Artificial intelligence is an aid, but not a panacea.

Rainer Trischak, Porsche Informatik

12. April 2021

How Porsche Informatik applies artificial intelligence in the company

The use of artificial intelligence has great potential in the industry when applied in the right areas. Application examples from the Salzburg-based IT leader Porsche Informatik demonstrate which areas those are.

Artificial Intelligence (AI) is a technology of the future with great potential – but it must be used correctly. “Artificial Intelligence is not a panacea.” This is a good way to start a conversation that shows what AI can actually do. What Rainer Trischak, Managing Director of Porsche Informatik, wants to express is that just because AI is currently hyped, it is not the solution to every problem. However, if used correctly, it can be a very helpful tool.

Porsche Informatik is driving digitalization in the Porsche Group

Porsche Informatik is one of the leading IT companies in the state of Salzburg. With the development of tailor-made business software for wholesale, retail and after-sales (service) as well as spare parts sales and financial services, Porsche Informatik, as a subsidiary of Porsche Holding, contributes to the success of Europe’s largest automotive retail group.

Many digital tools, such as cloud-based applications and artificial intelligence, are used for this. Managing Director Rainer Trischak and Business Unit Head Retail Services Thomas Soboll provide an insight into how Porsche Informatik uses artificial intelligence for itself and its customers.

AI can help, but not replace

“Artificial intelligence is implemented in the corporation as a support service,” emphasizes Rainer Trischak. “It never replaces a workforce, but supports them in doing their work more efficiently and faster.” The use of AI makes sense for tasks that occur routinely, that often need to be repeated and are not too complex. An example: In order to increase the customer experience, dealers must upload photos of cars to their online platform in a certain order, first a photo from the front, then from the side, then from the interior, etc. An artificial intelligence can be trained to recognize what is visible in the photo and to put it in the correct order. This saves dealers a lot of time.

The use of AI is also very suitable for monitoring ERP systems such as the retail system Cross. Cross is a very large system with tens of thousands of international users. If there are problems, such as in the performance or speed of business processes at individual dealer locations in the system, it is detected before the dealer notices or calls the support. The first-level support of Porsche Informatik is relieved and the dealers are pleased with a well-functioning system.

Crux of Data Processing

Artificial intelligence can be used to make processes faster and more efficient. However, it is less effective for complex tasks that require more human thinking. The basis for using AI is “clean data.” Learning the proper handling of data for the use of AI, also known as data literacy, had to be learned by Porsche Informatik and their clients. “Only when the data is properly processed and understood can AI work as desired. Data protection must also always be ensured,” explains Thomas Soboll. The quality, quantity, and availability of data are essential factors in the application of AI methods.

Data literacy is a continuous learning process. One reason why Porsche Informatik also relies on external support and cooperation. For example, they use the AI software from the Salzburg-based company Blumatix, which automatically recognizes and processes invoices. For an AI, it is complex to accurately determine and process individual data fields from differently designed invoices. The well-functioning system from Blumatix, however, makes invoice processing much more efficient.

How to get started with AI

For SMEs that want to invest in this area, Thomas Soboll advises first considering possible application areas, such as simple routine processes. As a second step, he recommends checking whether access to the required data is available and whether the company has the tools to process the data accordingly. The company culture is also important – are employees open to AI software, and can they handle it?

If these parameters are given, Thomas Soboll recommends approaching an experiment with external experts. “And one last tip: Start with organizational data, not personal data.”

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