02.1 - (Generative) AI and Machine Learning Solutions: From Data to Decisions

• Steliana Vasileva

  D. A. Tsenov Academy of Economics

  Yazar

Recent innovations in Artificial Intelligence (AI) have led to the development of new paradigms in machine processing, shifting from data-driven, discriminative AI tasks to advanced tasks, enabled by generative AI. These technologies allow companies to manage extensive volumes of both structured and unstructured data and produce actionable insights with remarkable speed and precision. Through the application of generative AI, businesses can create predictive models that reflect market scenarios, customer behaviours, and competitive dynamics. The current paper researches the relationship that exists between generative AI and machine learning, emphasizing their roles in market analysis and business development. The two terms are often used in both scientific and media contexts, at times interchangeably, and at other times with distinct meanings. The paper reviews relevant literature and aims to offer a foundation for (interdisciplinary) discussions and future studies on the topic. As businesses adopt these innovations, it is essential that they focus on ethical considerations in order to create systems that deliver both value and integrity, which is crucial for achieving long-term success and sustainability in a business environment, influenced by AI. The paper seeks to be a vital resource for researchers, students, and practitioners seeking insight into the complex journey to data-driven decision making through (Gen)AI.