The Rise of Generative Artificial Intelligence in Business

Generative artificial intelligence (hereinafter: AI) has emerged as a transformative force across industries, driving significant advancements in automation, efficiency, and innovation. This paper explores the impact of generative AI on business operations, focusing on its ability to enhance productivity, reduce costs, and improve customer experiences. By leveraging foundation models such as GPT-3.5, businesses are automating tasks that previously required human intervention, leading to substantial cost savings and operational efficiencies. Furthermore, this paper discusses the ethical implications of AI deployment, particularly in the areas of data privacy, algorithmic bias, and accountability. The paper also addresses the future trends in generative AI, including the development of multimodal models and their potential applications. This study provides a comprehensive overview of how businesses can harness generative AI to gain a competitive edge while mitigating the associated risks.

Authors

Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/informatics62280.2024.10900880
Citations
4
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Rise of Generative Artificial Intelligence in Business

Diana Mudrinić, Ivan Šoda
4 citations
Big Data and Business Intelligence
2.11
article

The Rise of Generative Artificial Intelligence in Business

Diana Mudrinić, Ivan Šoda
article en
4 citations

Abstract

Generative artificial intelligence (hereinafter: AI) has emerged as a transformative force across industries, driving significant advancements in automation, efficiency, and innovation. This paper explores the impact of generative AI on business operations, focusing on its ability to enhance productivity, reduce costs, and improve customer experiences. By leveraging foundation models such as GPT-3.5, businesses are automating tasks that previously required human intervention, leading to substantial cost savings and operational efficiencies. Furthermore, this paper discusses the ethical implications of AI deployment, particularly in the areas of data privacy, algorithmic bias, and accountability. The paper also addresses the future trends in generative AI, including the development of multimodal models and their potential applications. This study provides a comprehensive overview of how businesses can harness generative AI to gain a competitive edge while mitigating the associated risks.

Decent work and economic growth
Openalex Percentile: Top 10%
Big Data and Business Intelligence
2.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.