From Metadata to Enhanced Enterprise Transformation Management: An Integrated AI-Supported Architecture for Validated, Multi-Target Governance with Moregraph

Source abstract

Enterprises expose thousands of data entities as machine-readable metadata through APIs such as SAP Graph and Microsoft Graph, while adopting AI agents that act on the same data. Yet architecture repositories, process-governance workflows, and agent platforms each build their own view of the enterprise, and none is anchored in a formally validated specification. This paper asks how formally validated metadata can be turned into governed transformation capabilities that support autonomous enterprise operation. Following Design Science Research, we contribute (i) a repositioning of the Moregraph platform as a semantic integration layer; (ii) a validation gate that restates published Conceptual Graph and Formal Concept Analysis (CGFCA) results as re-checkable invariants; (iii) a target-parametric Metadata-to-Governance Transformation (MGT) with explicit commit conditions; and (iv) an integrated architecture connecting one validated source to architecture (SAP LeanIX), process (SAP Signavio), and agent (SAP AI Core) governance, mapped onto the BTM Tripod’s People, Process, and Application pillars of Business Transformation Management. We separate what is formally validated, what is demonstrated in a working prototype (LeanIX), and what is proposed (Signavio, AI Core), and set out an evaluation strategy. The central claim is bounded: explicit semantic and policy constraints derived from validated metadata can limit or prevent human- or agent-initiated changes from producing unauthorised or inconsistent enterprise outcomes.