An Ambidextrous AI Governance Framework for Smart Cities to Enhance IT Governance and Data Security

Authors

  • Agustinus Fritz Wijaya University of Bunda Mulia image/svg+xml
  • A’ang Subiyakto UIN Syarif Hidayatullah
  • Adhe Ronny Julians Amamapare Polytechnic, Timika
  • Merryana Lestari University of Bunda Mulia image/svg+xml
  • Gloria Batseyba Warella University of Bunda Mulia image/svg+xml

DOI:

https://doi.org/10.55826/jtmit.v4i2.1082

Keywords:

Ambidextrous AI, Smart City, COBIT 2019, IT Governance

Abstract

This study proposes an ambidextrous AI governance framework grounded in COBIT 2019 to guide the deployment of artificial intelligence in smart city infrastructures while ensuring robust IT governance and data security. The framework blends exploration‑exploitative governance strategies to support innovation in smart urban management, while maintaining accountability, risk control, and regulatory compliance. State‑of‑the‑art review includes AI governance adaptations of COBIT 2019. The study achieved measurable improvements in governance maturity, with notable increases such as a 69.2% enhancement in DSS05 (Manage Security Services) and a 60.7% improvement in APO12 (Managed Risk). The literature review was based on a targeted analysis of peer-reviewed sources published between 2020 and 2025, ensuring relevance to AI governance in smart cities. Keywords are arranged from general to specific to improve indexing and clarity: AI Governance, Smart Cities, COBIT 2019, Ambidextrous Governance, Data Security.

References

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Published

17-08-2025

Issue

Vol. 4 No. 2 (2025): Jurnal Teknologi dan Manajemen Industri Terapan

Section

Articles

License

Copyright (c) 2025 Agustinus Fritz Wijaya, A’ang Subiyakto, Adhe Ronny Julians, Merryana Lestari, Gloria Batseyba Warella

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
“An Ambidextrous AI Governance Framework for Smart Cities to Enhance IT Governance and Data Security”, JTMIT, vol. 4, no. 2, pp. 530 – 537, Aug. 2025, doi: 10.55826/jtmit.v4i2.1082.