Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review

Повышение производительности труда с помощью генеративного искусственного интеллекта: всесторонний обзор литературы
Zied Bahroun, Vian Ahmed, Humaid Al Naqbi
2024-01-30

ChatGPT and conversational agentsGenerative Artificial Intelligence (GAI)PRISMA methodologybibliometric analysiswork productivity
In this review, utilizing the PRISMA methodology, a comprehensive analysis of the use of Generative Artificial Intelligence (GAI) across diverse professional sectors is presented, drawing from 159 selected research publications. This study provides an insightful overview of the impact of GAI on enhancing institutional performance and work productivity, with a specific focus on sectors including academia, research, technology, communications, agriculture, government, and business. It highlights the critical role of GAI in navigating AI challenges, ethical considerations, and the importance of analytical thinking in these domains. The research conducts a detailed content analysis, uncovering significant trends and gaps in current GAI applications and projecting future prospects. A key aspect of this study is the bibliometric analysis, which identifies dominant tools like Chatbots and Conversational Agents, notably ChatGPT, as central to GAI’s evolution. The findings indicate a robust and accelerating trend in GAI research, expected to continue through 2024 and beyond. Additionally, this study points to potential future research directions, emphasizing the need for improved GAI design and strategic long-term planning, particularly in assessing its impact on user experience across various professional fields.
1
A PRISMA-based review of 159 publications provides a comprehensive analysis of Generative AI (GAI) across multiple professional sectors.
2
Bibliometric analysis identifies chatbots and conversational agents, particularly ChatGPT, as dominant tools central to GAI’s evolution.
3
Content analysis uncovers significant trends and gaps in current GAI applications and projects future prospects for the field.
4
Future research directions include improving GAI design and strategic long-term planning, especially to assess GAI’s impact on user experience across professions.
5
GAI positively impacts institutional performance and work productivity in sectors including academia, research, technology, communications, agriculture, government, and business.
6
GAI research shows a robust and accelerating trend expected to continue through 2024 and beyond.
7
The study highlights ethical considerations, AI challenges, and the importance of analytical thinking when deploying GAI in professional domains.

Use of Generative Artificial Intelligence (GAI) across diverse professional sectors

Impact of GAI on enhancing institutional performance and work productivity, including trends, gaps, tools (e.g., ChatGPT/chatbots), ethical considerations, and effects on user experience

Publication Details
Publication Date
2024-01-30
Journal
Publisher
ISSN
Cited by
291
Access Type
Author Information
Authors
Zied Bahroun
Vian Ahmed
Humaid Al Naqbi
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat
Make a presentation
100%