Integration and artificial intelligence

Today, we continue the theme of the future of enterprise information systems integration. That the future will be all about cloud services is now almost certain. However, in addition to the cloud, another new phenomenon is also coming into play, namely “artificial intelligence”, also referred to by the acronym AI.

You can read about this topic almost everywhere at the moment. You can even try it out for yourself and find out for yourself what possibilities or limitations this technology brings with it. So everyone can see today that, when AI is used correctly, it can produce very interesting results.

So the logical question is whether and how AI can be used in innovation for better business. Publicly available AI models primarily offer functionalities based on generating information available on the Internet. These models can indeed process the information you enter, but who can guarantee that the internal information thus entered cannot be subject to data leakage to competitors? Also, using direct AI outputs without processes to control them can harm rather than help the company.

Therefore, for the use of AI for business, it is recommended to use products that are designed for such use and have also solved the issue of security and data personalization.

While the massive expansion of AI use in enterprise IS still has a long way to go, the right scenario using AI on a proven and secure platform can start helping the enterprise today.

A good example is the integration of generative AI into solutions built on SAP, which enables companies to harness the power of algorithmic creativity to solve complex business problems and innovate faster. As part of the modern SAP BTP cloud platform, a set of interesting SAP AI Business Services tools are already available today and are gradually becoming standard in modern S/4HANA tools. However, you can also use these tools as available technology for your solutions built on your own ideas for AI innovation. For example, you can use them to automate processes based on extracting information from different types of documents. This in conjunction with another service, Business Entity Recognition, can identify any type of business information in unstructured text.

Another example of using the services is to analyse customer preferences and behaviour to create personalised recommendations for targeted marketing campaigns or tailored offers. The result can be a significant improvement in customer satisfaction and conversion rates.

Using AI, companies can also automate repetitive, low-value tasks. This allows employees to focus on more strategic activities, while generative AI-based systems take care of routine tasks. The result is an increase in overall efficiency and productivity.

Of course, there’s also the option to integrate other high-quality AI tools into your enterprise systems, which are well suited for integration with enterprise information systems such as Microsoft’s Azure OpenAI or IBM’s Watson.ai, which can perform data analysis based on the meaning and syntax of human speech, for example.

So those with a taste for innovation and, above all, a good idea can try to use AI to significantly advance the quality of an information system today.