A scalable data and AI Foundation for Mercedes-Benz by Arinti & Hyperion

From AI initiatives to a scalable foundation

The Mercedes-Benz Customer Assistance Center had already put money into modern data platforms and AI projects. These projects included agent assistance, multilingual routing, and automated classification. The next challenge was to establish the organizational and technical foundation needed to expand these capabilities and support its goal of becoming a global aftersales data domain within the Mercedes-Benz Group.

This required more than just selecting the right technology. Clear ownership, effective governance, consistent data quality, and

compliance needed to be part of the organization's operations.

Key takeaways

A clear data and AI strategy and governance model to scale across over 40 markets.

Strengthened data governance, quality, architecture and compliance across the delivery lifecycle.

Created a 12 to 24-month roadmap with quick wins to speed up implementation.

Mapping the current state

Arinti and Hyperion collaborated with business, IT,operations, and Intelligence and AI teams to evaluate the current situationconcerning people, processes, and technology.

Their assessment included data governance, data quality, technical architecture, AI readiness and compliance (GDPR, EU AI Act).Through in-depth workshops and validation sessions, the teams pinpointed the main gaps between the current state and the target state.

The outcome was a unified Data and AI alignment strategy, a gap analysis, and a hybrid governance model that combined SAFe delivery practices with Data Mesh principles.

Naturally, this all sounds very theoretical, which is why Arinti and Hyperion have provided a few concrete recommendations and quick wins. All of this is presented in a phased roadmap that can be followed step by step.

Three priorities for scaling Data and AI

The strategy targeted 3 areas to provide a foundation for sustainable growth:

1. A stronger organizational foundation

Clear ownership and responsibilities were set for data domains (instead of concentrated in a few roles) and embedding governance into planning and delivery.

2. Technical architecture in harmony

The strategy explained how to bring data platforms, ingestion, transformation, lineage, monitoring, and metadata together under consistent standards aligned with the broader Mercedes-Benz Group.

3. Embedding governance into delivery

Data quality and compliance became part of the delivery lifecycle, with measurement-driven approvals and automated quality gates included in the existing SAFe approach.

A roadmap ready for implementation

The engagement produced a practical strategy instead of a theoretical framework. Mercedes-Benz received a clear gap analysis, an alignment strategy between business and IT, a hybrid governance model, and a phased implementation roadmap.

The 12 to 24-month roadmap highlighted quick wins achievable in the first 6 months. This gave the CAC a clear path from strategy to execution.

With a stronger foundation for data governance, architecture, and AI readiness, the Mercedes-Benz Customer Assistance Center is now better prepared to scale its data and AI capabilities across its operations in over 40 markets.