Model Adopsi Kecerdasan Buatan (Ai) Berpusat pada Manusia untuk Kinerja Pelabuhan Berkelanjutan dan Pencapaian SDGS
DOI:
https://doi.org/10.30587/jurnalmanajerial.v13i03.12527Keywords:
Human-Centred AI, Human Resource Development, Employee Well-Being, Sustainable Port Performance, SDG'sAbstract
Background – Artificial intelligence (AI) offers ports substantial opportunities to improve vessel and berth scheduling, asset reliability, safety, energy efficiency, and emissions management. However, technology-centred implementation may also generate skills gaps, technostress, job insecurity, algorithmic distrust, and employee resistance, thereby limiting sustainable value creation.
Aim – This study develops an integrative human-centred AI adoption model linking AI readiness and algorithmic governance with human resource development, employee well-being, Green/Sustainable Human Resource Management (HRM), sustainable port performance, and the Sustainable Development Goals (SDGs).
Design / methodology / approach – An integrative literature review of international Scopus-indexed journal articles published in 2021–2026 was combined with VOSviewer-assisted bibliometric mapping and contextual interpretation of the Indonesian port ecosystem.
Findings – The synthesis indicates that AI improves operational, safety, environmental, and resilience outcomes when data interoperability, digital infrastructure, cybersecurity, auditability, and human-in-the-loop governance are reinforced by reskilling/upskilling, employee participation, AI self-efficacy, psychological safety, and Green/Sustainable HRM. Human resource development and employee well-being therefore function as organisational and psychological mechanisms through which AI readiness is converted into sustainable performance.
Conclusion – Sustainable AI adoption in ports is a socio-technical transformation rather than a purely technological upgrade. Its success depends on simultaneously creating organisational value and human value through responsible AI governance, workforce capability development, participatory work design, and protection of employee well-being.
Research implications – Ports should implement AI incrementally, integrate productivity, safety, environmental and well-being indicators, and align measurable outcomes with SDGs 3, 4, 8, 9, 12, 13, and 17.
Limitations – The proposed model is conceptual and relies on secondary evidence; its causal relationships and cross-port generalisability require longitudinal, multilevel, and empirical testing.
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