The decreased mortality of people living with HIV (PLWH) has revealed non-HIV-associated comorbidities such as neurocognitive disorders (e.g., dementia). There is an urgency to discover therapeutics to prevent or delay neurocognitive decline among PLWH. The artificial intelligence platform Automatic Graph-mining And Transformer based Hypothesis Generation Approach (AGATHA) was utilized to seek potential drugs to be repurposed for the management of non-HIV-associated dementia. AGATHA revealed angiotensin-converting enzyme inhibitors that cross the blood-brain barrier (BBB ACEi) as a target for decreasing dementia. Subsequently, we conducted a retrospective study evaluating incident dementia using the VA Informatics and Computing Infrastructure (VINCI) evaluating ACE inhibitors. Cox proportional hazards models were fit and hazard ratios (HR) with corresponding 95% confidence intervals (CIs) are presented. A total 9,419 PLWH exposed to an BBB ACE inhibitor (ACEi) and 8,831 PLWH unexposed demonstrated that PLWH exposed to BBB ACEi had a 21.4% (univariate) and 15.2% (multivariate) lower hazard of dementia. The propensity score matched analysis demonstrated a 14.3% lower hazard of incident dementia compared to BBB ACEi unexposed (HR 0.857, 95% CI 0.747-0.984). An artificial intelligence-based literature mining system (AGATHA) was utilized to uncover a medication with potential to be repurposed. AGATHA demonstrated that BBB ACEi as a target for decreasing dementia among PLWH. Additionally, we conducted a retrospective study demonstrating a decrease in incident dementia among PLWH exposed to BBB ACEi. Future research is needed to explore further and understand the relationship of dementia among PLWH exposed to ACEi.