As vehicles become more complex and fully connected, it is imperative that the industry identify new techniques and AI solutions to deliver value throughout the entire lifecycle of the vehicle. Within the automotive ecosystem, we now have the ability to detect anomalous behavior from extremely complex time-series data to identify defects and failures, before they happen. In this presentation, we will explore multiple use cases where AI can be leveraged to find meaningful patterns in connected data to aid quality, manufacturing, engineering and after-sales organizations. Off-the-shelf AI tools are not designed for time-series analytics, so we will go deeper into the importance of utilizing an unsupervised AI approach to deliver the insights needed for successful deployments within the industry