Analisis Pengaruh Penggunaan AI Image Generator terhadap Kinerja Karyawan Tim Desain Indra Group Semarang

  • Alberta Agnelia Priatko Unika Soegijapranata
  • Ridwan Sanjaya Magister Manajemen Unika Soegijapranata

Abstract

Advances in Artificial Intelligence (AI) in the field of architectural design offer opportunities to support the design exploration and development process. This study aims to examine the use of AI image generators and their impact on the performance of employees on the Indra Group design team in Semarang. This study employs a qualitative descriptive method, with data collected through observations and interviews with four informants (two employees who use AI and two who do not). The data were analyzed based on the aspects of productivity, creativity, and output quality using the Sociotechnical System theory and the AMO framework (ability, motivation, opportunity). The results show that the AI Image Generator serves as a supporting technology in concept exploration, the search for design alternatives, mood boards, inspiration, and visual development. The use of AI can support productivity through time efficiency and creativity through new ideas and visual alternatives; however, it has not yet significantly improved output quality because AI results are influenced by prompts, inputs, accuracy, detail, and design suitability. Based on AMO theory and the Sociotechnical System theory, the benefits of AI are influenced by employees’ capabilities and organizational support in integrating technology with work processes through joint optimization. Thus, the AI Image Generator serves as a supporting technology in the designer’s work process, with its effectiveness depending on employees’ ability to guide, evaluate, and refine the AI’s outputs.

References

Abbas, Roba, and Katina Michael. Socio-Technical Theory: A Review. TheoryHub Book, 2026. https://open.ncl.ac.uk.
Ahdussamad, Zuchri. Metode Penelitian Kualitatif. I. CV. syakir Media Press, 2021.
Appelbaum, Steven. ‘Socio-Technical Systems Theory: An Intervention Strategy for Organizational Development’. Management Decision 35, no. 6 (1997): Management Decision 35(6):452-463. https://doi.org/10.1108/00251749710173823.
Husein, Zamhir Basem, and Ade Sito. Manajemen Sumber Daya Manusia. PT Mafy Media Literasi Indonesia, 2025. https://penerbitmafy.com/wp-content/uploads/2025/04/MANAJEMEN-SUMBER-DAYA-MANUSIA-Skill-Motivasi-dan-Disiplin-Kerja.pdf.
Ismah, Nurhayatul. ‘Literatur review: Kecerdasan Buatan dalam Desain Grafis - Menavigasi Peluang dan Tantangan di Era Digital’. Jurnal Syntax Admiration 5, no. 10 (2024): 4285–93. https://doi.org/10.46799/jsa.v5i10.1707.
Li, Pengzhi, Baijuan Li, and Zhiheng Li. ‘Sketch-to-Architecture: Generative AI-Aided Architectural Design’. arXiv:2403.20186. Preprint, arXiv, 29 March 2024. https://doi.org/10.48550/arXiv.2403.20186.
Maheswari, Hafizha Rasendriya, and Vera Sylvia Sitio. Sustainable Human Capital for Gen Z: The AMO Model Approach in the Disruption Era. 1 (2025).
Purwanto, Ratih Dian, and Astrid Hapsari. Artificial Intelligence Dalam Perancangan Arsitektur. Universitas Katolik Soegijapranata, 2026. https://www.unika.ac.id/buku/artificial-intelligence-dalam-perancangan-arsitektur/.
Satria, Andy, Aadiyaat Pariccar Sinambela, and Raihan Apriansyah Irhami. ‘Pengaruh Software Arsitektur Berbasis AI Terhadap Proses Desain dan Pembelajaran’. DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY 4, no. 2 (2023): 218–27. https://doi.org/10.46576/device.v4i2.4107.
Suwindia, I. Gede, and Ni Nyoman Kurnia. Kinerja Pegawai. 1. Mpu Kuturan Press, 2021. https://siska.stahnmpukuturan.ac.id/repository/197611292001121002_2001.pdf.
Wicaksana, Gde Bagus Andhika, and Peter Ardhianto. ‘Peran AI Dalam Tahapan Ideasi Konsep Arsitektural’. JoDA Journal of Digital Architecture 4, no. 2 (2025): 51–61. https://doi.org/10.24167/joda.v4i2.12959.
Published
2026-10-21
How to Cite
PRIATKO, Alberta Agnelia; SANJAYA, Ridwan. Analisis Pengaruh Penggunaan AI Image Generator terhadap Kinerja Karyawan Tim Desain Indra Group Semarang. Otonomi, [S.l.], v. 26, n. 2, p. 259-269, oct. 2026. ISSN 2657-1684. Available at: <https://ejournal.uniska-kediri.ac.id/index.php/otonomi/article/view/9499>. Date accessed: 09 nov. 2026. doi: https://doi.org/10.32503/otonomi.v26i2.9499.
Section
Articles