As virtualization becomes a fundamental component of modern IT infrastructure, digital forensics should adopt challenges created by virtual environments. Traditional forensic methods, such as disk imaging and OS-based memory forensics, often fail in virtualized settings due to their dependence on direct systems access, which can change evidence and disrupt operation. The Virtual Machine Introspection (VMI) provides a non-intrusive, hyper-level approach to forensic data acquisition, which enables investigators to analyze memory, disks, and network activities without interfering with the internal state of the virtual machine. This paper reviews VMI-based forensic techniques, which compare them with traditional methods in the context of infiltration, system disintegration, detection capacity, scalability, and legal acceptance. While VMI excels in the detection of rootkits, stealth malware, and live memory forensics, it introduces computational overheads and hypervisor-specific implementation challenges. In addition, the paper discussed automation through forensic integrity verification, detection of AI-operated discrepancies, cross-platform governance, and legal compliance in VMI-based inquiry. The study highlights the importance of VMI in modern forensic workflows, which ensures scalability, efficiency, and legal reliability in cloud and virtual infrastructure.