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Summary:

Abstract: Artificial intelligence (AI) is quickly transforming business operations and society, as AI capabilities are incorporated into applications ranging from mobile personal assistants to self-driving cars. The potentially disruptive nature of AI calls for an extensive investigation into all aspects of AI-human interactions at individual, group, organizational and market levels. However, there is paucity of academic information systems (IS) research in this area that goes beyond the development and testing of specific narrow AI capabilities. AI represents an important opportunity for organizational and behavioral IS researchers, but also presents challenges associated with the underlying complexity of AI technologies and the diversity of AI applications. Understanding how existing AI research and business practice relate to traditional areas of IS research is an important step towards creating a comprehensive behavioral and organizational AI research agenda. This dissertation seeks to achieve a dual purpose in a series of three essays. Essay 1 seeks to understand the current state of business AI research and practice in business through a quantitative literature review, relate the findings to traditional IS research areas, and identify potentially fruitful research areas for AI-focused IS research. Essays 2 and 3 seek to address specific research questions related to one of such research areas, namely, human interactions with AI enabled applications. Essay 2 focus on user experience with a chatbot, a popular AI application, and Essay 3 explores how user experiences with AI assistant apps differ from their interactions with more traditional IT artifacts.

Author/Creator:

Nguyen, Quynh , author

Contributors:

Sidorova, Anna , committee chair

Languages:

English

Language Notes:

Item content: English

Main Work:

Three Essays on Artificial Intelligence Adoption and Use [by Nguyen, Q.]

Related Series:

NT dissertation, Business; [volume] 2019

Genres:

Academic theses

Dissertation Notes:

Ph. D. ― University of North Texas, 2019.

General Notes:

Includes bibliographical references.
Description based on: Online resource; title from PDF title page (UNT Digital Library, viewed July 28, 2021).

Physical Description:

1 online resource (ix, 167 pages).

Call Numbers:

Electronic Dissertation

OCLC Numbers:

1300232735