The integration of Artificial Intelligence (AI) into wireless energy transmission systems within smart cities represents a transformative shift in how urban environments manage and distribute energy. This technological evolution, driven by AI, aims to optimize energy usage, enhance grid efficiency, and reduce environmental footprints. However, the implementation of AI-powered wireless energy transmission brings with it complex accounting implications that require careful consideration by businesses, municipalities, and stakeholders. This explores the financial and accounting considerations associated with leveraging AI to enhance incentives for wireless energy transmission. It delves into the costs associated with adopting AI technologies, including capital investments in infrastructure, software, and the operational expenses for system maintenance and upgrades. Additionally, the impact of governmental and corporate incentives, such as tax credits and subsidies, is examined to understand how they influence the financial viability and attractiveness of these technologies for stakeholders. Revenue recognition models are explored, particularly in the context of dynamic pricing, energy savings, and usage-based billing enabled by AI. This further discusses the accounting treatment of incentives offered by governments and corporations, along with the financial reporting requirements surrounding these incentives. It emphasizes the importance of transparent reporting practices, the valuation of AI systems, and the implications of financial risk management due to uncertainties related to AI adoption, such as technical failures, cybersecurity risks, and energy market volatility. Ultimately, the study concludes by outlining the long-term financial sustainability of AI-driven wireless energy systems and the need for forward-looking accounting strategies to ensure successful integration within smart city infrastructures. By addressing these accounting implications, the review provides valuable insights for entities investing in AI-powered energy solutions to balance financial goals with the environmental and economic objectives of smart cities.