With the adoption of AI into talent acquisition and green policy procedures, there was a change in business models and the financial viability of recruiting businesses. The study evaluates the effects of AI-powered talent acquisition and green policies on recruitment agencies by drawing attention to operational effectiveness, cost-effectiveness, and revenue generation. The study evaluates the financial effects of AI on cost reduction and even profitability. The study analyzes how AI is changing business models and identifies the risks associated with it in recruitment. The study used purposive sampling techniques by gathering data from recruiters and HR professionals from different recruitment firms. A standardized, closed-end questionnaire with a 5-point Likert scale was distributed to big and midsized recruitment firms, yielding a sample size of 265 respondents. The pooled data was analyzed using statistical methods such as regression, correlation analysis, chi-square test, and descriptive statistics to assess how AI affects the transformation of business models and financial stability. The findings explain that AI-powered hiring lowered the hiring expenses, enhanced operational effectiveness, and improved the decision-making process for candidate selection. The study found that the companies implementing AI showed an increase in scalability and higher revenue growth when compared with traditional recruitment agencies. The issues like algorithmic bias, compliance hazards, and the requirement for labor reskilling were drastically held back after the implementation of AI. The study finally explains that AI-driven talent acquisition and green policies have been changing recruitment agencies by assessing substantial financial gains and operational improvements.