Alert fatigue is a significant issue for DevOps teams, characterized by an overwhelming number of alerts, most of which are non-essential, leading to desensitization and delayed responses to critical incidents. This challenge can be mitigated through AI-driven strategies and improved alert management practices. Key problems include over-sensitive static thresholds, duplicate monitoring tools, poor prioritization, lack of contextual information, and noisy alert patterns. Solutions involve using dynamic baselines for threshold tuning, implementing tiered escalation policies, consolidating alerts via correlation engines, and automating routine remediation steps. AI enhancements such as contextual pre-investigation and predictive anomaly detection can make alerts more actionable, while maintaining transparency and human oversight is crucial to build trust. Sustainable alert management requires continuous auditing and a focus on improving the signal-to-noise ratio, which should be complemented by team wellness practices to prevent burnout. Integrating AI into communication workflows and conducting post-incident learning can further optimize incident response and maintain team health.