Governance Is No Longer Optional for AI-Driven SAP Landscapes
SAP data governance today refers to the automated, policy-driven management of data access, quality, and lineage across SAP and non-SAP systems so that AI agents, analytics, and operational workloads can rely on consistent, compliant, and explainable information rather than ad-hoc integrations and manual oversight alone. That shift is not theoretical; it is reshaping the SAP ecosystem as AI moves from pilots to production. The harsh reality is that most enterprises are under-governed. Only 3% of organizations report a unified, governed data layer, while 38% still run in siloed or ad-hoc integration states. A third have no formal governance or only basic standards, and just 12% have reached automated governance at the level AI workloads expect. Against that backdrop, vendors are racing to turn governance from a side concern into essential infrastructure for AI-ready data platforms.
Microsoft Turns SAP Connector Policies into AI Compliance Controls
Microsoft’s latest Power Platform changes make SAP connector policies a front-line compliance tool instead of a back-office guardrail. On June 4, Microsoft released Advanced Connector Policies for Power Platform, then followed with updated SAP guidance on June 11 that refreshed at least 27 administration pages. These policies replace the older data loss prevention model with allowlist-based governance at the connector, action, and MCP server level. Administrators can now decide not only which SAP connectors are allowed but exactly which actions and MCP servers AI tools may use, with a single policy applied per environment or inherited from an environment group. Microsoft explicitly frames this as a response to a new compliance surface: AI agents reaching directly into SAP ERP and SAP OData endpoints. In opinion, this is the right direction—governing at the action level turns Power Platform into a governed integration layer instead of a risk amplifier for SAP connector policies and enterprise data integration.
Informatica Bets on Agentic MDM as the AI-Ready Data Backbone
Where Microsoft tightens access, Informatica attacks the quality problem with master data management automation. At Informatica World, the company unveiled Agentic Multidomain MDM, presented as the data-readiness foundation for enterprise AI agents across SAP and non-SAP estates. This system uses autonomous AI agents to cleanse, steward, and enrich master data in real time, governing customer, supplier, product, and financial domains across hybrid and multi-cloud environments. A Data Steward Agent continuously resolves quality issues, matches records, and enriches domain data without manual intervention from data teams. In large SAP deployments that split master data across SAP S/4HANA, SAP ECC, and external CRM platforms, this kind of continuously running MDM layer is not a luxury; it is a prerequisite for AI-ready data platforms and Joule activation. The launch lines up with a clear mandate: enterprises need trusted, lineage-rich records before they dare let Joule agents act on them.
CData and Collibra Push Governance into the AI Data Fabric
Connectivity and cataloging are being rebuilt for AI, not just analytics. CData, a long-standing SAP Business Data Cloud connector partner, has started treating AI access as a first-class design goal. On June 23, it shipped new AI developer tools built around the Model Context Protocol, an emerging standard for giving AI models real-time enterprise data. The free Connect AI Developer Edition, open-source Python SDK, and CLI aim to replace brittle, ungoverned pipelines with governed access that still moves at developer speed. At the same time, Collibra is strengthening its role as the governance fabric inside SAP Business Data Cloud. The company expanded its partnership with Snowflake on June 2 to synchronize governed business context and semantics, then on June 16 Databricks named it Governance Partner of the Year as bidirectional integrations with Unity Catalog, AI Command Center, and a new MCP Server went live. Collibra is already SAP’s governance partner of choice for BDC, and broader Snowflake integration availability is slated for Q3.
From Manual Oversight to Policy-Driven, Agentic Governance
Taken together, these moves signal a clear direction: SAP data governance is becoming automated, agentic, and policy-driven, or it will fail to keep up with AI. Advanced Connector Policies turn Microsoft Power Platform into an enforcement surface at the action and MCP server level. Agentic Multidomain MDM shifts master data governance from ticket queues to AI agents running continuously. CData’s MCP-based tools recognize that AI workloads will cross dozens of non-SAP sources and need governed connectivity at scale, not another fragile integration project. Collibra’s deeper ties with Databricks and Snowflake show that AI metadata, lineage, and trust scores must live where data and models run, not in isolated catalogs. The opinionated takeaway is blunt: treat governance maturity as a prerequisite for SAP Business Data Cloud and AI, not an afterthought. Enterprises that keep relying on manual oversight will stay stuck in siloed integration while the rest of the ecosystem standardizes on AI-ready data platforms backed by automated governance.
