A news summary based solely on the provided article body: The automotive industry is evolving into a more connected, software-defined future, creating a challenge for OEMs as vehicles become reliant on real-time diagnostics, OTA updates and always-on connectivity. Connected vehicles are creating a visibility problem, as data is fragmented across different systems, partners and operational teams, making it difficult to identify root causes of issues. AI can help OEMs move from reactive troubleshooting to proactive, data-led decision-making by analysing patterns across multiple sources. The article proposes an AI maturity model for connected vehicle operations, analogous to driving automation levels. At Level 0, OEMs rely on manual investigation. At Levels 1 and 2, AI assists by identifying patterns and recommending causes. By Level 3, AI takes the lead on specific tasks with human supervision. Levels 4 and 5 represent the goal of highly automated and eventually autonomous operations. Progress will come from building confidence in specific use cases such as diagnostics, OTA assurance, anomaly detection and connected service monitoring.