German project managers use AI for even simpler tasks

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In the example of the software development project, the AI ​​regularly analyzes the code and automatically detects the extent of completion of a task. Based on the previous work pace and the remaining tasks, the AI ​​can make precise predictions about the expected completion of a task or the entire project. 
Risk management
AI tools can analyze historical data to predict potential project risks and suggest mitigation strategies. By identifying and mitigating potential issues early, you and the project team can proactively address risks and avoid costly delays. 

By comparing actual progress with the planned schedule, AI can identify potential delays early and alert the project manager. AI-based tools can continuously analyze the source code and identify potential errors, security vulnerabilities, or inconsistencies early on.
As you can see, the most important areas of AI in project management belong c level executive list together and, when combined, lead to project success. 

In German companies, however, the distribution looks quite different from the international average. German project managers primarily see the benefits in scheduling optimization and task automation. AI is used very little in predictive analytics. Project risk management also performs poorly compared to the international average. Accordingly, other surveyed countries seem to be already tending to delegate somewhat more complex tasks. 

The biggest challenges of artificial intelligence in project management: data quality, employee acceptance and data protection
Despite the countless benefits of AI in project management, there are also challenges. Addressing these challenges is crucial for the successful use of AI in project management. The three most frequently cited challenges are key aspects that must be considered when implementing AI in project management. 

What's interesting here again is the difference in the responses of project managers worldwide compared to those in Germany. While the three biggest challenges are the same, the ranking is different. In Germany, 43% struggle with data protection, while this number is significantly lower worldwide at 32%. 

We want to look at the three most frequently mentioned challenges and explain why they are difficult to overcome.