how are you using AI tools on projects in 2025?

[Alice_Lahan]

Curious how others are handling AI tools in day-to-day project management. I keep hearing vendors pitch them as "time savers," but in practice I've found they add as many headaches as they solve. One example: automated reporting. Sure, it spits out a dashboard fast, but you still have to validate the data before handing it to leadership, otherwise it's just polished garbage. So my question: in your teams, what's actually useful from AI/automation in 2025? Is it task assignment, backlog grooming, sprint planning, risk tracking... or are we still better off with humans double-checking everything?

 

[brightlights]

A lot of the real value isn't in full automation but in how the tools augment what we already do. The most useful applications are in things like automated reporting and risk tracking. For example, AI can analyze project data to identify potential roadblocks or budget overruns before they become an issue but a human still needs to review the recommendations and decide on a course of action.

AI is also great for generating initial drafts of project documents, like a project charter or a communications plan. Saves a lot of time on the blank page problem but the final version still requires a project manager's judgment and context to ensure it's accurate and aligns with the project's specific needs. The biggest gains seem to come from using these tools to handle repetitive tasks so the team can focus on more strategic work, like problem solving and stakeholder management.

 

[Kdrazen]

AI mostly for draft reports and summarizing meeting notes. It speeds things up, but yeah, everything still needs a human check. I wouldn’t trust backlog grooming or risk tracking entirely to it yet because of too many context nuances AI can miss

 

[Alan]

That's a fair point about the validation problem, polished garbage issue is real.

What platforms are people even trying these days for PM work?