David Betzold, Enterprise AI Adoption & Transformation Advisor

Experience & Case Studies

The relevance of prior experience is not the number of sectors listed. It is repeated exposure to environments where change has to work across multiple teams, technologies, governance constraints and operational dependencies.

Automotive and manufacturing environments

Experience includes transformation work in automotive and manufacturing contexts where delivery spans multiple teams, technical dependencies and operational constraints.

Logistics and telecommunications environments

Work in logistics and telecommunications contexts brings experience with cross-functional coordination, service continuity, complex stakeholder networks and delivery systems that cannot be improved by changing one team in isolation.

Finance and insurance environments

Finance and insurance contexts add experience with governance-intensive change, accountability, risk-sensitive decision-making and the need to connect delivery improvement with organizational controls.

AI-enabled localization and production workflows

Experience also includes production environments where AI was already part of the work and human processes had to adapt around it – a useful practical reference point for questions of adoption, workflow redesign, quality control and human accountability.

Technical and delivery contexts

  • Enterprise Agile, Scrum, SAFe and Kanban transformation
  • SAP S/4HANA transformation environments
  • AI/ML workflow integration and adoption
  • Cloud, DevOps, MLOps and CI/CD operating contexts
  • Executive coaching, change leadership and product ownership
  • Business continuity and transformation governance

Selected case studies

These anonymized case studies connect enterprise transformation experience with practical lessons for AI adoption, workflow design and operating-model change.

The case studies are deliberately anonymized. Their purpose is to show the operating patterns and methods behind the work without publishing client-identifying or unsupported evidence.

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