國立虎尾科技大學 |

Trust in the Machine : = AI-Powered Tax Services vs. Human Experts.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Trust in the Machine :/
其他題名:	AI-Powered Tax Services vs. Human Experts.
作者:	Leffew, Barry Anderson.
面頁冊數:	1 online resource (186 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:	Dissertations Abstracts International85-11B.
標題:	Robotics. -
電子資源:	click for full text (PQDT)
ISBN:	9798382748405

Trust in the Machine : = AI-Powered Tax Services vs. Human Experts.
Leffew, Barry Anderson.

Trust in the Machine :AI-Powered Tax Services vs. Human Experts. - 1 online resource (186 pages)

Source: Dissertations Abstracts International, Volume: 85-11, Section: B.

Thesis (D.B.A.)--Drexel University, 2024.

Includes bibliographical references

Integrating Artificial Intelligence (AI) into digital automation technologies is revolutionizing numerous industries and business models. This research focuses on AI's role in creating digital workers for tax advice while exploring the differences and similarities of interacting with an AI digital worker compared to a human CPA. Digital workers, enabled by AI, are poised to significantly impact the white-collar workforce, particularly in automating routine tasks and enhancing efficiency in areas like financial advice, healthcare, and customer service.Advancements in AI, notably in large language models like ChatGPT, have opened new avenues for applications such as chatbots and virtual assistants. These AI-driven digital workers utilize technologies like Robotic Process Automation (RPA) and analytics, automating business functions and augmenting human interaction.Digital worker automation, combining conversational intelligence and RPA, works alongside employees, understanding and responding to commands. These workers represent metaverse-based extensions of digital assistants like Amazon's Alexa and Apple's Siri. The technology enabling digital workers is rapidly progressing, creating significant market opportunities and potentially disrupting white-collar job roles.A critical aspect of this research is understanding the factors influencing customers' willingness to share sensitive information with AI-driven digital workers compared to human experts. The study examines the broader adoption and utilization of digital workers, considering demographic factors and their impact on technology adoption.Theoretical frameworks like the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are used to analyze trust in digital workers. The study also explores the impact of perceived anthropomorphism, intelligence, and animacy on AI adoption and the level of technostress experienced by users.In summary, this research provides insights into the potential and challenges of employing AI-driven digital workers in specialized fields like tax advice. It aims to extend an understanding of how digital worker technology can be adopted and utilized effectively, studying both benefits and limitations.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382748405Subjects--Topical Terms:

561941
Robotics.
Subjects--Index Terms:

Technology Acceptance ModelIndex Terms--Genre/Form:

554714
Electronic books.

Trust in the Machine : = AI-Powered Tax Services vs. Human Experts.
LDR:03680ntm a22004217 4500 001 1148228
005 20240916070032.5
006 m o d
007 cr bn ---uuuuu
008 250605s2024 xx obm 000 0 eng d
020 $a 9798382748405
035 $a (MiAaPQ)AAI31144328
035 $a AAI31144328
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Leffew, Barry Anderson. $3 1474153
245 1 0 $a Trust in the Machine : $b AI-Powered Tax Services vs. Human Experts.
264 0 $c 2024
300 $a 1 online resource (186 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
500 $a Advisor: Gefen, David;Anandarjan, Murugan.
502 $a Thesis (D.B.A.)--Drexel University, 2024.
504 $a Includes bibliographical references
520 $a Integrating Artificial Intelligence (AI) into digital automation technologies is revolutionizing numerous industries and business models. This research focuses on AI's role in creating digital workers for tax advice while exploring the differences and similarities of interacting with an AI digital worker compared to a human CPA. Digital workers, enabled by AI, are poised to significantly impact the white-collar workforce, particularly in automating routine tasks and enhancing efficiency in areas like financial advice, healthcare, and customer service.Advancements in AI, notably in large language models like ChatGPT, have opened new avenues for applications such as chatbots and virtual assistants. These AI-driven digital workers utilize technologies like Robotic Process Automation (RPA) and analytics, automating business functions and augmenting human interaction.Digital worker automation, combining conversational intelligence and RPA, works alongside employees, understanding and responding to commands. These workers represent metaverse-based extensions of digital assistants like Amazon's Alexa and Apple's Siri. The technology enabling digital workers is rapidly progressing, creating significant market opportunities and potentially disrupting white-collar job roles.A critical aspect of this research is understanding the factors influencing customers' willingness to share sensitive information with AI-driven digital workers compared to human experts. The study examines the broader adoption and utilization of digital workers, considering demographic factors and their impact on technology adoption.Theoretical frameworks like the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are used to analyze trust in digital workers. The study also explores the impact of perceived anthropomorphism, intelligence, and animacy on AI adoption and the level of technostress experienced by users.In summary, this research provides insights into the potential and challenges of employing AI-driven digital workers in specialized fields like tax advice. It aims to extend an understanding of how digital worker technology can be adopted and utilized effectively, studying both benefits and limitations.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Robotics. $3 561941
650 4 $a Finance. $3 559073
650 4 $a Information technology. $3 559429
653 $a Technology Acceptance Model
653 $a ChatGPT
653 $a Robotic Process Automation
653 $a UTAUT
653 $a Technostress
655 7 $a Electronic books. $2 local $3 554714
690 $a 0310
690 $a 0489
690 $a 0800
690 $a 0508
690 $a 0771
710 2 $a Drexel University. $b Business Administration (LeBow College of Business). $3 1473537
710 2 $a ProQuest Information and Learning Co. $3 1178819
773 0 $t Dissertations Abstracts International $g 85-11B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31144328 $z click for full text (PQDT)