Leadership recruitment plays a pivotal role in shaping organizational success within the Indian Human Resource Management (HRM) ecosystem. However, the integration of Artificial Intelligence (AI) in recruiting leadership positions remains at a nascent stage, hindered by challenges in organizational readiness and strategic adoption. This paper presents a data-driven investigation into the readiness of Indian HRM to implement AI in leadership hiring, guided by a structured quantitative approach. The research surveyed HR professionals across multiple sectors using a validated instrument to assess infrastructure, awareness, perceived benefits and barriers to adoption. The dataset includes 544 responses analyzed through descriptive and inferential statistical methods. Findings reveal a generational and positional skew in AI familiarity, with greater openness among junior professionals but limited decision-making authority. The data also indicates that while AI tools such as resume screening and video interviewing are effective in high-volume roles, they fall short in evaluating complex behavioral and strategic traits essential for leadership. Additionally, infrastructural limitations, ethical concerns and lack of senior leadership engagement constrain broader AI implementation. The effectiveness of AI-driven recruitment for leadership roles is discussed with reference to organizational performance parameters such as cost-efficiency, hiring accuracy and strategic alignment. The outcomes suggest that a hybrid model integrating AI capabilities with human oversight is optimal. This research contributes to AI readiness assessment frameworks within Indian HRM and recommends targeted strategies for improving adoption in leadership contexts. The proposed model is evaluated on practical indicators such as implementation feasibility, perceived return on investment (ROI) and decision-making accuracy across varying organizational maturity levels.