Acinetobacter baumannii (A. baumannii) is a Gram-negative, nonfermenting bacterium implicated as a major cause of opportunistic infections in healthcare settings because it is a multidrug-resistant organism. Tigecycline was developed to circumvent the prevalent mechanism of A. baumannii resistance against tetracycline. This study aims to determine the frequency of tigecycline resistance and to characterize the tigecycline-resistant tet(Y), tet(X), and tet(A) genes in A. baumannii clinical isolates. A descriptive cross-sectional study was conducted at Lahore General Hospital (LGH), Lahore, Pakistan, from February 2023 to February 2024. A total of 195 A. baumannii samples were isolated from various samples collected from patients admitted to the intensive care unit of LGH over a period of 1 year. The antimicrobial susceptibility of A. baumannii was assessed using the Kirby-Bauer disc diffusion assay, and the results were reported according to the Clinical and Laboratory Standards Institute 2022 guidelines. The activity of tigecycline was reported according to the British Society for Antimicrobial Chemotherapy 2021 guidelines. The detection of tigecycline resistance genes tet(Y), tet(X), and tet(A) was performed using polymerase chain reaction, and the amplified products were confirmed using Sanger sequencing. Acinetobacter baumannii were resistant to multiple antibiotics. Minocycline was the most effective antibiotic, with 10.8% resistance, whereas cefotaxime was the least effective, with 74.4% resistance in 195 isolates of A. baumannii. Resistance to tigecycline was detected in 9% of isolates of A. baumannii. The tet(A) gene was the most frequently found gene, present in 20% of the tigecycline-resistant isolates, followed by tet(X) and tet(Y) genes in 18% and 9% of isolates, respectively. A high frequency of plasmid-mediated tigecycline resistance was detected in A. baumannii samples, with a high prevalence of tet(Y), tet(X), and tet(A) genes. This emphasizes the need for antibiotic stewardship, the detection of resistance profiles, and understanding underlying molecular mechanisms to plan clinical management effectively.