Generative AI for Advanced Value Creation

Sachin Tonk

Chapter 10 in Data Strategy and AI Value Creation:For Data Leaders by Data Leaders, 2025, pp 137-152 from World Scientific Publishing Co. Pte. Ltd.

Abstract: Generative artificial intelligence (AI), a developing subfield within the domain of machine learning, has become a catalyst for profound transformation across many industries. Generative AI employs various machine learning techniques, including deep learning and probabilistic modeling, to represent and manipulate data distributions. This allows it to generate novel data points that fall within the learned distribution, effectively creating something new from what it has seen. This dynamic subset of AI is characterized by the exceptional capacity to synthesize novel data patterns from existing data, prompting a wave of innovation with wide-reaching implications. In this chapter, we will examine the state-of-the-art developments and multifaceted applications of generative AI, highlighting its key role in promoting value creation worth trillions of dollars in the digital landscape and its impact in the ongoing digital era. Generative AI also poses a unique set of challenges. This chapter will also analyze the hurdles faced by practitioners pertaining to data quality, model bias, and the imperatives for responsible AI deployment. Additionally, it will delve into the complex ethical concerns that surround generative AI and address questions about intellectual property, privacy concerns, and the potential for misuse. The evolution of generative AI has propelled creativity and problem-solving into uncharted territories for businesses and researchers. This chapter emphasizes generative AI’s potential to drive invention, foster creativity, and intrinsically reshape the way we engage with data in the 21st century.

Keywords: Data Strategy; Data Governance; Data Quality; Privacy Protection; Artificial Intelligence; Generative AI; Business Value; Innovation; Digital Transformation; Regulations (search for similar items in EconPapers)
JEL-codes: O3 O32 (search for similar items in EconPapers)
Date: 2025
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