By Christoph Moll, CEO and Chief Solution Architect, BeNeering
For the past two years, the enterprise AI conversation has been dominated by models: which one is most capable, which one is cheapest, which one to standardize on. In 2027, that conversation moves closer to where business actually happens. AI is leaving the chat window and entering the transactional core of the enterprise, where purchase orders are created, budgets are committed and every document must stand up to an audit.
This is where the hard questions begin. How does AI reach ERP data without creating new risks? How much should AI be allowed to decide on its own? And what happens to the procurement systems many companies still run on platforms that are nearing the end of mainstream maintenance? Here are three predictions for the year ahead.
1. In 2027, enterprises will start treating data replication for AI as a liability, not an asset
Enterprises are connecting AI assistants to their business processes, and the question for IT is shifting from “which AI model” to “how does AI reach ERP data safely.” The default answer so far has been to copy data into a separate platform where AI can work with it. That approach is starting to show its costs.
Every copy creates a second version of the truth that is already out of date by the time an assistant uses it. Every copy needs its own security model, because the authorization concept of the ERP system does not travel with the data. And every copy widens the compliance perimeter: more places where sensitive supplier, pricing and employee data live, more pipelines to monitor and more questions from auditors. An AI assistant that answers from yesterday’s replica of the purchasing data is not only less useful, it is harder to govern.
In 2027, standard interfaces such as the Model Context Protocol (MCP) will become the expected way for AI agents to work with systems of record. Instead of moving data to the AI, the AI calls governed services that read and act on live data, within the permissions of the user it works for. CIOs will increasingly ask vendors a simple question: does your agent work on live data, or on a copy?
2. In 2027, the AI that moves from pilot to production will be the AI that suggests, not decides
Most enterprises have now run AI pilots, and many have learned the same lesson. AI is remarkably good at understanding what a person wants. It is far less reliable when it has to commit the company to something. A fluent answer that is right ninety-five percent of the time is impressive in a demo, and unacceptable for a purchase order, a contract call-off or a posting in the general ledger.
After the hype, 2027 will reward AI designs that keep execution deterministic. AI interprets the request: it turns a free-text need into the right catalog item, supplier or framework agreement, and prepares the document. Business rules then validate it, approvals follow the established workflow, and, most importantly, people decide. Every step remains traceable, which is what auditors, works councils and regulators expect.
This changes how success is measured. The question will no longer be how much the AI can do on its own, but how much of the process can be automated safely. Metrics such as no-touch rates, compliance with negotiated contracts and process cycle times will matter more than the sophistication of the model behind them.
3. The end of SAP SRM maintenance will force a large number of SAP customers to rethink procurement execution
SAP’s mainstream maintenance for the Business Suite, which includes SAP Supplier Relationship Management (SRM), ends at the end of 2027; extended maintenance to 2030 comes at a premium. For many organizations, on-premise run SRM has been the backbone of operational procurement for well over a decade, with years of customer-specific development built on top of it. Simply carrying it forward is not an option, and recreating it inside S/4HANA runs against the direction SAP itself is setting.
At the same time, the clean-core principle pushes extensions out of the ERP core. As a result, procurement execution will move to dedicated layers that connect to S/4HANA in real time while keeping the core clean. These layers handle the daily work of buying, from catalogs and requests to approvals and orders, and hand clean, compliant documents to the ERP system.
This is not a theoretical shift. Several of BeNeering’s largest customers have already replaced SAP SRM with our solution, and others are in the middle of doing so. In 2027, many more SAP customers will face the same decision, and those who start early will have the most room to redesign their processes rather than simply migrate them.
The common thread
All three predictions point in the same direction. In 2027, the value of enterprise AI will depend less on the model and more on the architecture around it: live access to the system of record, clear rules about who decides, and an execution layer that keeps the ERP core clean. The organizations that get this foundation right will be the ones that turn AI pilots into measurable results.
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ABOUT THE AUTHOR
Christoph Moll is CEO and Chief Solution Architect of BeNeering, a German software company that provides an SAP-native procurement execution layer for large enterprises. Founded in 2007, BeNeering serves more than 400,000 users in 86 countries across 12 industries.
