Projects are not managed in a world of certainty. Even the best project plan is built on assumptions: that people will be available, approvals will arrive on time, suppliers will deliver, users will cooperate, budgets will hold, and technology will work as expected. Some of these assumptions will be correct. Some will not. The real work of project management is often about noticing the difference early enough to act.
A project plan is only useful if it remains connected to reality. Many projects begin with reasonable intentions, but once execution starts, information becomes scattered. Some updates are in emails, some in meeting notes, some in spreadsheets, some in peopleโs heads, and some are never recorded properly. By the time a formal report is prepared, the project may already have moved on.
Projects rarely fail because teams lack enough templates. They fail because the early thinking is weak. The scope is unclear, assumptions are not tested, stakeholders expect different things, and the schedule is built on hope rather than evidence. This is why planning remains one of the most important stages of project management.
Artificial Intelligence is entering almost every professional field, and project management is no exception. Many discussions around AI begin with a dramatic question: Will AI replace project managers? I think that is the wrong question. A more useful question is: which parts of project management can AI improve, and which still require strong human judgment?
Artificial Intelligence (AI), and especially Generative AI, is now entering almost every professional field. Project management is no exception. But the real question is not whether AI will replace project managers. That is the wrong starting point. The more useful question is: how can AI help project managers work better?
