Exploring Artificial Intelligence and Data Analytics for Innovation in Digital Transformation

Abstract

This study explores the ways in which data analytics and artificial intelligence (AI) foster creativity within the framework of digital transformation. The main research question is related to how much operational effectiveness and strategic decision-making are improved by the combination of these two. The study paradigm, which offers insights into organizational adoption, is based on the Diffusion of Innovation Theory and the Technology Acceptance Model (TAM). A qualitative evaluation of applications specifically suited to the operational requirements and difficulties in the manufacturing, healthcare, finance, retail, and smart city sectors is incorporated into the process. Data analysis reveals the useful advantages of AI-powered automation and predictive analytics, illustrating how they affect resource optimization, customer satisfaction, and productivity. The results support the original theory that analytics and AI are important facilitators of competitive advantage and sustained innovation. But, the study also points up important obstacles, such as issues with data privacy, integration difficulties, and moral ramifications. To properly utilize these technologies, the conclusions stress the necessity of robust governance, moral frameworks, and infrastructure adaptability. In addition to outlining future research areas for optimizing the potential of AI and data analytics in digital transformation plans, this study provides a thorough perspective on best practices. CZU: 004.6:004.8; JEL: O33, M15, L86