Data und AI at Scale: Unlocking Innovation
summary
BMW describes a concrete stack: a decentralised data-exchange Kina X launched 2024 with >1,000 active partners and the largest fleet diagnostic transfer at 300 GB weekly, a central cloud data hub holding ~11,000 data assets and 2,300 use cases, and a deployed Group AI assistant (Feb launch) that supports 90,000 users, 40,000 monthly and has enabled 15,000 small AI apps. The platform uses mixed LLMs per region (different models in China), enforces metadata/ownership, and still faces integration patterns across many backend systems.
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chapters (12)
- 0:00BMW’s data and AI journey
- 2:13AI strategy across value chain
- 5:05Kina X data sharing
- 6:53Customer data access
- 7:35AI’s impact on innovation
- 8:18Three AI application pillars
- 9:44Integration challenges
- 10:27Global compliance and security
- 11:07Group AI assistant architecture
- 12:54AI platform use cases
- 14:42Platform metrics and governance
- 15:45Why in-house AI platform
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