AN ANALYSIS OF THE IMPACT OF GENERATIVE AI ON BUSINESS DECISION MAKING

Generative Artificial Intelligence (Generative AI) is increasingly becoming part of everyday business work, influencing how organizations gather, interpret and apply information. Rather than relying only on fixed instructions, these systems can respond to natural-language prompts and produce summaries, ideas, explanations and possible recommendations. This study examines how Generative AI may influence business decision-making across marketing, finance, human resources, operations and strategic planning. A quantitative framework is proposed, with primary data to be collected through a structured questionnaire from 250 people who have used Generative AI for work-related purposes. Secondary material is drawn from academic journals, books, scholarly publications and credible reports. The study considers perceived usefulness, quality and accuracy of AI outputs, ease of use, transparency, privacy concerns and human oversight as factors that may shape trust and decision-making effectiveness. Percentage analysis, descriptive statistics, reliability testing, Pearson correlation, multiple regression and hypothesis testing form the proposed analytical framework. The model results suggest that Generative AI can speed up information handling, reduce repetitive work and help users compare alternatives. However, unreliable responses, privacy issues, bias and overdependence can create serious limitations. Generative AI is therefore positioned as a support system for business decisions, with final judgement and accountability remaining with people.

Keywords: Generative AI, Artificial Intelligence, Business Decision-Making, Decision Support, AI Adoption, Trust, Human Oversight, Business Analytics

Generative AI Artificial Intelligence Business Decision-Making Decision Support AI Adoption Trust Human Oversight Business Analytics