achieving the global goals of sustainability.