{"id":249050,"date":"2026-10-05T15:09:18","date_gmt":"2026-10-05T13:09:18","guid":{"rendered":"https:\/\/blog.adesso-bc.com\/?p=249050"},"modified":"2026-10-05T15:09:18","modified_gmt":"2026-10-05T13:09:18","slug":"ai-in-sap-consulting-are-sap-consultants-now-obsolete","status":"publish","type":"post","link":"https:\/\/blog.adesso-bc.com\/en\/ai-in-sap-consulting-are-sap-consultants-now-obsolete\/","title":{"rendered":"AI in SAP Consulting: Are SAP Consultants Now Obsolete?"},"content":{"rendered":"\n

In February 2023, we completed an internal analysis to explore what AI could do in SAP consulting, using ChatGPT as an example. We later published some of our findings in the blog post \u201cChatGPT vs. SAP Consultant: Will artificial intelligence make SAP consultancies obsolete?<\/a>\u201d<\/p>\n\n\n\n

Admittedly, the article now feels almost completely outdated given the speed of development in generative AI.<\/p>\n\n\n\n

Our conclusion at the time was that AI can indeed be helpful for getting up to speed on new subject areas but still showed clear shortcomings when it came to specific SAP knowledge. One finding, however, still holds true today: AI-generated results must always be critically reviewed.<\/p>\n\n\n\n

Why AI Results Still Need Critical Review<\/h2>\n\n\n\n

It isn’t just the capability of the AI models themselves that has increased; the tooling surrounding these models has also advanced considerably. AI systems are now increasingly agentic. Developments such as Retrieval-Augmented Generation (RAG) combined with intelligent web search, along with new standards like the Model Context Protocol (MCP), Agent-to-Agent (A2A), and specialized skills, are continuously reducing incorrect answers (hallucinations).<\/p>\n\n\n\n

To properly assess AI-generated results, humans now need considerably deeper subject-matter expertise. When hallucinations do occur, they are often phrased so convincingly and even appear logically coherent within the given assumptions that AI-generated errors are recognized much later. This creates the risk that assumptions based on such errors, for example when planning projects, initially appear plausible but later turn out to be false and unrealistic.<\/p>\n\n\n\n

An example from a tender<\/strong><\/h3>\n\n\n\n

In practice, we have already reviewed tenders that showed clear signs of generative AI having been used. In one case, the planning was based on the assumption that certain customizing settings in an SAP module were not relevant. Accordingly, no effort was budgeted for them. Our experts had to correct this assumption, which also changed the assumed project scope.<\/p>\n\n\n\n

How AI Is Changing SAP Consulting Today<\/h2>\n\n\n\n

Roles involving repetitive work and little deep expertise are at risk, even in SAP consulting. What matters is achieving higher productivity through the correct use of AI. What is not enough: simply copy-pasting tasks through AI.<\/p>\n\n\n\n

Example: The modern Project Management Office (PMO)<\/strong><\/h3>\n\n\n\n

Modern PMOs no longer simply take notes; they have meetings transcribed by AI. They set up meetings so that the relevant AI functions run from the very start, for example with the correct language configured. The resulting minutes are then filed in a structured way via a workflow and subsequently reviewed critically. During the meeting itself, the PMO increasingly takes on the role of a moderator. Finding suitable dates and available time slots can likewise be supported by AI. Onboarding is also no longer handled manually: welcome emails, permissions, appointment forwarding, and other onboarding tasks are implemented through automated workflows.<\/p>\n\n\n\n

Undoubtedly, correctly applied AI reduces the personnel effort required for certain tasks. However, the PMOs that remain needed can, with AI support, handle a larger volume of work and correspondingly take on more responsibility. The complexity of a modern PMO should not be underestimated: familiarity with various AI and automation tools makes the work technically more demanding as well. If, for example, a workflow fails, a PMO must be able to fix the error itself.<\/p>\n\n\n\n

Customers are becoming more capable too<\/strong><\/h3>\n\n\n\n

Another factor must not be overlooked: customers are using AI and automation themselves. Customers that use AI effectively can perform many typical tasks of senior SAP consultants largely on their own and may only need targeted support. When they do, however, they expect absolute expert-level capability.<\/p>\n\n\n\n

SAP consultancies that lack a broad base of experts and do not pursue continuous AI enablement for their staff will increasingly fall behind in the market. What we already do at adesso today, and what we also see in the market, is that efficiency gains from AI are made transparent to customers and shared with them.<\/p>\n\n\n\n

New Practical Test: 17 SAP Expert Questions, Four AI Systems<\/h2>\n\n\n\n

For our new test, we used four different AI system configurations:<\/p>\n\n\n\n