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Automotive & Mobility AI Strategy: opportunities, use cases & the operating model
Beyond ADAS hype, AI value concentrates in warranty and quality analytics, connected-vehicle software monetisation, and manufacturing yield, reshaping the economics of the vehicle across its lifecycle.
Where AI creates value
ADAS and autonomyPerception and planning stacks for driver assistance
Connected-vehicle dataFleet telemetry monetised via features and services
Warranty and qualityEarly defect detection from field failure signals
Manufacturing yieldBody-in-white and paint-shop defect reduction
Battery and powertrainState-of-health prediction for EV cells
Aftersales and dealerPredictive parts demand and service routing
Top AI use cases
- Warranty claim clustering to isolate emerging component defects pre-recall
- Over-the-air software features personalised from connected-vehicle telematics
- EV battery state-of-health and range prediction from charge-cycle data
- Vision-based paint and weld inspection in body assembly
- Generative design and simulation for lightweighting and crash performance
What has to change (operating model)
- Software-defined vehicle governance separating hardware and OTA release cycles
- Functional-safety validation (ISO 26262, SOTIF) extended to learned models
- Vehicle data consent and privacy frameworks across connected-car estates
- Type-approval and homologation processes adapting to AI-driven ADAS updates
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