AIOps, or Artificial Intelligence for IT Operations, is a type of AI specifically designed to assist IT operations by tracking data and finding patterns undetectable by the naked eye. It uses machine learning and natural language processing to support, streamline, and enhance common IT processes, providing predictive, actionable insights that can help improve efficiency and reduce downtime. AIOps tools can be domain-agnostic or domain-centric, depending on the scope of their use case. The benefits of AIOps include broader data collection, automatic data processing, more actionable data, faster root cause determination, lower mean time to resolution (MTTR), increased uptime, task automation, and lower operational costs. However, there are also potential drawbacks such as implementation complexity, high upfront cost, long-term maintenance, and the need for ongoing IT scoping and staffing considerations. AIOps can be implemented in various stages, from training to adaptation, and can be used in various use cases, including consolidating similar incidents, automating resolution suggestions, predicting future risks, root cause analysis, and automation of ticket responses. To implement AIOps, businesses should consult with their IT teams, find a product that fits their needs and growth projections, determine implementation capability, create a realistic plan and timeline for rollout, and demonstrate value to stakeholders.