###### Abstract  
The advent of sixth-generation (6G) networks promises revolutionary advancements in wireless communication, marked by unprecedented speeds, ultra-low latency, and ubiquitous connectivity. This research paper delves into the integration of Artificial Intelligence (AI) in 6G network applications, exploring the challenges and outlining future directions for this transformative synergy. The study investigates the key AI technologies for 6G: the potential of AI to optimize network performance, enhance user experience, and enable novel applications in diverse domains and AI-enabled applications. Analyzing the current landscape, the paper identifies key challenges such as scalability, security, and ethical considerations in deploying AI-enabled 6G networks. Moreover, it explores the dynamic interplay between AI and 6G technologies, shedding light on the intricate relationships that underpin their successful integration. The research contributes valuable insights to the ongoing discourse surrounding the convergence of AI and 6G networks, laying the groundwork for a robust and intelligent future communication infrastructure. The envisioned applications of 6G are extensive and revolutionary, potentially transforming sectors such as transportation with real-time, secure, and ultra-low latency connections for autonomous vehicles and trains. These advancements leverage high-speed adaptive networks, particularly in the terahertz band, for critical and aggregate data transmissions [1]. The introduction of 6G technology promises unprecedented speeds, minimal latency, and transformative possibilities in wireless communication. Achieving these goals requires cutting-edge technologies, including terahertz band communication for high-frequency electromagnetic wave utilization, seamless integration of terrestrial and satellite networks for global coverage, and AI-driven network management for adaptive resource allocation and enhanced service optimization. Sustainability will be ensured through energy-efficient designs, supporting massive connectivity without compromising energy resources. New communication paradigms, such as ambient backscatter communications and quantum communication for enhanced security, will further augment 6G capabilities [2]. AI-enabled 6G networks are expected to deliver ultra-low latency, extensive connectivity, and enhanced reliability, supporting advanced applications across smart cities, autonomous vehicles, industrial automation, and healthcare. The integration of AI facilitates intelligent decision-making, real-time data processing, and network optimization, addressing current IoT limitations and paving the way for more efficient and resilient systems. However, achieving AI-enabled 6G IoT networks involves overcoming challenges such as developing advanced algorithms, enhancing data handling capabilities, ensuring robust security measures, and addressing ethical and societal concerns related to privacy and digital equity. This paper stands out from existing review papers by providing a holistic view of the synergy between AI and 6G within the IoT ecosystem. Unlike other reviews, we offer a detailed analysis of key enabling technologies such as edge computing and intelligent reflecting surfaces, and we identify unique opportunities arising from this convergence, including ultra-reliable low-latency communications and enhanced data analytics. Our comprehensive discussion on the multifaceted challenges--technical, regulatory, and ethical--along with a forward-looking research roadmap, provides strategic guidance for future developments. Further, our interdisciplinary approach integrates insights from telecommunications, computer science, and data science, ensuring a well-rounded understanding of the subject. This comprehensive, nuanced, and forward-looking perspective sets our review apart from the more generalized or narrowly focused existing literature.