Autonomous Business Intelligence: Integrating Artificial Intelligence, Machine Learning, and Predictive Analytics for Organizational Excellence

Abstract

Autonomous Business Intelligence (ABI) is a new generation of Business Intelligence (BI) that fuses with Artificial Intelligence (AI), Machine Learning (ML), and Predictive Analytics, while incorporating intelligent decision-making systems to transform how businesses make decisions. This study focused on how these technologies contribute to organizational excellence by improving information processing, predictive capability, strategic decision-making, and operational efficiency. The research design was quantitative and cross-sectional, collecting data from 300 organizational professionals with knowledge or experience in Business Intelligence, AI, ML, and Predictive Analytics. Descriptive statistics and diagnostic procedures were used in analysing the data. The findings showed positive perceptions of AI (M = 3.87, SD = 0.68), ML (M = 3.79, SD = 0.71), Predictive Analytics (M = 3.84, SD = 0.69), and Organizational Excellence (M = 3.91, SD = 0.65). The diagnostic analysis did not indicate serious multicollinearity, as the VIF values ranged from 2.04 to 2.31, and the Durbin–Watson value of 1.91 is satisfactory for testing residual independence. The findings revealed that these three technologies were important capabilities for creating more intelligent and proactive decision-making environments in an organization: AI, ML, and Predictive Analytics. The research revealed that including ABI can contribute to organizational success by strengthening analytical skills, prediction, organizational response, and data management. The study recommends investing in people, systems, processes, and AI, as well as data quality, digital infrastructure, employee analytical capacity, and collaborative opportunities between humans and AI, all of which are critical. The study contributes to the existing corpus of ABI research by providing a comprehensive understanding of the relationship between intelligent technologies and organizational excellence and by recommending continued exploration of this relationship across industries and environments.

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