Author ORCID Identifier(s)

Tugrul Daim (0000-0003-1432-8958)

Published In

IEEE Engineering Management Review

Document Type

Pre-Print

Publication Date

10-1-2026

Subjects

Technology Assessment, Artificial Intelligence, Personal Computers, Decision Modeling, Innovation Management, Hierarchical Decision Model, Taiwan

Abstract

This study examines the key factors influencing the adoption of Artificial Intelligence Personal Computers (AIPCs) by enterprises, exploring both the benefits and challenges of their business applications. As enterprises increasingly require real-time computing, autonomous decision-making, and improved cybersecurity, AIPC—combining artificial intelligence and edge computing—has become a strategic technology for boosting competitiveness. Particularly in scenarios with less reliance on cloud services, businesses are more likely to adopt devices with local processing and standalone AI capabilities to meet the dual needs of operational efficiency and data privacy. Through an extensive review of the literature, this study identifies four main dimensions and sixteen criteria that affect AIPC adoption: Computing Performance and Efficiency, User Experience, Cost Optimization, and Security and Privacy. A Hierarchical Decision Model (HDM) was used to develop a structured questionnaire, which was distributed to 22 experts from the technology industry and enterprise information systems. The collected responses underwent multilevel weighting and consistency checks to identify the most important considerations and key decision factors for enterprise AIPC adoption.

Rights

© Copyright the author(s) 2026

Description

This is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published as: (2026). Factors Influencing Enterprise Adoption of AI-Enabled Computers: An Expert Judgment Quantification Approach Across Multiple Sectors. IEEE Engineering Management Review, 1–27. https://doi.org/10.1109/emr.2026.3718190

DOI

10.1109/EMR.2026.3718190

Persistent Identifier

https://archives.pdx.edu/ds/psu/45188

Publisher

IEEE

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