Information Technology Perspective On Business

The business landscape is fundamentally being reshaped by the unrelenting rise of Artificial Intelligence (AI) and the necessity of data-driven decision making (DDDM). This transformation demands a parallel evolution in the practice of Business Analysis (BA). This thesis examines the critical intersection of Business Analysis and Information Technology (IT) within this new paradigm. It argues that traditional BA approaches, while foundational, are insufficient to navigate the complexities of AI integration, big data ecosystems, and the velocity of modern decision cycles. The BA position is evolving from one of a requirements facilitator to one of a strategic orchestrator of data, technology, and business value from an IT perspective. This paper examines how advanced analytics (ML, NLP), AI capabilities (predictive modeling, automation), and IT infrastructure (cloud, data lakes, APIs) are redefining BA processes, tools, and competencies. Process modeling incorporating AI-driven automation and real-time analytics; solution evaluation focusing on model performance and ethical implications; and requirements elicitation shifting toward data product definition and algorithmic fairness are all examined. An IT perspective is used to examine important issues like data governance, algorithmic bias, technical literacy gaps, and ethical considerations. The thesis proposes a framework that places an emphasis on technical fluency, data literacy, ethical stewardship, and collaborative agility in contemporary IT environments for the AI-savvy Business Analyst. Case studies illustrate successful integration, while recommendations guide organizations in empowering BAs to become indispensable translators and value drivers in the age of intelligent systems.