With the rapid advancement of artificial intelligence technologies, the public sector stands at the threshold of a fundamental transformation in employment patterns, service delivery, and governance paradigms. This study aims to systematically identify opportunities and challenges, and to formulate practical strategies for the application of artificial intelligence in the future of work within the public sector. The research methodology is grounded in systematic literature review (SLR) and qualitative content analysis of internationally recognized studies — including OECD reports — and relevant policy documents. Data were collected from credible scientific databases, including Scopus, SID, and Google Scholar. Findings indicate that artificial intelligence, through the automation of repetitive processes, enhanced decision-making via big data analytics, and the personalization of public services, has generated unprecedented opportunities for improving governmental efficiency and effectiveness. However, significant challenges were also identified, including ethical concerns (algorithmic bias and transparency), organizational resistance to change, a shortage of digital skills in the workforce, and risks pertaining to data privacy and cybersecurity. In response to these challenges, macro-level strategies are proposed, encompassing the development of ethics-based AI governance frameworks, investment in data and technological infrastructure, the design of long-term employee training and reskilling programs, and the implementation of experimental (pilot) policies. By offering an integrated perspective, this article assists policymakers and public sector managers in leveraging the opportunities presented by artificial intelligence, mitigating its adverse consequences, and facilitating the transition toward a smart and resilient government.