Generative AI is having its moment.
The tech world is buzzing. LinkedIn is flooded. Demos are dazzling.
But behind the scenes, SAP customers are asking a different set of questions:
“How will this actually help my team?”
“Can it reduce workload — or just add another tool?”
“What data does it need to be useful?”
“Will it break compliance or security?”
Because while everyone’s talking about the future, SAP customers — especially those running real-world operations — want practical, safe, and business-aligned impact.
This blog isn’t about the promise of GenAI. It’s about what customers are actually asking for, right now.
First: What Is GenAI in the Context of SAP?
“GenAI” refers to AI models that can generate text, code, summaries, insights, or recommendations — based on prompts or context.
In an SAP world, that means:
- Summarizing customer interactions in SAP Sales Cloud
- Generating draft purchase requisitions or service tickets
- Suggesting pricing terms or delivery windows based on patterns
- Providing contextual help in SAP Fiori apps
- Drafting emails, quotes, or reports
It’s not about replacing humans — it’s about amplifying them with real-time, context-aware assistance.
What SAP Customers Are Not Looking For
Before we dive into the wishlist, it’s important to clear the air.
Here’s what SAP customers are not asking for:
- More dashboards with AI labels
- Abstract predictions with no actionable insight
- Another virtual assistant that doesn’t integrate
- Black-box models that can’t explain outputs
- One more tool their teams won’t use
Why? Because these customers have been burned before — by “AI-powered” solutions that overpromised and underdelivered.
So What Do SAP Customers Actually Want From GenAI?
After dozens of discovery workshops, demos, and advisory sessions, here’s what real SAP users — from CFOs to customer service agents — say they want.
1. Faster, Smarter Document Generation
“Can GenAI help us build draft quotes, emails, or reports faster?”
Yes — and this is where adoption can explode.
Examples:
- Generate a first draft of a sales quote explanation based on product configuration
- Summarize a long customer interaction history into a bullet-point brief for the next rep
- Draft a materials availability response to a customer’s inquiry
- Create a supplier onboarding checklist from a vendor master record
Why it matters:
This isn’t automation — it’s augmented execution. It saves time and reduces context-switching.
2. Insightful Summarization — Not Just Data Surfacing
“I don’t want another report. I want someone to tell me what it means.”
SAP customers are data-rich, insight-poor.
GenAI can help by:
- Summarizing exceptions in the week’s sales orders
- Flagging anomalies in goods receipt vs invoice
- Explaining why a project budget is trending over
- Extracting high-risk supplier mentions from notes, texts, and ticket logs
They don’t want raw data. They want narrative intelligence — in plain English.
3. Contextual Help Inside SAP Transactions
“I’m doing a task in SAP — help me right there, not in a separate tool.”
Instead of opening manuals or submitting IT tickets, users want:
- Inline explanations of fields, statuses, and rules
- Step-by-step guidance for rarely used processes
- Clarification of what went wrong in a failed posting
- Preemptive suggestions when filling out a complex sales order or service request
This turns SAP into a co-pilot, not just a database.
4. Quote and Configuration Support (Especially for Complex Products)
“If AI can help guide configuration and pricing, that would be real.”
In industries with complex variant configuration or CPQ flows, sales teams often struggle to:
- Understand what’s valid
- Know what’s allowed
- Get pricing right without delay
SAP customers want GenAI to:
- Guide users through product selection based on need
- Flag invalid combinations in real-time
- Suggest pricing tiers or discounts based on similar deals
- Explain why certain configurations are not manufacturable
The goal: reduce reliance on engineering for every quote.
5. Automated Suggestions in Customer Service
“Our agents spend too much time searching for previous tickets or responses.”
In SAP Service Cloud or similar CRM tools, GenAI can:
- Suggest responses based on ticket context and sentiment
- Pull relevant KB articles without search
- Summarize ticket history before handover
- Propose follow-up tasks or categorization codes
This leads to faster resolution, more consistent service, and better agent experience.
6. Help With Mass Changes and Master Data
“I have 200 materials to update — can GenAI help suggest values?”
While this is still emerging, customers want GenAI to:
- Detect outliers in master data
- Suggest missing values (e.g. missing units of measure)
- Group materials or vendors by pattern
- Auto-classify new entries based on historical data
Why it matters:
Master data governance is still a huge bottleneck — and GenAI can ease the load.
What Customers Worry About — And Rightfully So
SAP customers aren’t blindly jumping in. They ask smart questions:
- Where is the data coming from?
- Is this model trained on my data or public data?
- Can we explain how a decision was made?
- How do we ensure no confidential info leaks into the model?
- What’s the audit trail for AI-generated output?
They don’t want “cool.”
They want safe, compliant, business-embedded GenAI.
What’s Getting in the Way
Even when the interest is high, here’s what slows things down:
- Data quality issues
Garbage in = hallucination out. Many SAP customers know their master and transactional data isn’t clean.
- Disconnected systems
Sales quotes in one system, service tickets in another, product data in a spreadsheet. GenAI needs context — and fragmented landscapes get in the way.
- No clear owner
Is GenAI an IT initiative? A line-of-business tool? A data team effort? Many companies haven’t figured out where it belongs yet.
- Overhype from vendors
Too many PowerPoints. Not enough demos that show real SAP processes.
What to Do If You’re Exploring GenAI in SAP
- Pick a process, not a platform.
Start with one specific flow — quoting, ticket response, report summaries.
- Focus on time savings, not automation.
Let GenAI augment your users. The business case is often in minutes saved per task, not jobs eliminated.
- Invest in clean context.
Better input = better suggestions. Clean master data, well-labeled transactions, and tight integrations go a long way.
- Pilot with the users who feel the most friction.
Sales reps, service agents, and operations analysts often benefit first — and give honest feedback.
Final Thought: SAP Customers Want Help — Not Hype
The GenAI conversation is evolving.
SAP customers don’t want moonshots. They want:
- Less time wasted
- Fewer tabs open
- Fewer errors
- More support in moments that matter
They don’t need GenAI that “transforms the enterprise.”
They need GenAI that helps the person doing the work.
And that’s the opportunity — not in the future, but now.