The rapid integration of Artificial Intelligence (AI) into education systems is redefining teaching and learning paradigms across the globe. In India, with the rollout of the National Education Policy (NEP) 2020 and the push for digital transformation, AI holds the potential to completely change faculty development and pedagogical practices in higher education. This research investigates the impact of AI-based tools on Indian educators, focusing on personalized teaching, adaptive learning systems, and data-driven decision-making. The study examines how AI technologies empower faculty through continuous upskilling and reskilling, enabling them to adapt to evolving learning environments. Using AI-driven Learning Management Systems (LMS), teachers can now access real-time analytics, automate assessments, and personalize student feedback. However, the adoption of these technologies depends on institutional readiness, faculty digital literacy, and infrastructure availability. A structured questionnaire was distributed to 100 faculty members across Indian universities. The data was analyzed using SPSS tools, including percentage analysis, multiple regression, and chi-square analysis. The study identifies eight key factors influencing faculty empowerment: digital literacy, institutional support, training programs, AI integration in LMS, perceived usefulness, ease of use, policy awareness, and resistance to change. Results reveal a strong correlation between AI adoption and enhanced teaching effectiveness. Faculty members exposed to AI tools demonstrated increased engagement, better course customization, and improved student performance metrics. However, challenges such as lack of AI training, fear of redundancy, and inadequate infrastructure remain. The study emphasizes the need to implement structured AI competency programs and clear policy directives under NEP 2020. This research contributes to ongoing discourse by offering a faculty-centric perspective on AI adoption in Indian higher education. It offers concrete recommendations for policymakers, academic leaders, and EdTech developers to collaboratively design future-ready academic ecosystems.