<![CDATA[Abstract The implementation of Artificial Intelligence (AI) in modern corporations has shifted from merely being a technological experiment to becoming a key driver of business transformation and operational efficiency. This study aims to analyze and document the quantitative and qualitative impacts of AI adoption on workforce productivity, cost efficiency, and corporate financial performance through a Systematic Literature Review (SLR) approach based on the PRISMA standard. Based on a comprehensive analysis of empirical studies, Monte Carlo simulation studies, and reports from international institutions, the findings indicate that AI adoption has a positive and statistically significant relationship with operational efficiency. The key findings reveal that every 10-point increase in the AI Usage Index contributes to a 7.95% increase in labor productivity, with companies in the highest adoption quartile demonstrating 43% higher productivity compared to those in the lowest quartile. Furthermore, companies adopting AI experience a significant reduction in operational cost ratios (38% compared to 46% among non-adopters) and an improvement in Return on Assets (ROA 11.8% versus 7.4%). Workflow time reductions were recorded at 30–100% across various core administrative and recruitment tasks. Nevertheless, successful AI implementation is highly dependent on organizational digital readiness, data governance, and collaborative Human-AI Workflow strategies. This review formulates a three-stage strategic framework and provides practical recommendations for business leaders and policymakers. Keywords — Artificial Intelligence (AI), Business Efficiency, Human-AI Workflows, Labor Productivity, Operational Cost Control, Systematic Literature Review]]>
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