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Artificial Intelligence in Businesses : = Adoption, Acceptance, and Implementation.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Artificial Intelligence in Businesses :/
Reminder of title:	Adoption, Acceptance, and Implementation.
Author:	Maldonado Burgos, Zedrick A.
Description:	1 online resource (138 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-11, Section: A.
Contained By:	Dissertations Abstracts International85-11A.
Subject:	Information technology. -
Online resource:	click for full text (PQDT)
ISBN:	9798382763637

Artificial Intelligence in Businesses : = Adoption, Acceptance, and Implementation.
Maldonado Burgos, Zedrick A.

Artificial Intelligence in Businesses :Adoption, Acceptance, and Implementation. - 1 online resource (138 pages)

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

Thesis (D.B.A.)--Universidad Ana G Mendez - Gurabo, 2024.

Includes bibliographical references

This study identifies and measures the variables influencing the adoption of artificial intelligence (AI) in Businesses from 116 participants who are professionals, entrepreneurs, and those involved in daily business operations. The research focuses on perceived ease of use, perceived usefulness, psychological readiness, credibility, perceived risk, privacy, security, social influence, and AI adoption. Through multivariate analysis, the study evaluated variables associated with AI adoption, revealing that 52.6% of AI adoption was explained by five independent variables included in the research model. The research demonstrates that the association businesses can take to integrate AI better starts with perceived ease of use and perceived usefulness, leading to psychological readiness. From there, it progresses to credibility and perceived risk, ultimately resulting in AI adoption. Credibility emerged as the strongest predictor for businesses to adopt AI, with 82.5%, as demonstrated by Psychological Readiness. Psychological readiness also explains AI adoption, with 80.4% showing its significant influence.To ensure users adopt AI technologies, they must perceive the AI tools as credible. This credibility is achieved when the tools demonstrate ease of use and usefulness. Businesses should focus on evaluating AI tools that score high in these areas. Addressing data privacy and algorithmic bias is important as perceived risk is negatively associated with AI adoption. Privacy had a strong positive association with AI adoption, highlighting the importance of privacy measures for user trust. Security concerns, with 70.6%, gave an important view of how users of these technologies are concerned about their well-being while using AI. While social influence was not a high predictor of AI adoption, it provided insights into how businesses can better educate employees to understand these emerging technologies. The study highlights psychological readiness and credibility as significant predictors of AI adoption, addressing perceived risk and privacy concerns. These findings provide insights for businesses aiming to integrate AI into their operations effectively. Addressing these key variables can significantly enhance the acceptance and implementation of AI technologies in various sectors.

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

Mode of access: World Wide Web

ISBN: 9798382763637Subjects--Topical Terms:

559429
Information technology.
Subjects--Index Terms:

AI adoptionIndex Terms--Genre/Form:

554714
Electronic books.

Artificial Intelligence in Businesses : = Adoption, Acceptance, and Implementation.
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520 $a This study identifies and measures the variables influencing the adoption of artificial intelligence (AI) in Businesses from 116 participants who are professionals, entrepreneurs, and those involved in daily business operations. The research focuses on perceived ease of use, perceived usefulness, psychological readiness, credibility, perceived risk, privacy, security, social influence, and AI adoption. Through multivariate analysis, the study evaluated variables associated with AI adoption, revealing that 52.6% of AI adoption was explained by five independent variables included in the research model. The research demonstrates that the association businesses can take to integrate AI better starts with perceived ease of use and perceived usefulness, leading to psychological readiness. From there, it progresses to credibility and perceived risk, ultimately resulting in AI adoption. Credibility emerged as the strongest predictor for businesses to adopt AI, with 82.5%, as demonstrated by Psychological Readiness. Psychological readiness also explains AI adoption, with 80.4% showing its significant influence.To ensure users adopt AI technologies, they must perceive the AI tools as credible. This credibility is achieved when the tools demonstrate ease of use and usefulness. Businesses should focus on evaluating AI tools that score high in these areas. Addressing data privacy and algorithmic bias is important as perceived risk is negatively associated with AI adoption. Privacy had a strong positive association with AI adoption, highlighting the importance of privacy measures for user trust. Security concerns, with 70.6%, gave an important view of how users of these technologies are concerned about their well-being while using AI. While social influence was not a high predictor of AI adoption, it provided insights into how businesses can better educate employees to understand these emerging technologies. The study highlights psychological readiness and credibility as significant predictors of AI adoption, addressing perceived risk and privacy concerns. These findings provide insights for businesses aiming to integrate AI into their operations effectively. Addressing these key variables can significantly enhance the acceptance and implementation of AI technologies in various sectors.
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