Do I need to rebuild my IT landscape for AI?

No. An enterprise AI infrastructure is integrated as an additional layer into the existing architecture. SAP remains ERP, Workday remains the HR platform. The AI layer reads, writes and orchestrates via APIs and connectors.

How do AI agents communicate with SAP?

Via SAP standard APIs (RFC, OData, BAPIs) and middleware. The agent reads data, processes it and writes results back. The SAP instance is not modified – the agent operates as an external integration layer.

What happens to my existing security policies?

They remain fully valid. AI agents are subject to the same network, access and compliance rules as any other system. They are integrated into existing architecture boards and security processes.

Integrating AI Infrastructure into Your Existing IT Landscape

The Integration Problem

Most enterprises do not have an empty IT landscape. They have SAP, Workday, SuccessFactors, DATEV, SharePoint, industry-specific systems, established middleware and proven security architectures. This is not an obstacle to AI – it is the reality into which AI must fit.

The most common cause of failed AI projects in enterprises is not technology. It is that AI is introduced as an isolated system – alongside existing IT, not within it. This creates shadow IT, data silos and governance gaps.

The correct approach: AI infrastructure as an integration layer that connects existing systems rather than replacing them.

Architecture Principle: Integration Layer, Not Platform Migration

An enterprise AI infrastructure consists of four layers that fit into any existing IT landscape.

The lowest layer is system connectivity. Connectors to SAP (via RFC, OData, BAPIs), to Workday (via REST APIs), to DATEV, SharePoint, email systems and industry-specific applications. These connectors read and write data – source systems remain unchanged.

Above it sits the orchestration layer. This is where AI agents run: Document Agents that read and classify incoming documents. Workflow Agents that manage processes across systems. Knowledge Agents that answer questions based on enterprise knowledge.

The third layer is the Decision Layer. It separates AI analysis from business decisions. The model recommends, the human decides. Every decision is documented, versioned and auditable.

The top layer is the interface: a unified chat interface for employees or direct system-to-system integration without human interaction.

In Practice: How an AI Agent Integrates into an SAP Landscape

A real-world example: sick leave processing.

An employee submits a sick note via email or a portal. A Document Agent identifies the document type, extracts relevant fields (name, period, diagnosis group) and validates the data against the collective agreement. Via the SAP connector, it checks personnel master data, calculates continued pay and prepares the booking.

At this point, the Decision Layer intervenes: if the case falls within automatable rules (standard case, no anomalies), the booking is presented to the responsible clerk for approval. If an anomaly is detected (frequency, deadline breach, missing data), the case is escalated.

The SAP instance was not modified at any point. The agent operates as an external integration layer communicating via standard APIs. Existing authorisation concepts, network zones and audit processes remain unchanged.

What the IT Architecture Must Deliver

For clean integration, AI infrastructure requires four properties.

First: API-first. All communication between agent and source system runs via documented APIs. No direct database access, no proprietary interfaces.

Second: multi-tenancy. In group structures, agents must be configurable per entity – different rules, different systems, different compliance requirements per subsidiary.

Third: logging and audit. Every interaction between agent and source system is logged – who read, wrote or decided what, and when. This is not optional; it is the foundation of Governance by Design.

Fourth: rollback capability. If an agent makes an error, every action must be reversible. This requires transaction-oriented communication with source systems.

No Greenfield, No Platform Migration

The most common objection from CIOs: “We cannot introduce another system.” And this objection is valid.

This is why AI infrastructure is not a new system in the traditional sense. It is a layer that fits into the existing architecture. SAP remains SAP. Workday remains Workday. The network architecture remains in place. Security policies remain valid. The agent is an additional participant in the existing ecosystem – subject to the same rules, the same controls, the same audit requirements.

At Gosign, we build AI infrastructure as an integration layer: on Azure, GCP or self-hosted, connected to the systems already in place. No shadow IT. Agents become part of the existing IT governance – not a new parallel world.