Artificial Intelligence-Driven Business Analytics for IT Strategy: Advancing Decision-Making, Real-Time Insights, and Organizational Agility Through Intelligent Automation and Data Integration

Shariful Haque; Nur Mohammad; Azamat Mambetaliev; Aibek Karshiboev; Khadeza Yesmin Lucky; Md Tamjidul Haq khan; Hasibul Islam

doi:10.63332/joph.v5i6.2287

Authors

Shariful Haque School of Business, International American University, Los Angeles, CA 90010, USA
Nur Mohammad College of Technology & Engineering, Westcliff University, Irvine, CA 92614, USA
Azamat Mambetaliev College of Technology & Engineering, Westcliff University, Irvine, CA 92614, USA
Aibek Karshiboev College of Technology & Engineering, Westcliff University, Irvine, CA 92614, USA
Khadeza Yesmin Lucky College of Business, Westcliff University, Irvine, CA 92614, USA
Md Tamjidul Haq khan School of Business, International American University, Los Angeles, CA 90010, USA
Hasibul Islam School of Business, International American University, Los Angeles, CA 90010, USA

DOI:

https://doi.org/10.63332/joph.v5i6.2287

Keywords:

Artificial Intelligence, Business Analytics, IT Strategy, Intelligent Automation, Digital Transformation, Strategic Alignment, Machine Learning

Abstract

This research assesses the way AI-driven analytics help organizations operate more flexibly, make decisions quickly, and fully align their IT with business priorities. In the current digital era, companies depend on business analytics powered by AI to modify their IT strategies and improve their ability to decide. AI with business intelligence, organizations process huge amounts of data quickly to get useful information that supports efficient work and gives them an edge over their competitors. The focus is on how using smart automation and integrated data allows IT governance to become proactive and enterprise planning to adapt. A combination of qualitative and quantitative methods is used in this study. Through surveys given to 300 IT experts and leaders from many industries. The experience with AI-driven analytics tools and how they see AI helping with strategic planning was recorded. Deep insight into these factors was gathered through interviews with 20 IT executives. The author used SPSS software for statistics on numbers and thematic coding on words to look for similar themes and links between AI adoption and IT plan results. AI technology in business analytics is shown to help companies react more quickly, support data-driven choices and ensure alignment between the business and IT. With intelligent automation, there is less complexity in operating the business and to real-time analytics, reactions to market changes are faster. Some integration obstacles and data quality issues did not stop organizations from achieving better innovation and standing out in the market. The research makes clear that AI is key to having successful data-based and flexible IT systems in the future.