Antimicrobial resistance (AMR) has escalated into a severe global health threat, disproportionately burdening low- and middle-income countries like Ghana. This study is crucial for advancing precision public health by evaluating the role of genomic surveillance in tracking AMR dynamics across Ghana from 2020 to 2024. Using a descriptive, retrospective design, data were extracted from clinical, environmental, and veterinary sources (n=105), analyzed through ANOVA, regression, chi-square, and correlation techniques. Findings revealed significantly higher resistance rates in urban clinical settings (65%) versus rural (45%), with overall AMR prevalence at 57%. Environmental and animal sources showed ARG prevalence at 33% and 27%, respectively (F=19.44, p<0.001), while surveillance effectiveness improved with timeliness (from 10 to 5 days) and coverage (60% to 80%) (Wilks’ Lambda = 0.303, F=48.77, p<0.001). Crucially, a Pearson correlation of r = -0.92 (p<0.001) confirmed that increased genomic surveillance intensity strongly inversely relates to AMR rates, with the regression model (R² = 0.85) explaining 85% of the variance in AMR reduction. These findings highlight that surveillance is not merely observational but a transformative intervention. Policy implications call for expanded surveillance infrastructure, antibiotic stewardship, and One Health integration. The study recommends prioritizing surveillance in low-income, high-risk zones and embedding genomic insights into national health strategies for effective AMR control.