Artificial Intelligence and Data Analytics Integration Transforming U.S. Business Intelligence Practices

Abstract

Purpose

This study looks at the impact of artificial intelligence (AI) and data analytics on the business intelligence (BI) space and how they can help improve organizational performance in the USA. The study looks at the various impacts of using AI, its analytical power, the effectiveness and implementation issues of BI, and how all of these together collectively affect the competitiveness and digital transformation of organizations.

Design/Methodology/Approach

This study used a quantitative cross sectional survey design. A 35-item structured questionnaire was administered on a Likert scale to 300 experts from organizations using AI at the United States. The seven constructs measured by the instrument were linked with the use of AI, the ability to use data analytics, the effectiveness of business intelligence, organizational performance and future readiness. Cronbach's alpha was used to evaluate the reliability and the proposed relationships were analyzed by descriptive statistics, Pearson correlation, multiple regression and ANOVA in SPSS.

Findings

The findings of the study show that the organizations are in the stage of high level of AI adoption, data analytics capability and effectiveness of Business Intelligence. The results of the correlation analysis showed that all major constructs were positive and significant. Multiple regression analysis showed that Business Intelligence Effectiveness (β = 0.34) and AI and Data Analytics Integration (β = 0.31) were the most important factors in predicting organizational performance. Negative impact of challenges and ethical issues was identified. The regression model achieved an R2 value of 0.67, which accounted for 67% of the variance in organizational performance, and was statistically significant (F = 74.32, p < 0.001), further supporting the significance of business intelligence through AI for organizational success.

Practical Implications

The study provides executives and decision-makers with actionable tips and strategies on how to leverage their AI-enabled business intelligence tools to improve their organization's performance. The findings emphasize the importance of focusing on investments in advanced analytics, reskilling the workforce, and building robust governance and management structures for AI and data to maximize value and secure a competitive advantage in the business.

Originality/Value

The present study offers an empirical understanding of the strategic use of AI and data analytics in the system of business intelligence in the United States. It offers a holistic view on how smart analytics can support better organizational decision making, operations, innovation and long term business success and highlights the importance of considering ethics and governance issues when seeking digital transformation.