Our study shows that a positive return on investment, project managers' trust in AI capabilities and their versatile benefits drive investments in artificial intelligence in project management.
Artificial intelligence (AI) is penetrating our working world ever more deeply and revolutionizing the way we plan, implement and evaluate projects. From automated task allocation to predictive analysis, AI offers endless possibilities for increasing the efficiency and success of projects.
We look at how AI can be used in project management and what challenges need to be overcome. This article is of interest to all project managers and companies who are considering investing in AI-based project management software, as well as to project managers who already have experience with it and want to support more areas with AI and solve current challenges.
As part of a larger study, we surveyed 2,500 project managers in 12 countries* and found that 46% use AI in their PM tools . This report takes a deep dive into that 46% (1,153 project managers) to find out how they use AI and what benefits they see. From Germany, 200 project managers were surveyed, of which 44% use AI in their project management tools. This article mainly refers to the global results. Data from Germany is highlighted when there is an interesting difference from the international average.
The most important highlights:
On average, project managers surveyed worldwide plan to increase their AI investments by 36% by 2025.
The main use cases of AI in project management are risk management, task automation and predictive analytics.
The biggest challenge project managers face is data quality.
48% see false trust or misconceptions about AI’s capabilities as the most dangerous disadvantage of AI.
Positive ROI and PM confidence drive further investments
The majority of project managers report the success of their current AI investments: 90% of project managers who use AI in project management reported a positive ROI in the last 12 months. Project managers say that investments in AI for project management in their company will increase by an average of 36% by 2025.
In Germany, AI investments in project management are expected to increase by 29% by 2025. 89% of project managers recorded a positive ROI.
As AI becomes more widely used, so does acceptance and trust in the technology. The willingness to delegate important tasks to AI is high among project managers surveyed worldwide: 85% say they trust the tool enough to do so.
This delegation not only improves productivity and efficiency, but also allows PMs to focus on more strategic aspects of project management, such as decision making and stakeholder management. This mix of trust, comfort and awareness drives momentum for further investment in AI and underscores its role as an important tool in modern project management.
The most important use cases of artificial intelligence in project management: risk management, task automation and predictive analytics
Current AI capabilities are quite effective when it comes to giving PMs deeper insights into potential risks, automating repetitive tasks, and creating more accurate forecasts, so it's only logical that these are the top current use cases of AI for project managers. Taken together, these AI-driven improvements can lead to more efficient project management and a higher success rate, ultimately driving business growth and competitiveness.
Let's look at examples of what these three main use cases might look like and how they fit together.
task automation
AI can take over repetitive tasks like project status updates, task notifications, and report generation that would normally take the project team hours or even days per week to complete. Automation allows the team to focus more on important, high-value activities, reducing project timelines and improving overall performance.
For example, in a software development project, developers used to have to manually record their working hours in a spreadsheet. This was time-consuming and error-prone. With AI, this process can be automated. The AI is integrated into a project management tool that manages the project's tasks and milestones. As soon as a developer starts a task, the AI can automatically detect this (e.g. through the activity in the code repository) and start time tracking.
predictive analytics
AI-driven predictive analytics can help you create an effective project plan and mexico telegram data identify potential risks before they happen. These tools can predict potential time and budget overruns by analyzing historical data and identifying trends and patterns. This foresight helps you plan more accurately, allocate resources better, and ultimately deliver projects with fewer disruptions.
In the example of the software development project, the automatically detects how far a task has been completed. The AI can make precise predictions about the expected completion of a task or the entire project based on the previous work speed and the tasks still open.
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 together and, when combined, lead to project success.
German project managers use AI for even simpler tasks
In German companies, however, the distribution looks quite different from the international average. German project managers primarily see the benefit in scheduling optimization and task automation. AI is used very little in predictive analysis. Project risk management also performs poorly compared to the international average. Accordingly, other countries surveyed seem to be tending to delegate somewhat more complex tasks.