转化(遗传学)
计算机科学
过程管理
知识管理
业务
生物化学
基因
化学
作者
Anurag Shrivastava,Sheela Hundekari,RVS Praveen,Layth Hussein,Neeraj Varshney,Satya Subrahmanya Sai Ram Gopal Peri
标识
DOI:10.1109/icetm63734.2025.11051646
摘要
Artificial Intelligence (AI) is revolutionizing enterprise strategy and business model transformation by enabling data-driven decision-making, automation, and enhanced customer experiences. This paper explores how AI is reshaping traditional business models and driving new paradigms of digital innovation. By integrating AI-powered analytics, machine learning algorithms, and automation tools, enterprises can achieve higher operational efficiency, reduce costs, and enhance scalability. The study examines AI’s role in predictive analytics, process optimization, intelligent automation, and dynamic market adaptation, focusing on how businesses can leverage AI to remain competitive in an evolving digital landscape. Key challenges such as ethical AI adoption, regulatory considerations, and workforce adaptation are also discussed. A comparative analysis of AI-driven and traditional business models highlights the strategic advantages AI offers in terms of agility, personalization, and competitive positioning. The findings underscore that organizations that strategically embrace AI-driven transformation are better positioned to navigate industry disruptions and create long-term value. This research contributes to the growing body of knowledge on AI-enabled business strategies by providing insights into best practices and future trends in enterprise transformation.
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