Enterprise AI Reference Framework

Target Architecture for Scalable Enterprise AI
Herausforderung

Scale, integrate, and securely operate AI systems without architectural disruptions or loss of control.

What is it fundamentally about?

The Enterprise AI Reference Framework describes the overarching vision for deploying AI within an enterprise. It defines how AI systems are integrated into existing IT landscapes in a stable, secure, and scalable manner – not as isolated applications, but as a sustainable enterprise capability.

The focus is on how data, models, agentic systems, platforms, and existing core systems consistently interact. The reference architecture provides guidance, reduces complexity, and forms the basis for controlled AI scaling in an enterprise context.

Relevanz

Warum das jetzt relevant ist

Typical Deployment Scenarios

When is this approach suitable? For which scenarios?

The Enterprise AI Reference Framework is particularly suitable for organizations that:

  • want to deploy AI enterprise-wide or across business units
  • need to consistently integrate multiple AI use cases
  • connect existing IT systems (ERP, CRM, line-of-business applications)
  • operate agentic or data-driven systems
  • want to architecturally secure scalability, security, and operations early on

It is suitable for complex enterprise environments with high demands on stability, security, and reusability.

Ansatz

System & Struktur des Ansatzes

System & Structure of the Approach

How is the solution logically structured? Which components are included?

The Enterprise AI Reference Framework defines central architectural principles and structural building blocks for Enterprise AI, including:

  • Vision & Architectural Principles
    Clear guardrails for the integration, scalability, and security of AI systems.
  • Platform and Infrastructure Layer
    Cloud, hybrid, and platform architectures as the foundation for AI workloads.
  • Data & AI Layer
    Models, data pipelines, agents, and lifecycle mechanisms.
  • Integration Layer
    Integration of existing enterprise systems and data sources.
  • Security & Identity by Design
    Identities, access controls, and protection mechanisms as an integral part of the architecture.

The framework serves as a guidance and decision-making framework, not as a rigid implementation pattern.

Outcome

Struktureller Mehrwert für Unternehmen

Outcome – Structural Benefits for Enterprises

The Enterprise AI Reference Framework enables enterprises to:

  • Consistent and scalable AI landscapes
  • Reduction of architecture and integration risks
  • Faster implementation of new AI use cases
  • Enhanced decision-making through clear target visions
  • Sustainable operability of AI systems

AI is therefore not introduced piecemeal, but strategically and architecturally anchored.

Die Umsetzung erfolgt durch spezialisierte Teams

Enterprise AI & Data Engineering

We orchestrate autonomous AI agents into controlled, scalable enterprise workflows.

Cloud Platform Engineering

The secure, scalable platform foundation for cloud and AI workloads.

Integration & Enterprise Connectivity

We connect AI directly with operational business processes – standardized, modular, and secure. This ensures use cases become productive instead of remaining isolated.

Enterprise Identity & Cyber Defense

The Enterprise Identity & Cyber Defense team creates the security and trust foundation that companies need to operate digital and AI-supported processes.