This research investigates the impact of leadership diversity, HR sustainability practices, and ethical governance on ESG performance. Based on machine learning models—Random Forest and XGBoost—the research forecasts ESG score development for the next five years, indicating a 10% rise in leadership diversity can increase ESG scores by 0.8–1.2 points. The research points out some important gaps, such as the lack of predictive ESG models, industry-specific benchmarks, and overall employee engagement metrics. The convergence of Green HRM, ESG-influenced business models, and sustainable financial models has a paradigm-shifting influence on the national economic growth and financial resilience and demands confluence of AI-based tools and techniques. Analysis of stock market performance data from India’s National Stock Exchange (NSE) and historical ESG datasets is conducted in the paper, it involves companies adopting sustainability practices and ESG transitions are likely to experience higher financial stability and investor confidence. Conversely, companies that ignore ESG principles experience increased volatility and risk exposure. An analysis of international ESG trends also underscores the need for companies to integrate sustainability policies into strategic decision-making, energy transition programs, and environmental footprint management. The results indicate that organizations need to make Green HRM policies more robust, improve diversity metrics, and leverage data-driven insights to foster sustainable growth. Future studies must address ESG risk assessments and industry-specific HR sustainability strategies to enable a greener and more responsible economy.