AI-Driven Decision-Making and Its Impact on Business Performance

This study investigates the impact of Artificial Intelligence (AI)-driven decision-making on business performance, focusing on how intelligent systems are reshaping strategic, operational, and organizational outcomes. The main objective is to explore the fundamental models and mechanisms through which AI enhances decision quality, assess its performance outcomes across key business functions, and examine associated ethical and governance challenges. A systematic literature review methodology was adopted, drawing from peer-reviewed journal articles published between 2020 and 2025. Data were sourced from academic databases including Scopus, Web of Science, ScienceDirect, and IEEE Xplore. The review followed PRISMA guidelines and applied rigorous inclusion, exclusion, and thematic analysis procedures.

Findings reveal that AI contributes significantly to operational efficiency, financial forecasting, customer engagement, and innovation capacity. However, challenges such as data quality, talent shortages, ethical risks, and resistance to change hinder its optimal implementation. The study further identifies future trends including hyper-personalization, generative AI, and platform-based ecosystems, alongside strategic implications such as the need for hybrid decision-making and ethical governance structures.

The study concludes that AI, when aligned with business strategy and supported by ethical frameworks, offers transformative potential for organizational performance. Business leaders and policymakers are advised to adopt holistic, inclusive, and forward-looking approaches to AI integration to ensure sustainable and equitable outcomes.