Workplace bias and gender disparities are barriers to professional environments. Artificial Intelligence (AI) has the potential to detect & mitigate these inequalities. It raises a risk of amplifying them when models are trained on skewed data. This paper presents a statistical analysis of existing gender biases using recruitment & salary datasets that are available in the public domain. This study investigates the differences in hiring outcomes & compensation by gender & education levels using Orange Miner for data visualization and exploratory data analysis (EDA). Furthermore, the paper conceptualizes these findings with women's empowerment schemes of the Indian government. It highlights the inequalities currently present in historical data and examines the role of AI models in detecting bias and disparities. It highlights the requirements of designing ethical AI systems to ensure equality, transparency, and a supportive environment for women. The paper emphasized how female inclusiveness can be promoted through AI-powered, ethical, transparent, and responsive models that enable true analysis and decision-making.