SAP is continuing to push ahead with its AI strategy, focusing specifically on data integration. With the planned acquisition of Reltio, SAP wants to combine SAP and non-SAP data and make it usable for AI. SAP AI is thus clearly moving towards a platform based on consistent and networked corporate data.
The development clearly shows that competition in the area of AI is not only decided by models, but above all by data.
SAP AI explains:
SAP KI stands for the use of artificial intelligence within SAP ecosystems, particularly in areas such as ERP, supply chain and financial processes.
However, the decisive factor for powerful AI is not the model itself, but the database. AI can only work as well as the data on which it is based.
In many companies, however, data is fragmented. Different systems, formats, and silos make uniform use difficult.
This is exactly where SAP AI comes in. The aim is to connect data from various sources and make it available consistently.
This creates the basis for more precise analyses and better decisions.
SAP and Reltio: What's behind the takeover
With the planned takeover of Reltio, SAP is pursuing a clear goal: the standardization of company data.
Reltio specializes in so-called master data management. This involves consistently managing central data such as customer, product or supplier data.
This data forms the basis for many business processes.
By integrating Reltio, SAP can combine data from different systems â even outside its own platform.
This is a crucial step towards making AI applications more effective.
Why data integration is so important
A powerful SAP AI platform requires a uniform database.
Without consistent data, errors, inconsistencies, and inefficient processes occur.
By integrating SAP and non-SAP data, companies can get a complete picture of their business processes.
This makes it possible to:
- better forecasts
- more informed decisions
- automated processes
- higher efficiency
Data integration is thus becoming the basis of modern AI systems.
SAP AI in Practice: Specific Use Cases
SAP AI is already being used in many areas today.
In the financial sector, for example, AI can detect anomalies and identify fraud at an early stage.
In the supply chain, SAP AI helps to forecast demand and avoid bottlenecks.
AI is also used in human resources, for example when analyzing applications or employee development.
Another important area is customer management. AI can analyze customer data and enable personalized offers.
These use cases show how important a consistent database is.
Data silos: The biggest problem for many companies
Many companies are struggling with so-called data silos.
This means that data is stored in different systems and is not connected to each other.
This fragmentation makes it much more difficult to use AI.
SAP addresses this issue by integrating data platforms and tools such as Reltio.
The goal is a central view of all relevant data.
This is the only way AI can develop its full potential.
SAP AI vs. other AI platforms
Compared to other AI platforms, SAP relies heavily on corporate data.
While many providers focus on general data or cloud platforms, SAP focuses on operational business processes.
This is a clear advantage for companies that already use SAP systems.
By integrating non-SAP data, this advantage is further expanded.
SAP is thus positioning itself as a platform for data-driven corporate management.
Where the platform is developing
The development of SAP AI is showing a clear direction.
In the future, the platform will be even more focused on data integration and automation.
An important trend is the increasing use of real-time data.
Combining AI with other technologies, such as automation and analytics, will also become more important.
In the long term, many business processes could be fully supported or controlled by AI.
However, data quality always remains the basis for this.
SAP's Strategy
Companies should reassess their data strategy in the context of SAP AI.
A first step is to analyze the existing data landscape.
What data is available? Where are the silos? How can they be resolved?
Building on this, companies should invest in data integration and quality.
Selecting the right platform also plays an important role.
SAP offers an integrated solution here that is constantly being expanded.
Why data is becoming a decisive factor
The competition for AI will increasingly reveal which companies can make the best use of their data.
Technology alone is not enough.
Access to high-quality and networked data is becoming a decisive advantage.
SAP addresses exactly this point and is expanding its platform accordingly.
Companies that rely on a consistent data strategy at an early stage can secure clear competitive advantages.
Conclusion: SAP AI shows why data is more important than models
The development around SAP and the takeover of Reltio makes it clear that the key to successful AI lies in data.
Companies must standardize and make their data accessible in order to effectively use AI.
SAP is positioning itself as a central platform for data-driven business processes.
For companies, this means aligning their strategy accordingly and taking action at an early stage.
The KI Company helps you optimize your data strategy and successfully implement AI in your company. Please feel free to contact us for a non-binding consultation.
SAP AI FAQ
What is SAP AI?
SAP AI describes the use of artificial intelligence within SAP platforms and applications.
Why is data integration important for SAP AI?
Because AI can only work reliably with consistent and networked data.
What does Reltio do?
Reltio offers solutions for master data management and helps to standardize company data.
What are the benefits of SAP AI?
Better decisions, automated processes, and more efficient operations.
What should companies do now?
Review your data strategy and invest in data integration.
