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In recent years, cloud computing has emerged as a promising paradigm providing various resources in the Cloud Data Center (CDC), including computations, storage, and even platform as a service. The virtualization technology plays a pivotal role in CDC resources management and provides an enchanting feature of virtual machine (VM) migration which provides several benefits in terms of VM scheduling, fault tolerance, load balancing, energy efficiency, power management, and security. To achieve efficient VM migration, a plethora of VM migration schemes have been proposed in the literature aiming to serve the quality of service-driven user requirements. This paper surveys the most recent and state-of-the-art Artificial Intelligence (AI) based and conventional load balancing, energy-aware, SLA aware, and network-aware live VM migration schemes. Through an extensive literature review, this paper investigates the most critical aspects of conventional and AI-driven live VM migration schemes. Finally, a few open research challenges that require further consideration from the research community are highlighted. [Display omitted] • Overview of cloud computing, data centers, virtualization, and VM migration. • Conventional and AI-based Live VM migration schemes categorization. • Live VM migration survey of load, energy, SLA, and network schemes. • VM migration analysis based on migration cost and AI benefits and drawbacks. • Live VM migration research challenges and future directions. [ABSTRACT FROM AUTHOR]