Enterprise AI adoption is becoming increasingly fragmented as employees use multiple assistants for research, coding, productivity and automation. Rencore, a Germany-based provider of Microsoft 365 and AI governance software, is responding with a multi-AI governance capability that brings Microsoft 365, Microsoft Copilot, Copilot Studio, AI agents and Claude Enterprise into a single management layer. The company says ChatGPT Enterprise governance will enter preview later in October 2026.
Microsoft Copilot may be part of an enterprise’s AI strategy, but it is increasingly unlikely to be the only AI assistant employees use.
That creates a governance problem. Employees can access Microsoft Copilot for everyday productivity, Claude for research or coding, and ChatGPT or other AI systems for specialized tasks. Each platform typically has its own administrative console, identity records, audit data and policies.
Rencore wants to address that fragmentation with a new multi-AI governance capability in its AI & Agents module.
The Germany-based company says the platform can govern Microsoft 365, Microsoft Copilot, Copilot Studio, AI agents and Claude Enterprise from one interface, with Microsoft Entra ID serving as the identity layer. Claude Enterprise governance is currently available in preview, while ChatGPT Enterprise governance is scheduled to enter preview later in October 2026.
The preview is opt-in, with Rencore offering organizations access to help validate use cases with its product team.
The multi-AI governance problem
The shift toward multiple enterprise AI assistants is not simply a matter of employee preference. It creates a new layer of operational complexity for IT and security teams.
Rencore cites Gartner research indicating that two-thirds of organizations use at least two enterprise generative AI assistants in addition to Microsoft 365 Copilot. The research also advises organizations to evaluate alternatives rather than automatically standardizing on a single vendor.
That means an employee’s AI footprint can extend across several platforms even when most corporate data remains inside Microsoft 365.
The issue becomes more complicated as external AI providers add connectors to Microsoft 365 services such as SharePoint, OneDrive and Outlook. AI assistants can potentially access the same corporate information that employees already have permission to reach, making existing identity and oversharing problems relevant across a larger AI estate.
Rencore’s proposition is to treat each AI service as another component of the enterprise technology inventory rather than as an isolated application.
Entra ID becomes the common identity layer
The platform connects to AI services through their respective APIs and uses Microsoft Entra ID to associate accounts with individual users.
That approach is intended to give administrators a person-centric view rather than requiring them to reconcile separate identities across multiple AI consoles.
For Claude Enterprise, Rencore says its inventory can cover more than 400 event types, including users, groups, roles, projects, collaborators, chats, Claude Code and Cowork sessions, artifacts, skills, connectors and plugins. It also tracks 46 organization-level settings.
The planned ChatGPT Enterprise support is designed to cover workspaces, custom GPTs, agents, service accounts, canvases, library files and project-level connectors.
This inventory approach could become increasingly important as enterprises move from individual AI assistants toward agentic systems that can create projects, connect tools and execute actions.
AI governance is also a cost problem
Security and compliance are only part of the challenge.
Enterprise AI increasingly uses consumption-based pricing, making it harder for organizations to forecast costs based solely on seat counts. Rencore says its platform can track usage, token consumption and costs by user, group, department or cost center.
That can help identify unused licenses and potentially reassign them.
The company also points to audit retention as another concern. Rencore says some provider audit histories can be retained for as little as 30 days. Its platform continuously pulls activity data to create a longer-running operational record.
The distinction matters for organizations investigating incidents after the fact. A short provider retention window can make it difficult to reconstruct what happened unless an organization has its own monitoring process.
From inventory to policy enforcement
Rencore is also positioning the platform as an action layer.
Its AI & Agents module includes policies intended to identify issues such as publicly shared projects or artifacts, external users with AI seats and accounts that remain active after a user’s Microsoft Entra identity has been deactivated.
The company says administrators can trigger automations from findings, including actions such as deleting projects or unpublishing agents, with approval controls available.
For ChatGPT Enterprise, Rencore says it provides 35 out-of-the-box policies.
The ability to manage agents is particularly relevant as enterprise AI shifts from conversational assistants to systems capable of performing tasks. An organization may need to know not only which employees have AI access, but which agents exist, who owns them, what tools they connect to and whether they remain appropriate as employees change roles.
Operational governance, not model guardrails
Rencore draws a boundary around its approach: the company describes the platform as operational governance rather than runtime AI guardrails.
It says the system reads metadata and does not read, store or display message bodies, session transcripts or file contents.
That positions the platform alongside, rather than as a replacement for, tools such as Microsoft Purview. Rencore says its role is to provide current inventories, ownership information and lifecycle data that can support governance and regulatory processes involving frameworks including the EU AI Act, GDPR, NIS2 and DORA.
This distinction is important because enterprise AI governance is increasingly becoming a layered discipline. Runtime safety, data-loss prevention, identity management, model risk, application governance and lifecycle management may all sit in different systems.
The emerging AI control plane
Rencore’s strategy reflects a broader change in enterprise AI infrastructure.
The first wave of enterprise AI governance largely focused on individual assistants. The next challenge is governing an ecosystem in which employees can use multiple models, business units can deploy their own tools and AI agents can operate across corporate systems.
A centralized inventory does not solve every AI risk, but it can establish visibility into who owns what, which services are being used and where policies need to be applied.
For IT teams, that could become the foundation for a broader AI control plane—one that connects identity, lifecycle management, usage, cost and policy across an increasingly diverse collection of AI services.
Rencore’s expansion beyond Microsoft Copilot therefore reflects a larger enterprise AI trend: organizations are moving from asking which AI assistant should we deploy? to asking how do we govern all of the AI our employees and systems are already using?
Market Landscape
Enterprise AI governance is shifting from single-platform administration toward multi-model and multi-agent management. As organizations adopt assistants from Microsoft, Anthropic, OpenAI, Google and other providers, IT teams face fragmented identities, separate audit systems, inconsistent policies and increasingly complex AI spending.
Rencore is positioning its AI & Agents module at this control-plane layer, with Microsoft Entra ID acting as the common identity anchor. Its approach complements rather than replaces runtime security and data-governance products.
The competitive opportunity extends across AI governance, enterprise AI applications, AI agents, identity management and AI observability. As agentic AI adoption grows, inventories will likely need to evolve from tracking users and licenses toward tracking agent ownership, permissions, connectors and lifecycle status.
Top Insights
- Multi-AI is becoming the enterprise reality, with employees increasingly using several AI assistants instead of relying exclusively on Microsoft Copilot.
- Identity is central to AI governance, and Rencore uses Microsoft Entra ID to associate accounts across AI services with individual employees.
- AI governance increasingly includes cost management, as token consumption and usage-based pricing make traditional seat-based budgeting less predictable.
- Agent inventories will become more important, as organizations need visibility into who owns AI agents, what tools they access and whether those agents remain authorized.
- Operational governance complements runtime controls, providing inventory, lifecycle and ownership data alongside security and data-governance platforms.
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