This talk demonstrates how artificial intelligence can be harnessed to analyze online discussions in real time, providing actionable insights for crisis communication. The presentation outlines a workflow in which data is continuously gathered from social media platforms, video sites, and news feeds. Advanced natural language processing techniques are then applied to detect sudden surges in topic mentions, map shifts in public sentiment, and identify dominant narratives without manual intervention. Misinformation detector highlights emerging rumors that require rapid correction.

Through illustrations across multiple crisis scenarios such as natural disasters, public health threats, and geopolitical events the talk shows how an AI‑powered dashboard can visualize trending concerns, emotional tone changes, and disinformation hotspots. The session advocates for organizations and governments to integrate such systems into their crisis protocols, enabling teams to anticipate public anxieties, tailor messages dynamically, and allocate resources more effectively. Attendees will gain a practical framework for designing the necessary data pipelines, deploying sentiment and topic analysis at scale, and embedding real‑time monitoring into existing communication strategies.