Journal of Information Technology Review M. Krishnamurthy 17 2 2026 https://doi.org/10.6025/jitr/2026/17/2/43-64 https://www.dline.info/jitr/fulltext/v17n2/jitrv17n2_1.pdf This study investigated the emergence of generative artificial intelligence as a vector for misinformation during heightened US-Iran geopolitical tensions, drawing on a systematic analysis of The New York Times investigative report (March 2026). We analyzed 110+ verified AI-generated visual media items identified within the initial fourteen-day escalation period, employing a multi-layered verification framework encompassing visual forensics, digital watermark analysis, algorithmic detection, and cross-referencing with authoritative sources. Results reveal pronounced narrative asymmetry, with approximately 78% of content advancing a pro-nation strategic framing across five thematic categories: civilian targeting, military fabrications, infrastructure damage, symbolic propaganda, and event re-enactments. Aggregate viewership exceeded several million impressions across public platforms, with propagation dynamics aligning with epidemic diffusion models characterized by high infection rates and low recovery rates. Comparative forensic analysis identified consistent differentiators between synthetic and authentic footage, including cinematic exaggeration, symbolic artefacts, and physical inconsistencies in AI-generated content. Evaluation of mitigation strategies indicates that cross-verification with trusted sources remains the most reliable, while platform-level interventions have proven heterogeneous and largely reactive. Modeling using SIR, SEIR, and rumor-propagation frameworks quantifies the viral potential of emotionally charged conflict visuals and the impact of network structure on dissemination. These findings establish generative AI as an operationalized force multiplier in cognitive warfare, underscoring urgent needs for hybrid detection approaches, proactive platform governance, and coordinated policy responses to preserve informational integrity in algorithmically mediated conflict environments.