## 6 Discussion and Conclusions
This can be because of external factors that affect their decision making, which results in irrational decisions and may lead to an overestimating or underestimation of time and cost and affect the outcome of projects. Project managers' previous decisions might also lead to anchoring bias, which can affect estimates. According to the experts, a common goal should be to have the ability to obtain reliable information and data about a project to be able to make rational, numerical decisions based on valuable data. AI in project management is designed to provide valuable insight into decision making and planning. Although AI can assist managers with decision making, it might be complicated for AI to deal with cognitive biases. It might cause problems such as biases being built into algorithms, which can result in unreliable outcomes. The cognitive biases that affect project managers decision-making processes are common and result in using shortcuts in thinking, which may appear when programming and designing AI due to biased assumptions. The right data must be inserted into systems to collect and process the data, as missing data or information might also cause biases. Therefore, it is essential to research the potential biases and the errors it can cause when developing AI software. Biases can be a challenge when developing AI, and the algorithms used for AI might be influenced by biases. As mentioned during the interviews, the developers of AI might not be able to choose the optimal key indicators or variables to design the appropriate system for project managers without bias. To prevent this from happening, good communication between managers and AI developers is essential, as the design of AI needs to incorporate ideas from the end-user, which is the project manager. Project schedule, cost and risk management are the three areas of project management that are considered to be weakest, as these areas are where project managers can do better when it comes to estimates and also areas that are prone to the impact of cognitive biases. They have the greatest potential for improvements. Further research can give more specific results about AI's impact on project management. In-depth interviews with specialists in the field of AI could be conducted to give more specific answers to exactly how AI can be used in the different elements of project management. Research on cognitive biases when developing AI systems for project schedule, cost-and risk management could give better insight into the potential biases that can occur in AI. This could give an even deeper understanding of how AI can be used for specific tasks and its future effect on project management. It would also be interesting to research the knowledge of AI within the project management profession, as several of the respondents thought it to be difficult to imagine the effects of AI, which may have resulted in some inconsistency in their answers. Conceptualization, H.T.I. ; Methodology, T.V.F. ; Validation, H.I.J. ; Investigation, T.V.F. and H.G. ; Writing--original draft, T.V.F. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Not applicable. **Conflicts of Interest:** The authors declare no conflict of interest. **Appendix A**  
**Table A1. Statements for the interviews. **