AI in project management: what changes are already taking place in the workplace?
AI is a hot topic everywhere. Interest is also growing rapidly within project organizations. Not because projects will be fully driven by AI tomorrow, but because the nature of the work is already starting to change today.
In the field of project management, this is particularly evident in two areas: Project Controls Management (PCM) and Document & Information Management (DIM). Reporting is becoming smarter, document workflows more efficient, and analyses available more quickly. At the same time, there is a growing need for structure, standardization, and control.
The question, therefore, is not whether AI affects project management, but rather: what does this mean in practical terms for day-to-day work?
For this article, we spoke with colleagues in the field: a project controller, a document controller, and a solution consultant. Their experiences clearly illustrate where the opportunities lie and where the biggest challenges still remain.
More data, more speed, higher expectations
According to Dennis van Loon, who works as a Project Controller, the change is most evident in the growing demand for data.
“Particularly with the introduction of Power BI and the growing number of reports it contains, it’s clear that the appetite for data is growing rapidly. More details, more information—everything has to happen faster.”
Whereas reports used to be prepared primarily on a periodic basis, organizations now expect faster insights and greater flexibility. Last-minute changes, additional analyses, and more in-depth data queries have become increasingly common.
This means that the role of project control is shifting. Less time is spent gathering information, and more focus is placed on interpreting it.
AI as a catalyst for routine tasks
It is precisely in repetitive tasks that professionals see the greatest potential for AI.
Dennis cites cost allocations and recurring analyses as examples. Every month, time entries must be checked, rates must be linked, and WBS elements must be validated. This requires a lot of manual work.
“I see the greatest potential in repetitive tasks and analyses, especially when dealing with large data sets. That’s where the power of AI really shines.”
Gerben Jacobs, a Solution Consultant, also sees that as the biggest benefit.
“Manually entering codes, summarizing texts, filling in metadata… basically all the manual tasks that take a lot of time.”
Here, AI is not seen as a replacement for expertise, but as a tool to streamline tasks that require significant resources yet add little substantive value.
In document control, the role is shifting from execution to oversight
Within document control, that change may be even more noticeable.
Stan Brouwer works with SharePoint and document workflows on a daily basis within projects. He sees how automation is already making many tasks more efficient.
“Thanks to a Power Automate flow, instead of having to manually fill in 14 metadata fields, I now only have to fill in a maximum of 4.”
Standard reports from SharePoint can also be automatically generated and sent. Setting them up takes time, but they significantly improve efficiency throughout a project.
However, according to him, the real shift lies in the role itself.
“Instead of manually checking all documents for metadata, it will be much more about managing the data.”
That calls for a different approach: less focus on post-hoc monitoring and more on designing processes effectively in advance.
The biggest mistake: thinking that AI solves poor processes
A common theme in all these conversations is the same warning: AI only works well if the foundation is right.
Gerben sees this happen regularly in organizations.
“Many companies are now asking how AI can help with their work, but it soon becomes clear that their processes aren’t properly documented. That’s always the first step.”
This is also a familiar scenario in document management. Metadata, naming conventions, approval processes, and handover to the client must first be clearly defined before automation can truly add value.
Stan confirms that:
“A project needs to have a solid foundation. That’s always been the case, but it’s becoming even more important now.”
AI amplifies what already exists. Good processes get better. Bad processes become problematic more quickly.
Technology also requires a change in behavior
Another challenge lies not in systems, but in people.
Stan notices that many users still fall back on old ways of doing things.
“People still prefer leaflet after leaflet after leaflet. Because that’s what they’re used to.”
Although platforms like SharePoint can operate much more efficiently, this does require a different way of thinking—less focused on storage and more on information.
Dennis also emphasizes that using AI requires new skills.
“You need to know how to ask the right questions, and it’s always important to verify the results.”
AI does not provide definitive answers. It remains essential to maintain a critical eye toward the output and to take responsibility for the information you share.
Don’t automate everything just because you can
The rise of AI makes it tempting to want to make everything smarter. However, a more nuanced approach is needed.
Stan is clear about that:
“It’s easy to think, ‘I can automate that.’ But you have to take a critical look at whether it will actually pay off in the long run.”
Automation should not be an end in itself. The question should always be: Does this make the project better, faster, or more reliable?
That decision is still a human one.
What will really be valuable in the future?
When repetitive tasks take less time, it frees up time for other work.
Dennis plans to focus primarily on developing his own Power BI reports to better meet the needs of the refinery in Rotterdam.
Gerben mentions change management and improving information processes.
Stan particularly values the ability to combine his systems expertise with project-specific requirements.
This shows where the future of project management lies: not in having fewer people, but in having different expertise.
The professionals who remain valuable are those who combine subject matter expertise with an understanding of systems, who understand processes and are able to guide change.
As Dennis puts it:
“You have to embrace new tools and learn how to use them. It’s very important to keep up with the changes that are taking place.”
AI is transforming project management not only technically, but also organizationally
AI is not just an IT issue. It affects processes, collaboration, and decision-making.
Within both PCM and DIM, the focus of work is shifting from manual execution to management, analysis, and design. This requires standardization, clear processes, and professionals who look beyond the tool itself.
Organizations that are preparing for this now are not only building more efficient projects, but also a stronger project organization for the future.