SAP AI: A 5-point Scorecard for Selecting the Right Use Case

Summary: What is a successful AI solution? Its the one that solves a complex problem and delivers measurable impact. When there are so many competing problems to choose from, how do we select the right use-case? Is there a framework to assess or compare use-cases? This blog attempts to address these questions.

The success of any AI solution lies in solving a real business problem, supporting a business process, or innovating a business model. Many organizations make the mistake of looking at ready AI solutions and working backward to see if they can use them. SAP has a vast catalog of solutions, applications, and AI capabilities that can overwhelm anyone. The right approach should be inside-out: first identify your own use case, then leverage AI for success.

So here are some tips for identifying the right SAP AI use case.

1. Start with the business pain, not AI

No pain, no gain!

Don't start with, “Where can we use GenAI?” It's easy to fall in love with the amazing solutions in the catalog. However, look at real-world problems or opportunities in your business.

Start with:

• Where are employees spending too much time?
• Where are decisions slow or inconsistent?
• Which processes have high error rates?
• Where are exceptions difficult to identify?
• Where could better decisions directly improve revenue, cost, or customer experience?

For example, instead of saying “Let's build an AI procurement agent,” start with a problem such as:

“Our buyers spend several hours every week reviewing purchase requisitions and identifying exceptions.”

2. Define the problem before defining the AI solution

The devil lies in the details!

Once you identify the pain areas and select some candidates, take the effort to define the process in greater detail. A good use case needs more than a one-line description. Understand the end-to-end process. Who interacts with the AI? What systems does it need to access? What decisions can it make? Where does a human need to intervene?

Consider:

• Human-AI interaction: Is AI recommending, assisting, or executing?
• Process flow: What happens before and after the AI interaction?
• Integration: Which SAP and non-SAP systems and data sources are involved?
• Change management: How will users' roles and ways of working change?
• Exception handling: What happens when AI is uncertain or wrong?
• User experience: Should users interact through Joule, a Fiori app, another interface, or a combination?

This is where many AI projects discover that the hard part isn't building the AI. It's redesigning the process around it.

3. Do you have clean data?

‘You can’t manage what you don’t measure’

AI needs data. And not just lots of data, but relevant, reliable, and usable data.

If the basic material master or business partner data is inconsistent or missing, you cannot run a model to predict using such data. So the availability of good data is an essential prerequisite for identifying the right use case.

Before you short list a use case, assess the following:

• Is sufficient historical data available?
• Is it accurate and complete?
• Is it accessible to the AI?
• Is it structured consistently?
• Is the historical data still representative of today's business?

Data readiness should be a gate for the AI use case, not an activity discovered halfway through the project.

4. Define governance and security upfront

‘Distrust and caution are the parents of security’ - Franklin

Before you give any user access to your SAP system, thoroughly check their roles and responsibilities, and use that as the basis for controlling access. Any AI model should also pass a similar test. It helps to plan it all beforehand: will it be AI Only, AI + Human (Human in the loop), or Human + AI (Human first)?

An AI use case is incomplete without its governance model.

Ask:

• What data can the AI access?
• What data must it not access?
• Who can use the capability?
• What decisions can AI make autonomously?
• Which decisions require human approval?
• Can the AI action be audited?
• What happens when the AI gets it wrong?

For example, an AI agent that recommends a purchase order change is very different from one that can execute the change.

5. Set realistic ROI and success measures

‘Measure what is measurable’ - Galileo

AI doesn't need to transform the entire company to be successful.

A use case that reduces invoice processing time by 20%, cuts manual effort by 30%, or improves exception detection can be a very good investment.

Define success before building:

• Time saved
• Cost reduction
• Error reduction
• Faster cycle time
• Better compliance
• Improved customer or employee experience
• Adoption and usage
• And be realistic.

Also plan how you will use the resources freed up by the AI use case. For example, if the process becomes 50% faster, what more can you do with that time? Or how can you deploy your key resources for doing strategic work and automating the regular chores?

Define your AI Readiness Score

When you compare several potential use cases, it helps to quantify the score based on the parameters discussed above. Or you can customize the criteria and metrics according to your requirements.
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Imagine an SAP customer wants an AI agent to identify and optimize inventory levels.

About Jade Global

Choosing the right use case is the first step in your AI journey. Identify real-world problems and then search for AI solutions. SAP systems are a great source of structured historical data. Security and access are robust. Roles and responsibilities are well defined. Business processes are mapped and documented. All these are great foundations for implementing AI.

To help you navigate the selection process, map requirements to SAP AI solutions, and deliver a Proof of Value, you need a strong partner like Jade Global. We offer a complete suite of SAP AI offerings, from concept to implementation. Our team of domain and AI experts can help drive your AI journey!

Turn the right SAP AI use case into business value with SAP implementation services. Partner with Jade Global’s SAP experts to prioritize the right opportunities and build a clear path from idea to implementation. 

Frequently Asked Questions:

How to choose the right SAP AI use case?
Start with a real business problem, then assess process, data, governance, and expected value. The best SAP AI use cases solve a clear need and have the right foundation to move forward.

What is the SAP AI readiness scorecard?
The SAP AI readiness scorecard helps compare SAP AI use cases across business value, process readiness, data readiness, AI and human readiness, and governance readiness.

How to calculate ROI for SAP AI projects?
Measure the impact of SAP business AI use cases through time saved, cost reduction, fewer errors, faster cycle times, better compliance, and improved user experience.

What are the prerequisites for SAP Joule adoption?
Before implementing SAP Joule, assess your process, data quality, integrations, security, governance, and human involvement to determine whether the business process is ready for AI.

How to evaluate data readiness for SAP AI?
For successful SAP AI adoption, check whether your data is sufficient, accurate, complete, accessible, consistently structured, and relevant to current business needs.