As artificial intelligence adoption accelerates across global enterprises, a persistent architectural barrier has emerged for organizations running SAP software. Employees across departments are routinely utilizing advanced large language models and assistant tools—ranging from Anthropic’s Claude and OpenAI’s ChatGPT to Microsoft Copilot and SAP’s own Joule—to drive daily productivity gains in content generation, reporting, and complex data analysis. However, when these productivity gains prompt the natural follow-up question of whether an organization’s chosen AI assistant can execute tasks directly within SAP, IT teams are almost universally forced to answer that it cannot yet be done, or at least not without significant friction.

This disconnect has created an acute integration challenge. Compounding the difficulty, SAP’s updated API policies now require corporate customers to direct AI access to SAP-published APIs exclusively through endorsed pathways. Consequently, connecting a third-party AI assistant to a core SAP Enterprise Resource Planning (ERP) system has become a complex undertaking. It typically requires custom integration work that must be built entirely from scratch for every new AI platform an organization introduces to its enterprise stack. As businesses adopt an increasingly diverse array of AI tools, this architectural debt accumulates at a rate that stretches IT departments thin, particularly as many are already managing demanding S/4HANA migration schedules.

To address this challenge head-on, data integrity and automation provider Precisely has announced the launch of the new Precisely Automate MCP Server alongside native OData support in Precisely Automate. Together, these two powerful capabilities are designed to provide any Model Context Protocol-compatible AI assistant with governed, standards-based access to SAP automation workflows, eliminating the need to rebuild custom integrations every time an enterprise’s underlying AI stack evolves.

Navigating the Challenges of Manual AI-to-SAP Connectivity

The operational hurdles of manual AI-to-SAP connectivity are well-known to enterprise technology leaders. When a finance lead wants an AI assistant to initiate 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 external AI tool and the internal SAP system. This process traditionally demands custom API development, intricate authentication configurations, and ongoing maintenance. When the enterprise subsequently adopts an additional AI platform to serve different business units, the entire integration process must be repeated.

Modern enterprises rarely converge on a single AI tool. Instead, they increasingly operate several systems in parallel, utilizing Copilot for general office productivity, Claude for deep data analysis, ChatGPT for specific operational workflows, and Joule for native SAP interactions. If each of these tools requires a bespoke connection to the enterprise SAP landscape, the resulting backlog becomes untenable for IT teams already grappling with complex cloud migrations.

The stakes have grown even higher due to SAP’s evolving connectivity policies regarding third-party software and large language models. Organizations that rely on legacy scripting approaches, such as BapI calls, RFC-based scripting, and GUI automation, are discovering that these methods face mounting restrictions within cloud environments, most notably in S/4HANA Cloud and RISE with SAP deployments. The strategic direction established by SAP is clear: enterprise integrations must run through sanctioned, API-based protocols. What was once considered an industry best practice is rapidly hardening into a strict compliance requirement.

Research conducted jointly by Precisely and the America’s SAP Users Group underscores the widespread industry pressure surrounding these modernization efforts. According to the findings, the vast majority of SAP-using organizations place a high premium on low-code and no-code capabilities when evaluating automation platforms. Organizations that successfully establish a standards-based interface to connect AI assistants directly to their SAP systems stand to secure a distinct operational advantage over competitors forced to manage integrations on a case-by-case basis.

The Mechanics of the Precisely Automate MCP Server

The Precisely Automate MCP Server is constructed upon the Model Context Protocol, an open standard originally developed by Anthropic and rapidly embraced across the broader artificial intelligence ecosystem. By leveraging this framework, the server exposes Automate Studio scripts and Automate Evolve workflows as AI-callable tools, allowing virtually any MCP-compatible AI client to discover and invoke them through a unified configuration.

This integration allows business users to interact with enterprise systems using plain language, bypassing the need to file internal IT support tickets or wait for dedicated developer resources. In the background, Automate Studio and Evolve manage the underlying SAP interactions, ensuring that established corporate governance controls and security protocols remain fully intact throughout the transaction.

While the Automate Studio scripts and Evolve workflows exposed by the MCP Server must still be built and configured initially, the solution eliminates the recurring overhead of re-exposing those same workflows to every newly adopted AI platform. Organizations can build their automation assets once and connect them to any MCP-compatible AI tool introduced in the future. Prominent platforms including Claude, ChatGPT, Microsoft Copilot, Joule, and Gemini already feature native support for the Model Context Protocol. As additional AI solutions adopt the standard, they can connect directly to the existing Automate MCP Server without requiring auxiliary integration projects, thereby multiplying the long-term value of an enterprise’s existing automation investments.

This product release forms a central component of Precisely’s broader strategic initiative to roll out enterprise Model Context Protocol server support across its entire software portfolio. By doing so, the company aims to connect AI agents to core capabilities spanning data quality, location intelligence, master data management, and process automation through a single, cohesive interface.

The Role of Native OData Support in Cloud SAP Environments

The push toward native OData support is deeply intertwined with SAP’s broader architectural evolution. For years, SAP has guided developers away from direct BAPI calls, Remote Function Call scripts, and user interface automation, restricting these legacy methods within modern cloud application suites. Organizations attempting to execute cloud SAP automation via these older paradigms face significant operational risks as cloud policies tighten.

Open Data Protocol, commonly known as OData, serves as SAP’s preferred REST-based API standard for modern enterprise integrations. It represents the required architectural approach for Clean Core environments, including RISE with SAP and S/4HANA Cloud, and stands as the formally endorsed protocol for third-party connectivity. By building native OData support directly into Automate Studio, Precisely ensures that AI-driven SAP automations operate via SAP-sanctioned protocols from the outset.

The operational scope accessible through OData is extensive. The SAP Business Accelerator Hub currently publishes more than 2,700 OData APIs spanning the breadth of SAP’s cloud application portfolio, encompassing S/4HANA Finance, SAP SuccessFactors, SAP Ariba, SAP Concur, and SAP Customer Experience. This expansive coverage enables cloud automation strategies to extend seamlessly across the entire enterprise software landscape, moving far beyond the boundaries of traditional on-premises processes where legacy scripting methods were historically deployed.

Practically speaking, native OData support bridges requirements that once appeared mutually exclusive: maintaining Clean Core compliance while simultaneously enabling flexible, AI-driven accessibility.

Implications for SAP Teams Preparing for AI-Ready Data

For autonomous enterprise systems to deliver genuine value within an SAP environment, they require reliable, governed access to critical institutional data, including financial records, supply chain operations, human resources files, and procurement logs. Without this direct access, AI tools are relegated to operating around the periphery of core systems rather than actively participating within them.

Enterprise AI systems must possess the capability to read from and write back to authoritative systems of record. The Automate MCP Server extends this functional reach directly into SAP, allowing AI agents to invoke authorized workflows through governed processes where every action is logged, monitored, and traceable.

For organizations already utilizing Automate Studio or Evolve, this release transforms pre-existing automation assets into native AI components. Existing scripts, workflows, and governance configurations become accessible to the everyday productivity tools utilized by employees, sparing companies from disruptive re-platforming initiatives. Conversely, organizations approaching cloud SAP automation for the first time through an AI-first perspective gain a robust starting point that avoids vendor lock-in to a single AI provider.

Controlling core SAP processes through natural language commands represents a natural evolution in enterprise software usage, and the foundational connectivity layer required to support this shift is now fully available to the market.