AI Governance for Sustainable Tech Adoption and Carbon Reduction in Smart Industries

Suryari  Purnama; Richard Andre  Sunarjo; Marviola  Hardini; Jonathan Parker

doi:10.34306/ajri.v7i2.1387

Authors

Suryari Purnama Universitas Esa Unggul https://orcid.org/0000-0002-7872-2869
Richard Andre Sunarjo Universitas Pelita Harapan https://orcid.org/0009-0007-7349-2375
Marviola Hardini Sundara Sejahtera Indonesia https://orcid.org/0000-0003-3336-2131
Jonathan Parker Rey Incorporation https://orcid.org/0009-0000-8585-3245

DOI:

https://doi.org/10.34306/ajri.v7i2.1387

Keywords:

AI Governance, Sustainable Technology, Carbon Reduction, Smart Industries, Digital Transformation

Abstract

Rapid advancements in Artificial Intelligence (AI) and sustainable technologies are transforming smart industries, yet many organizations still struggle to establish governance mechanisms that ensure responsible adoption while contributing to carbon-reduction objectives. This study aims to examine how AI governance frameworks support sustainable technology adoption and promote carbon reduction across smart industrial environments. Using a mixed-methods research design, the study integrates a systematic literature review, expert interviews, and quantitative assessment of governance maturity to explore the relationship between governance structures, sustainability practices, and emission reduction outcomes. The empirical data were collected through semi-structured expert interviews and a structured survey involving 150 professionals from manufacturing, logistics, and energy sectors, representing managerial, technical, and governance roles within smart industry environments. The findings reveal that AI governance significantly enhances the effectiveness of sustainable technology deployment, particularly through standardized accountability mechanisms, transparent decision-making models, and proactive risk-management protocols. Organizations with higher governance maturity not only adopt sustainable technologies more efficiently but also demonstrate measurable decreases in operational carbon intensity. These results suggest that robust AI governance serves as a critical enabler for sustainable industrial transformation, ensuring that AI driven innovations align with environmental objectives and long-term strategic value. The study concludes that strengthening AI governance frameworks can accelerate responsible technology integration in smart industries, offering practical pathways for carbon reduction and sustainable competitiveness. Future research is encouraged to investigate cross-industry implementation models and develop governance metrics that better capture environmental impacts in evolving digital ecosystems.

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