AI Agents for Predictive and Prescriptive Analytics: Enhancing Foresight and Strategy

Abstract

The rapid evolution of artificial intelligence (AI) has positioned intelligent agents as critical enablers of predictive and prescriptive analytics in enterprise decision-making. Predictive analytics focuses on forecasting future outcomes using historical and real-time data, while prescriptive analytics extends this capability by recommending optimal actions to achieve strategic objectives. This paper explores the role of AI agents in enhancing organizational foresight and guiding proactive strategies across sectors such as finance, healthcare, supply chain, and human resources. By integrating advanced machine learning models, reinforcement learning, and optimization techniques, AI agents can uncover hidden patterns, anticipate risks, and generate actionable recommendations with high accuracy. The proposed framework emphasizes explainability, scalability, and compliance, ensuring that predictive and prescriptive insights remain trustworthy and ethically aligned. Results from case studies and comparative analyses highlight improvements in efficiency, agility, and strategic adaptability.