Next Level Digital Transformation - will GenAI alone bring the big shift for (SAP) initiatives?

Motivation

Digital transformation is critical in today's business world, especially for companies that rely on SAP systems. SAP, a leading provider of enterprise software, plays a central role in numerous organizations worldwide. With the emergence of new technologies such as artificial intelligence (AI) and machine learning, the question is: can GenAI alone make the big shift for SAP transformations?

The integration of GenAI into SAP systems undoubtedly has the potential to transform the way companies optimize their business processes and improve their performance. By leveraging advanced algorithms and data analytics, GenAI enables companies to make informed decisions, automate processes and create personalized customer experiences.

However, it is important to emphasize that GenAI alone is not enough to bring about a complete SAP transformation. Success depends not only on the technology, but also on other critical factors such as business strategy, change management and expertise. Companies need to ensure that they have the right skills and resources to effectively integrate GenAI into their SAP systems and maximize the benefits.

Overall, however, it is crucial that companies take a holistic approach that not only relies on GenAI as the sole solution, but also takes other key factors into account. Only by combining technology, strategy and expertise can companies successfully manage the major shift in their SAP transformation and set themselves up for a successful future.

Use Case

To make things a little easier, I would like to use a small use case to illustrate important aspects that are crucial for the success of a GenAI project. I would like to use the following use case:

?We want to use Gen AI to help our support staff solve routine B2B tasks more efficiently!“

• What exactly are our goals?

Integration of the project idea into the overall company's goals. It's not about introducing a technology, but about supporting the strategic goals and creating added values. Of course there are prototypes and the building knowledge is extremely important, especially in this area, but concrete projects should always have a concrete and, in the best case, measurable goal.

• How should it be integrated into our processes?

Local optimizations can sometimes even have a negative impact on the overall picture. It is therefore important to check how the activities are integrated into the overall process and whether framework conditions may even have a negative impact on the success of the project.

• How do we get correct data from our systems?

System landscapes and data architectures in companies have often grown dynamically and are not homogeneous. Ideally, it is therefore important to simplify these with the help of enterprise architecture or at least to check where current and correct data comes from for the GenAI project.

• What do I need to consider when introducing GenAI?

In addition to legal regulations, companies often have internal regulations and framework conditions that need to be examined in particular now in order to avert negative negative impact.

• How do I get a good picture of my landscape?

Without a clear picture of the IT architecture, it is often almost impossible to achieve the best possible added value with new initiatives. Therefore, in my opinion, it is necessary to document the current landscape and dependencies in order to quickly realize high-quality GenAI projects with confidence

• Do I have to think it all up and build it myself?

In addition to the challenges described above, GenAI is a highly complex technology. Therefore, you can gain a lot of speed if you develop your own solutions based on SAP services and content.

• How do I know what the GenAI is doing and whether everything is working?

Once the GenAI is running and supporting our employees, there will certainly be a reason to celebrate! But the initiative should definitely not stop there: We should in any case actively keep an eye on and improve performance, data quality and AI specific issues such as hallucination.

• What should a current (SAP) landscape look like?

At SAP, there is the term Clean Core - there are a number of thoughts and ideas behind it. In any case, a clear and simple architecture based on standards is a major success factor. If this is not the case, other challenges often have to be solved with a GenAI project.

• How do I keep track of the many initiatives?

In addition to GenAI projects, companies typically have a whole host of other projects ranging from technical upgrades to major transformations. In order to create added value in the long term, it helps immensely to document the dependencies, milestones and goals and make them universally available.

• If I want to get started, how do I go about it?

Every start is difficult. In the SAP context, I can recommend the Discovery Center or API Business Accelerator Hub, for example.

Support the introduction of GenAI

With SAP LeanIX's application portfolio management product, you can store all key information about artificial intelligence (AI) software in a single repository. From here, you can log a range of metrics in custom dashboards that you can share with all your stakeholders.

Using the SAP LeanIX architecture and roadmap planning solution, you can then experiment with this data in a sandbox environment to see what potential changes could move your infrastructure forward. Once you have a vision for the future, you can map a path from the current situation to your destination.

Together with SAP Signavio and SAP Cloud ALM as a business transformation suite, we can address and highlight many points to support sustainable solutions and ensure added value through GenAI initiatives.

AI governance in SAP LeanIX

The AI governance extension to the meta model in SAP LeanIX provides you with improved AI governance and adoption tools, allowing you to effectively track, manage, and categorize AI usage and risk. The extension enables you to adopt best practices for modeling AI in your workspace for both commercial off-the-shelf (COTS) and self-built software.

With the AI governance extension, you get the following benefits:

• AI integration and governance: Integrate AI technologies into your IT landscape, ensuring they align with your organization's policies and standards. Establish standards for assessing AI risk and business criticality.
• AI adoption: Create a shared understanding of where AI adoption can most benefit the organization and make AI adoption visible across the IT landscape.
• AI impact overview: Understand how AI technologies impact various aspects of your IT landscape.

By using the AI governance extension, you can get valuable insights, such as:

• Objective: How does generative AI contribute to your business objectives?
• Business capability: Which business capabilities have high potential for efficiency or automation?
• Applications: Which AI algorithms and large language models (LLMs) are available and applied for which use case in applications?