Systematic Literature Review tentang Transformasi Digital, Kesiapan Adopsi Artificial Intelligence, dan Produktivitas Kerja Pegawai - Rizka Nur Fitriana; Dewi Purnamawati (Lembaga Yasin AlSys, 2026)
Although digital transformation and the adoption of Artificial Intelligence (AI) have the potential to improve employee productivity, their implementation continues to face organizational resistance, limited human resource readiness, and the risk of dependence on AI, which may weaken critical thinking skills. This study aimed to synthesize empirical evidence regarding the effects of digital transformation and AI adoption readiness on employee productivity and identify research gaps relevant to the context of the Direktorat Produksi dan Distribusi Farmasi. The study employed a Systematic Literature Review (SLR) method based on the PRISMA 2020 guidelines. Articles were retrieved from Scopus, ScienceDirect, PubMed, Google Scholar, and Garuda and subsequently selected according to predetermined inclusion criteria. A total of 20 articles were analyzed using narrative synthesis through the stages of comparison, grouping, and integration of findings. The results showed that AI implementation consistently contributed to increased employee productivity, including accelerating document retrieval processes by up to 60% and increasing job satisfaction by 51%. However, excessive dependence on AI was negatively correlated with critical thinking skills. The success of AI implementation was also determined by human resource readiness, technology acceptance, an inclusive organizational culture, and ethical governance. These findings confirm that the use of AI can improve organizational productivity when supported by the digital capabilities of human resources and adequate governance. This study contributes to the development of research on digital transformation and AI adoption readiness and provides practical implications for the Direktorat Produksi dan Distribusi Farmasi and other public-sector organizations to strengthen digital competencies, organizational readiness, and ethical AI adoption policies.