Impact of Artificial Intelligence–Driven Talent Analytics on Marketing Performance and Financial Outcomes of Organizations

The rapid advancement of Artificial Intelligence (AI) has transformed organizational decision-making processes, particularly in the domain of talent management. AI-driven talent analytics has emerged as a strategic tool that enables organizations to systematically collect, analyze, and interpret workforce data to enhance employee performance, optimize human capital deployment, and align talent strategies with organizational objectives. Despite growing practitioner interest, empirical research examining the impact of AI-driven talent analytics on marketing performance and financial outcomes remains limited, especially in comparative organizational contexts. The present study conducts a comprehensive empirical investigation into how varying levels of AI-driven talent analytics adoption influence marketing effectiveness and financial performance across organizations. The study is based on a purposive sample of 200 organizations, categorized into high AI-analytics adopters and low AI-analytics adopters. Using a quantitative research design, the study employs independent samples t-tests, chi-square tests of independence, and discriminant analysis to examine differences across multiple dimensions, including analytics-driven decision quality, employee capability optimization, marketing performance indicators, financial outcomes, and perceived implementation barriers. The findings reveal statistically significant differences between organizations with high and low adoption of AI-driven talent analytics. Organizations with advanced analytics capabilities demonstrate superior marketing performance, including improved customer targeting accuracy, campaign effectiveness, and market responsiveness, alongside enhanced financial outcomes such as revenue growth, profitability, and operational efficiency. Conversely, organizations with lower analytics maturity report greater challenges related to data quality, skill gaps, and integration costs. The results underscore the strategic value of AI-driven talent analytics in strengthening organizational competitiveness and financial resilience. The study highlights the necessity for organizations to invest in analytics capabilities, cross-functional integration, and data-driven talent strategies to achieve sustainable performance advantages