In January, we ventured an initial outlook on the development of artificial intelligence (AI) for the year 2024. In this article, we want to show you the specific areas where AI can already be useful for your company today and how you can identify them. 

In our forecast, we came to the conclusion, among other things, that AI will become more invisible overall and further optimize the user experience. However, we also found that generative AI seems to have reached its zenith for the time being and that exaggerated AI promises are increasingly proving to be unrealistic. This is partly due to the over-hype generated by the major technology companies in particular. In this context, it is clear that despite the progress made in generative AI and co-pilot systems, major breakthroughs are still a long way off.  

AI in everyday business: distinguishing between fad and added value 

Over the past two years, many people have conveyed the feeling that AI will soon be the ultimate tool for solving every conceivable business task and problem. In this context, Artificial Intelligence has been portrayed as a technology for everyone that saves time and money and creates innovations out of thin air without any major training. However, most people can already see from their own day-to-day work that we are still a long way from reaching this point. Worse still, trust in innovation in general and AI in particular is in decline. The question therefore arises as to which applications AI and automation actually have the greatest benefit and how companies themselves can identify these useful areas of application. First things first: the answer to this question is, as almost always, extremely individual. Nobody can relieve you of the preliminary work of analyzing for yourself where the added value of such applications lies in your specific case. You should therefore take a closer look at the following aspects. 

  1. Identification of tasks that can be automated 
    Before investing in automation technologies, it is important to conduct a thorough analysis of existing operational processes. Identify repetitive and manual tasks that require little specific expertise, such as data entry, scheduling or standard report generation. These activities are ideal for automation as they are often time-consuming and can be performed faster and error-free by machines.

  2. Understanding the technology 
    Invest time and resources to understand how automation and AI tools work. This includes not only the technical aspects, but also understanding the impact on workflows. Training for employees who will be working with these technologies is critical to ensure they are used effectively. 

  3. Creating a scalable infrastructure 
    Ensure that your IT infrastructure can support the introduction of automation technologies. This includes assessing existing hardware and software and any upgrades that may be required to ensure compatibility and efficient performance. The ability to quickly ramp processes up or down as needed is key to long-term success. Find out how to successfully master the complexity of system integration in our detailed blog post. 

  4. Ensuring the quality of the data 
    Automated systems and AI applications are heavily dependent on the quality of the underlying data. Incomplete or incorrect data can lead to inefficient processes and inaccurate results. Invest in good data collection and data cleansing practices to ensure that your automation projects are built on a solid data foundation.

  5. Continuous monitoring and adaptation 
    Implementing automation is not a one-off project, but a continuous process. It is important to regularly monitor and adjust the performance of the implemented systems. Use feedback from employees and performance data to further optimize processes and ensure they remain effective as business conditions change.


Investments in AI and automation are promising if you have obtained precise information in advance about where their use makes sense and is cost-efficient. This often means that individual niche applications and processes in which special algorithms are used are particularly suitable for the introduction of artificial intelligence. However, these must first be validated through data collection and analysis.

With our help you can quickly identify suitable applications and processes in your company. Then you too will quickly benefit from AI and automation. 

About the author

Mathias Herrmann


Mathias Herrmann is an internet entrepreneur going back to the Internet’s early days with a deep interest in digital and future technologies. For over 20 years, he has been helping companies make the most of their data by forging innovative solutions – without forgetting the people behind the data.

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