Authors : Võ Thị Thu Hồng; Vũ Kiều Sa

Volume/Issue : Volume 11 - 2026, Issue 8 - August

Google Scholar : https://tinyurl.com/mwrdayzn

Scribd : https://tinyurl.com/327uav9n

DOI : https://doi.org/10.38124/ijisrt/26aug789

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Purpose – This study investigated how a maritime logistics firm in Vietnam could develop organizational readiness for the responsible use of artificial intelligence (AI) in compliance risk management. It addressed three connected questions: which compliance risks should be prioritized, what organizational conditions constrain AI adoption, and which implementation sequence is feasible for a resource-conscious firm. Design/methodology/approach – An applied qualitative single-case design was used at TRA-SAS. Evidence comprised three semi-structured interview sessions involving eight participants from leadership and key functional areas, internal process and business documents, public corporate reports for 2021–2025, and a 5 × 5 risk-assessment matrix. Thematic analysis was combined with a purpose-specific AI-readiness assessment covering data, technology, people, processes, finance, leadership, compliance culture, and security/legal governance. Findings – Eight material compliance risks were identified. Customs compliance (CR04) received the highest priority within the portfolio (likelihood 3, impact 5, score 15; High). The firm displayed an uneven M2–M3 digital-maturity profile: software and selected processes were near M3, while data standardization and system integration remained closer to M2. High-value AI opportunities were document checking, contract and obligation analysis, regulatory change monitoring, early-warning analytics, and compliance reporting. However, these use cases depended on data governance, standardized workflows, role clarity, human review, and model monitoring. Originality/value – The study connects compliance-risk materiality with purpose-specific AI readiness in an under-researched maritime logistics setting. It proposes a risk-first, readiness-gated, human-in-the-loop pathway that avoids treating AI adoption as a technology procurement decision.

Keywords : Artificial Intelligence; AI Readiness; Compliance Risk; RegTech; Maritime Logistics; Responsible AI; Vietnam.

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