Information Technology Project Managers

Right now, many IT project management tools incorporate AI to help with routine tasks. For example, AI “schedule optimizers” already promise to take over tedious calendar work and speed up scheduling ^[1]. AI tools can also analyze project data – for instance, research shows generative AI can cut time on content-heavier tasks (like writing reports or drafting plans) by roughly 40% ^[1].

In practice, this means AI can automatically summarize trends or forecast timelines and costs for you ^[2], helping with status updates and tracking progress. However, tasks that need personal judgment or conversation are still mostly human jobs. Things like understanding a customer’s needs or negotiating with suppliers involve trust and nuance that AI can’t fully handle ^[3].

In other words, AI tools often augment managers by handling data work and alerts, but the human manager remains in charge of decisions and people skills.

How fast companies use these tools depends on many factors. AI software for scheduling or reporting exists today, and it can boost efficiency (for example, PMs can work faster on reports with it) ^{[1] [4]}. But buying or building AI systems costs money and training.

Right now, surveys show most teams are only starting to try AI – one found only about 4% of project managers actually use it, though many plan to very soon ^[4]. Common reasons to adopt AI include saving time (66% of managers expect faster projects) and better quality (56% expect higher project quality) ^[4]. However, people must trust and learn the new tools before leaning on them.

In general, if projects need to run faster or have tight budgets, managers will push for AI help ^{[1] [4]}. Still, important human skills like communication, problem-solving, and teamwork will remain valuable. AI can do more of the routine work, but project managers’ leadership and people skills will stay essential for success ^{[3] [1]}.