Enterprise technology stacks are increasingly defined by a persistent disconnect. Across organizations running SAP, digital transformation teams report a common pattern: employees are deeply invested in artificial intelligence tooling, leveraging assistants like Claude, Microsoft Copilot, and ChatGPT on a daily basis. These tools are delivering measurable productivity gains in content generation, reporting, and data analysis. However, when users inevitably ask the next logical question—whether their chosen AI assistant can execute an action directly within their SAP system—the answer remains a frustrating restriction, usually amounting to "not yet" or "not very well."
Compounding these architectural hurdles, SAP’s updated API policy requires enterprise customers to direct AI access to SAP-published APIs exclusively through endorsed pathways. Consequently, connecting a third-party AI assistant to an enterprise SAP ERP system has historically involved complex, custom integration work. Compounding matters further, this bespoke engineering often needs to be repeated from scratch every time an organization adopts a new AI platform. As the enterprise AI stack rapidly expands to include multiple specialized tools, this technical debt accumulates far faster than internal IT departments can remediate it.
To tackle this operational bottleneck head-on, Precisely has announced the launch of the new Precisely Automate MCP Server alongside native OData support in its flagship Precisely Automate platform. Together, these two capabilities provide any Model Context Protocol-compatible AI assistant with governed, standards-based access to SAP automation workflows. Crucially, this integration model eliminates the need to rebuild custom connections every time an enterprise’s underlying AI stack evolves or expands.
The Growing Challenges of Manual AI-to-SAP Connectivity
The friction involved in connecting modern artificial intelligence to enterprise resource planning infrastructure stems from the fragmented nature of both software ecosystems. When a finance lead wants an AI assistant to trigger a journal entry workflow, or a supply chain manager needs an automated update to a vendor record, an engineering bridge must be constructed between the AI interface and the SAP core. This traditionally demands custom API development, intricate authentication configurations, and ongoing maintenance. When the enterprise introduces a secondary or tertiary AI platform, the entire integration cycle starts over.
Most modern enterprises are not converging on a single, monolithic AI tool. Instead, they are running several solutions in parallel: Microsoft Copilot for general productivity, Claude for complex analysis, ChatGPT for specific workflow automation, and SAP’s native Joule assistant for targeted SAP tasks. Each of these applications represents a distinct integration project if it requires direct connectivity to core SAP systems. For IT teams already stretched to their limits by massive digital transformation projects, such as ongoing S/4HANA migrations, maintaining this integration backlog is entirely untenable.
At the same time, SAP’s evolving connectivity policies for third-party software and large language models have dramatically raised the stakes. Organizations relying on legacy scripting approaches—including BAPI, RFC, and traditional GUI automation—are finding that these methods face increasing restrictions within modern cloud environments, particularly in RISE with SAP and S/4HANA Cloud deployments. SAP’s strategic direction is unequivocal: enterprise integrations must run through sanctioned, API-based protocols. What was once considered a best practice is rapidly hardening into a strict compliance requirement.
Research conducted by Precisely in collaboration with the America’s SAP Users Group (ASUG) highlights the widespread nature of this organizational pressure, underscoring that enterprises adopting standards-based interfaces for AI-to-SAP connectivity will hold a decisive operational advantage over competitors forced to manage integrations on a case-by-case basis.
How the Precisely Automate MCP Server Functions
The Precisely Automate MCP Server is engineered around the Model Context Protocol, an open standard originally developed by Anthropic and now broadly adopted across the wider artificial intelligence ecosystem. By leveraging this framework, the server exposes existing Automate Studio scripts and Automate Evolve workflows as AI-callable tools. As a result, virtually any MCP-compatible AI client can seamlessly discover and invoke these pre-built automation processes through a single, unified configuration layer.
This entire interaction occurs in plain conversational language, bypassing the need to file internal IT support tickets or wait for dedicated developer resources. In the background, Automate Studio and Automate Evolve manage the complex SAP interactions while keeping established enterprise governance controls strictly intact throughout the process.
It is important to note that the underlying Studio scripts and Evolve workflows exposed by the MCP Server must still be built and configured initially. This release is not a zero-configuration shortcut that bypasses the foundational requirements of cloud SAP automation. Instead, it eliminates the recurring overhead of re-exposing those established workflows to every new AI platform that enters the enterprise ecosystem. Organizations can build their automation logic once and connect it securely to any MCP-compatible AI tool moving forward.
Leading AI platforms including Claude, ChatGPT, Microsoft Copilot, Gemini, and SAP Joule are already MCP-compatible. As more platforms adopt the standard over time, they will be able to connect to the existing Automate MCP Server without requiring additional integration engineering. This approach compounds the long-term value of every automation asset already built within Studio or Evolve, moving away from a model where each emerging AI tool triggers a brand-new integration project.
This strategic release forms part of a broader corporate initiative by Precisely, which is rolling out enterprise MCP Server support across multiple products in its portfolio. The overarching goal is to connect intelligent AI agents to data quality, location intelligence, master data management, and core automation capabilities through a unified, cohesive interface.
The Necessity of Native OData Support for Cloud SAP Automation
SAP’s connectivity policies have been moving in a definitive direction for years, and recent policy shifts have significantly accelerated that trajectory. Direct BAPI calls, remote function call scripting, and legacy GUI automation are facing strict limitations or outright lack of support for third-party software and LLMs operating within SAP cloud environments. Organizations whose cloud automation strategies rely on these legacy methodologies face substantial operational and compliance risks.
Open Data Protocol, commonly known as OData, serves as SAP’s preferred REST-based API standard for modern enterprise integrations. It is the mandatory approach for Clean Core environments, including RISE with SAP and S/4HANA Cloud, and represents the officially endorsed standard for all new third-party software connectivity. By building native OData support directly into Automate Studio, Precisely ensures that AI-driven SAP automation executed through the platform operates via SAP-sanctioned protocols right from inception.
The scope of functionality reachable through OData is vast. The SAP Business Accelerator Hub currently publishes more than 2,700 OData APIs spanning SAP’s extensive cloud application portfolio. This comprehensive coverage includes S/4HANA Finance, SAP SuccessFactors, SAP Ariba, SAP Concur, and SAP Customer Experience, among others. This breadth enables Automate-driven cloud automation to extend smoothly across the entire enterprise application landscape rather than remaining confined to the legacy on-premises processes where older scripting techniques were historically deployed.
For enterprise IT architects, native OData support bridges two requirements that previously felt mutually exclusive: achieving AI accessibility while maintaining strict compliance with Clean Core mandates.
Implications for SAP Teams Building Toward AI-Ready Data
For autonomous systems to deliver genuine business value within an enterprise SAP environment, they require reliable, strictly governed access to the authoritative data and processes held within SAP, including financial records, supply chain operations, human resources data, and procurement pipelines. Without that secure connectivity, artificial intelligence tools operate entirely outside the perimeter of the enterprise system of record rather than acting within it.
Modern AI systems must possess the capability to both read from and write back to authoritative databases. The Automate MCP Server extends this capability directly into SAP, allowing intelligent AI agents to invoke standardized SAP workflows through governed Automate processes while maintaining complete audit logs and traceability for every action performed.
For organizations already running Automate Studio or Evolve, this latest release effectively transforms their existing automation investments into AI-native assets. The established scripts, workflows, and governance frameworks already in place become immediately accessible to the everyday AI tools utilized by business teams, all without requiring expensive re-platforming initiatives.
Conversely, for enterprises approaching cloud SAP automation for the first time through an AI-first lens, the Automate MCP Server provides a viable starting point that avoids forcing the organization to commit prematurely to a single proprietary AI vendor.
Data from the Precisely and ASUG research partnership indicates that 75 percent of SAP-centric organizations rate low-code and no-code capabilities as highly important when selecting an enterprise automation platform. Controlling complex SAP processes through natural language interfaces represents the logical next step in that evolution, and the underlying connectivity infrastructure required to support it is now fully available to the market.
