The adoption of Artificial Intelligence (AI) in the public sector has accelerated rapidly, challenging public managers (PMs) to adapt to emerging technologies like Generative AI (GenAI). Despite limited training, PMs face weekly technological advancements and increasing pressure to implement AI solutions. This chapter examines how PMs navigate this fast-changing landscape and the evolving role they play when using GenAI technologies. The central question guiding this chapter is: To what extent can evidence-based practical principles be developed to guide public servants in the implementation and operational governance of generative AI technologies, given the current state of technological development and public sector constraints? Building on sociotechnical theory, I examine strategies for introducing generative AI to public managers and offer a set of guiding principles for its effective implementation within government operations. The framework addresses the unique challenges of public sector AI adoption, including technical constraints, organizational readiness, and ethical considerations specific to government contexts. By identifying best practices and potential pitfalls, this chapter provides a structured approach for PMs to evaluate, implement, and govern GenAI applications. The proposed framework supports a more informed, responsible, and effective adoption of AI technologies in the public sector.