Generative AI for Business and Economics
Theory and Applications
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Beschreibung
This book explores the growing influence of generative artificial intelligence in reshaping business practices, economic systems, and strategic decision-making. Centred on the theoretical foundations, computational models, and applied use cases of generative AI, it brings together contemporary research and real-world applications across key domains such as finance, markets, entrepreneurship, supply chains, policy analysis, and sustainability. The chapters address large language models, generative analytics, intelligent automation, predictive modelling, and human–AI collaboration in economic and organizational contexts. By combining rigorous analytical approaches with practical insights, the book offers a timely reference to researchers, practitioners, students, and policymakers.
This book explores the growing influence of generative artificial intelligence in reshaping business practices, economic systems, and strategic decision-making. Centred on the theoretical foundations, computational models, and applied use cases of generative AI, it brings together contemporary research and real-world applications across key domains such as finance, markets, entrepreneurship, supply chains, policy analysis, and sustainability. The chapters address large language models, generative analytics, intelligent automation, predictive modelling, and human–AI collaboration in economic and organizational contexts. By combining rigorous analytical approaches with practical insights, the book offers a timely reference to researchers, practitioners, students, and policymakers.
Discusses generative AI from an interdisciplinary, practical-oriented perspective Addresses the role of data, analytics, and digital infrastructure in enabling generative AI adoption Gives attention to ethical, legal, and policy considerations
Autor*in
Srikanta Patnaik
Themen in »Generative AI for Business and Economics«
Business Applications of Generative AI Predictive Models Data-Driven Decisions Operational Efficiency Generative Adversarial Networks Deep Neural Networks Supply Chain Optimization Reinforcement Learning Human-centric AI design Digital Transformation Hybrid AI–human Approaches Market Trend Analysis Sustainable Entrepreneurship