ChatGPT is considered here not as a single-purpose tool, but as a technology whose uses and limitations vary across business and economic settings. This edited collection brings together studies on its applications in finance, economics, management, and marketing, pairing broad questions about AI with focused examples of how researchers and organizations are exploring it.
AI across four connected fields
The book’s 18 chapters are grouped into sections on general topics, finance, economics, business, and marketing. That structure makes it possible to follow a particular discipline or compare how similar questions—such as reliability, decision-making, and responsible use—arise in different contexts.
From market analysis to customer service
Topics range from ChatGPT-related equities, portfolio hedging, fraud detection, and startup valuation to economic forecasting and agricultural tax compliance. Other chapters consider human resource management, AI policy, and Excel analysis. The marketing section turns to consumer behavior, ethical and legal concerns in marketing communication, and the use of chatbots and virtual assistants in customer support.
Research examples, not one-size-fits-all answers
Public sentiment on Twitter, hotel guest feedback, and management education are among the settings explored. Across these varied cases, the collection presents ChatGPT as a subject for practical investigation while also drawing attention to constraints and questions that accompany its use. Readers can compare approaches rather than assume that a tool useful in one domain will work equally well in another.
For readers studying AI in business
This volume will be relevant to researchers, students, educators, and professionals looking for a cross-disciplinary view of generative AI in business and the social sciences. Its breadth is especially useful for readers who want to connect finance, economic analysis, organizational practice, and marketing within one collection.
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