Artificial Intelligence Driven Smart Office: Enhancing Employee Efficiency and Productivity in the Age of Machine Autonomy
Abstract
Digital transformation is accelerating the adoption of smart offices powered by Artificial Intelligence (AI) and the Internet of Things (IoT) to enhance operational efficiency and employee productivity. This study examines the level of AI adoption, patterns of use, and employee perceptions regarding comfort and the perceived importance of AI in supporting workplace performance. A descriptive approach was applied through a literature review and a 5 point Likert based questionnaire. Primary data were collected from 28 respondents using convenience sampling and analyzed descriptively with Microsoft Excel. The findings show that 46.4% of respondents work in offices without AI, 32.1% in offices that already implement AI, and 21.4% in offices with potential adoption. AI usage is mostly occasional (46.4%), while 21.4% report never using it. The mean scores for comfort working alongside AI and the perceived importance of AI are both 3.75 (on a 1-5 scale), indicating a generally positive attitude despite limited adoption. The study concludes that AI driven smart offices have the potential to improve efficiency and productivity, but further advancements in digital literacy, employee training, and infrastructure readiness are needed. Practical recommendations and avenues for future research are provided to encourage broader and more responsible adoption.
References
Artificial Intelligence Support System Design for Smart Offices. (2023). Proceedings of ICEARS 2023. https://doi.org/10.1109/icears56392.2023.10085205
Bin Masud, S., Chowdhury, S., Abubakkar, M., Sozib, H. M., Bellal, R. B., Hoque, A., & Bin Shafi, S. (2025). The revolution of AI in enhancing infrastructure and facilities management. Business & Management Journal, 54(4), 5605–5624. https://doi.org/10.48047/bb97xk66
Challenges and opportunities involved in implementing AI in workplace. (2023). International Journal for Multidisciplinary Research. https://doi.org/10.36948/ijfmr.2023.v05i06.10001
Chaniago, H. (2025). Manajemen kantor kontemporer (Edisi 2). Politeknik Negeri Bandung.
Chaniago, H., & Efawati, Y. (2026). Individual absorptive capacity as a stepping stone for digitalization, digital transformation, and small business performance; Entrepreneurial perspectives. Contaduría y administración, 71(2), 1-36.
Chaniago, H., Hidayat, H., & Efawati, Y. (2025). Intrinsic Motivation and the Use of Artificial Intelligence (AI) in the Public Sector: Evidence from Indonesia. Revista Brasileira de Políticas Públicas, 15(2).
Chaniago, H., & Efawati, Y. (2024). Individual Innovative Behavior Model: The Role of Entrepreneurial Leadership in Uncertain Times. Quality-Access to Success, 25(202).
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., & Kar, A. K. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Efawati, Y. (2023). Trust as Antecedent of Innovative Behavior in the Workplace. International Journal Administration, Business & Organization, 4(3), 35-47. https://doi.org/10.61242/ijabo.23.381
Efawati, Y. (2024). Peran Budaya Digital dan Kreativitas terhadap Kinerja Karyawan: Apakah Krusial Bagi Perusahaan?. Jurnal Akuntansi Keuangan dan Bisnis, 17(2), 139-150.
Efawati, Y., Ahman, E., & Chaniago, H. (2021, September). The effect of entrepreneurial leadership on firm innovation through innovative work behavior. In 5th Global Conference on Business, Management and Entrepreneurship (GCBME 2020) (pp. 188-194). Atlantis Press. https://doi.org/10.2991/aebmr.k.210831.037
Efawati, Y., Rachman, A., Andriani, R., & Veranita, M. (2025). Digital Transformation and Organizational Resilience: The Mediating Role of Digital Literacy. International Journal Administration, Business & Organization, 6(3), 457-471.
Efawati, Y., & Rinawati, R. (2026). Digital Transformation And Sustainability: Is Peer-To-Peer Lending A Solution?. Riset: Jurnal Aplikasi Ekonomi Akuntansi dan Bisnis, 8(1), 054-071.
Exploring the impact of artificial intelligence on employee productivity. (2025). REST Journal on Banking, Accounting and Business, 4(2), 43–46. https://doi.org/10.46632/jbab/4/2/6
Garg, R., Jagan, S., Singh, P., Rawat, R., Kaliappan, S., & Manikandan, G. (2025). Interactive system for smart workplace management with environmental sensors and employee tracking. https://doi.org/10.1109/incet64471.2025.11140066
Gatea, A. H., Al-Ibadi, A., & Alaziz, M. (2024). Optimizing workplace performance by using ESP32 to monitor and enhance environmental quality in smart office solutions. Advanced Engineering, Physics & Computer Science Review, 1(1), 31–37. https://doi.org/10.64820/aepjcser.11.31.37.122024
Generative AI at work. (2023). https://doi.org/10.48550/arxiv.2304.11771
Gowda A. G., A., Su, H.-K., & Kuo, W.-K. (2023). Unleashing potential of employees through artificial intelligence. ECBIOS Proceedings, 204–206. https://doi.org/10.1109/ecbios57802.2023.10218636
Hadi, S., Purnasari, E., Hidayat, R., Lukitaningsih, A., Kirana, K. C., & Siripipatthanakul, S. (2025). Challenges and management practices in protecting employee personal data in the digital era. In Digital Transformation and Security (pp. 89–116). https://doi.org/10.4018/979-8-3693-97206.ch004
Kayyali, M. (2025). Ethical AI and automation in the workplace. In Responsible AI Practices (pp. 103–138). https://doi.org/10.4018/979-8-3373-5127-8.ch004
Komalasari, D. D. N., Rachmawati, S. S., & Chaniago, H. (2025). Efisiensi energi kantor berbasis artificial intelligence (AI) dan Internet of Things (IoT) pada perguruan tinggi vokasi. Nusantara: Jurnal Ilmu Pengetahuan Sosial, 12(6), 2510–2516.
Ndaguba, E., & Arukwe, C. (2024). Ecosystem of smart spaces: An overview review. In Smart Space Technologies (pp. 139–166). https://doi.org/10.1016/b978-0-443-13462-3.00010-8
Ramya, S. S., Saikrishnan, S., Sumathi, S., Kamalakannan, S., Keerthana, J., & Indhumathi, G. (2024). Optimizing the strategic fusion of IoT and AI for enhanced HR performance in stocks. ICCPCT Proceedings, 697–702. https://doi.org/10.1109/iccpct61902.2024.10673028
Rk, K., & Mk, S. (2024). Exploring the role of technology in enhancing organisational productivity. Shanlax International Journal of Management. https://doi.org/10.34293/management.v11is1mar.7994
Shrestha, Y. R., Krishna, V., & von Krogh, G. (2021). Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges. Journal of Business Research, 123, 588–603. https://doi.org/10.1016/j.jbusres.2020.09.068
Shrivastava, A. (2024). Artificial intelligence (AI): Evolution, methodologies, and applications. International Journal for Science Technology and Engineering, 12(4), 5501–5505. https://doi.org/10.22214/ijraset.2024.61241
Suram, R. (2024). Integration of emerging technologies for business workflow optimization: A systematic analysis of IoT, AI, and blockchain solutions. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(6), 1995–2003. https://doi.org/10.32628/cseit2410612390
Technology Assisted Smart and Sustainable Workspace. (2023). https://doi.org/10.1109/icoei56765.2023.10126000
The Intersection of AI and Employees: Evolutionary Trends in Research. (2025). Revista de Management Comparat Internaţional, 26(1). https://doi.org/10.24818/rmci.2025.1.46
Ulla, M. M., Preethi, P., & Sapna, R. (2024). A role of AI and IoT in building smart office. In Smart Computing Advances (pp. 107–116). https://doi.org/10.58532/nbennurcech11
Wójcik, M. (2025). AI meets HR – Systematic review of implementation and operational barriers. Zeszyty Naukowe, 224, 643–660. https://doi.org/10.29119/1641-3466.2025.224.35
Copyright (c) 2026 Fazril Muhamad Mursyidhan, Rakha Yathaqi Witsqa
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish in this journal agree to the following terms:
- The authors confirm that they are the authors of the submitted article, which will be published (online) in the journal IJABO (International Journal Administration, Business & Organization) by the Asosiasi Ahli Administrasi Indonesia (A3i), Bandung, Indonesia. The author’s name will be evident in the article. The publisher makes all decisions regarding the layout and distribution of the work.
- Authors guarantee that the work is their own original creation and does not infringe any statutory or common-law copyright or any proprietary right of any third party. In case of claims by third parties, authors commit themself to defend the interests of the publisher and shall cover any potential costs.
- Authors retain copyright and grant the journal the right of first publication, with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). This license allows the redistribution and reuse of papers provided the authorship is properly credited.
- Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., posting it to an institutional repository or publishing it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as this can lead to productive exchanges and earlier and greater citations of published work.
