Optimized AI Operating Models.

Processes: Optimization and standardization of value streams as a basis for AI deployment, with clearly defined end-to-end processes. Value stream analysis enables the identification of AI potential.

Technologies: Development of the necessary data infrastructure and selection and integration of AI systems into processes, including standards for development and operation.

Structure: Definition of departments and AI competence centers with clear responsibilities that promote collaboration.

Roles and responsibilities: Integration of AI roles into structures with a clear distribution of tasks between business and AI experts.

Cooperation: Effective collaboration between specialist departments, AI teams, and external partners to maximize customer benefit.

Leadership style: Focusing the leadership approach on data-driven decision-making and AI integration.

Culture: Promoting a culture based on innovation and systematic learning that supports the integration of AI into everyday activities.

Change management: Introducing systematic change and stakeholder management.

Monitoring and control: Rules and processes for managing AI systems with clear guidelines and metrics in line with corporate strategy.

Risk management: Systematic identification and assessment of AI-specific risks.

Compliance: Ensuring compliance with AI regulations, data protection, and ethical guidelines.