Presented by SAP<\/i><\/p>\n
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When SAP ran a quiet internal experiment to gauge consultant attitudes toward AI, the results were striking. Five teams were asked to validate answers to more than 1,000 business requirements completed by SAP\u2019s AI co-pilot, Joule for Consultants \u2014 a workload that would normally take several weeks.<\/p>\n
Four teams were told the analysis had been completed by junior interns fresh out of school. They reviewed the material, found it impressive, and rated the work about 95% accurate.<\/p>\n
The fifth team was told the very same answers had come from AI.<\/p>\n
They rejected almost everything.<\/p>\n
Only when asked to validate each answer one by one did they discover that the AI was, in fact, highly accurate \u2014 surfacing detailed insights the consultants had initially dismissed. The overall accuracy? Again, about 95%.<\/p>\n
\u201cThe lesson learned here is that we need to be very cautious as we introduce AI \u2014 especially in how we communicate with senior consultants about its possibilities and how to integrate it into their workflows,\u201d says Guillermo B. Vazquez Mendez, chief architect, RI business transformation and architecture, SAP America Inc.<\/p>\n
The experiment has since become a revealing starting point for SAP\u2019s push toward the consultant of 2030: a practitioner who is deeply human, enabled by AI, and no longer weighed down by the technical grunt work of the past.<\/p>\n
Resistance isn\u2019t surprising, Vazquez notes. Consultants with two or three decades of experience carry enormous institutional knowledge \u2014 and an understandable degree of caution.<\/p>\n
But AI copilots like Joule for Consultants are not replacing expertise. They\u2019re amplifying it.<\/p>\n
\u201cWhat Joule really does is make their very expensive time far more effective,\u201d Vazquez says. \u201cIt removes the clerical work, so they can focus on turning out high-quality answers in a fraction of the time.\u201d<\/p>\n
He emphasizes this message constantly: \u201cAI is not replacing you. It\u2019s a tool for you. Human oversight is always required. But now, instead of spending your time looking for documentation, you\u2019re gaining significant time and boosting the effectiveness and detail of your answers.\u201d<\/p>\n
Historically, consultants spent about 80% of their time understanding technical systems \u2014 how processes run, how data flows, how functions execute. Customers, by contrast, spend 80% of their time focused on their business.<\/p>\n
That mismatch is exactly where Joule steps in.<\/p>\n
\u201cThere\u2019s a gap there \u2014 and the bridge is AI,\u201d Vazquez says. \u201cIt flips the time equation, enabling consultants to invest more of their energy in understanding the customer\u2019s industry and business goals. AI takes on the heavy technical lift, so consultants can focus on driving the right business outcomes.\u201d<\/p>\n
AI is also transforming how new hires learn.<\/p>\n
\u201cWe\u2019re excited to see Joule acting as a bridge between senior consultants, who are adapting more slowly, and interns and new consultants who are already technically savvy,\u201d Vazquez says.<\/p>\n
Junior consultants ramp up faster because Joule helps them operate independently. Seniors, meanwhile, engage where their insight matters most.<\/p>\n
This is also where many consultants learn the fundamentals of today\u2019s AI copilots. Much of the work depends on prompt engineering \u2014 for instance, instructing Joule to act as a senior chief technology architect specializing in finance and SAP S\/4HANA 2023, then asking it to analyze business requirements and deliver the output as tables or PowerPoint slides.<\/p>\n
Once they grasp how to frame prompts, consultants consistently get higher-quality, more structured answers.<\/p>\n
New architects are also able to communicate more clearly with their more experienced counterparts. They know what they don\u2019t know and can ask targeted questions, which makes mentorship far smoother. It\u2019s created a real synergy, Vazquez adds \u2014 senior consultants see how quickly new hires are adapting and learning with AI, and that momentum encourages them to keep pace and adopt the technology themselves.<\/p>\n
\u201cWe\u2019re still in the baby steps of AI \u2014 we\u2019re toddlers,\u201d Vazquez says. \u201cRight now, copilots depend on prompt engineering to get good answers. The better you prompt, the better the answer you get.\u201d<\/p>\n
But that represents only the earliest phase of what these systems will eventually do. As copilots mature, they\u2019ll move beyond responding to prompts and start interpreting entire business processes \u2014 understanding the sequence of steps, identifying where human intervention is needed, and spotting where an AI agent could take over. That shift is what leads directly into agentic AI.<\/p>\n
SAP\u2019s depth of process knowledge is what makes that evolution possible. The company has mapped more than 3,500 business processes across industries \u2014 a repository Vazquez calls \u201csome of the most valuable, rigorously tested processes developed in the last 50 years.\u201d Every day, SAP systems support roughly $7.3 trillion in global commerce, giving these emerging AI agents a rich foundation to navigate and reason over.<\/p>\n
\u201cWith that level of process insight and data, we can take a real leap forward,\u201d he says, \u201cequipping our consultants with agentic AI that can solve complex challenges and push us toward increasingly autonomous systems.\u201d<\/p>\n
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