How much percentage of time is saved by PMs Using AI ?

Totally Agree Luis, that's why Human-in-loop is important !!

Thank you Lissette - 20-30% is still a great deal. Agree with your point on the time savings during key decisions and strategic discussions.

Absolutely true Syed, I have seen AI doing wonders by skimming through the outlook emails and alerting, summarising and even creating draft responses.

Aaron, thank you for your inputs. AI can significantly enhance many Project Management activities, provided the Project Manager knows how to use it effectively. It's also important to ensure that any AI usage complies with the organization's AI policies and data security guidelines.
Here are a few practical examples that Project Managers can try using any standard AI platform:
1. Project Charter and Project Plan Generation
By providing contract documents, statements of work, or requirements, AI can generate an initial draft of the Project Charter and Project Plan in seconds. Traditionally, preparing the first draft for a moderately sized software project can take 2–4 days. With AI, after a few prompt refinements and reviews, a high-quality version can often be ready in less than an hour.
2. Kick-off Presentation Creation
Creating a comprehensive project kick-off deck typically takes a couple of days. AI can dramatically reduce this effort by generating a professional presentation based on project documents, contracts, and requirements. The Project Manager can then review, tailor, and refine the content to meet the project's specific needs.
3. Analysis of Project Data from JIRA or Other Tracking Tools
AI can quickly analyze data exported from JIRA or similar tracking systems to produce valuable insights, including:

• Defect trend analysis
• Aging analysis
• Pending and overdue action tracking
• Sprint and delivery metrics
• Risk identification based on correlations across multiple trackers and project documents

These examples only scratch the surface of what's possible.
The key isn't just having access to AI; it is knowing when, where, and how to use it effectively. Equally important is recognizing that AI is an assistant, not a replacement for sound project management judgment. Many critical PM responsibilities, such as stakeholder management, negotiation, decision-making, leadership, and handling complex project dynamics, still rely heavily on human experience and expertise.

You mentioned about organisations relying on the notes taken, AI can even read that and yet save lot of time of the PM in coming up with action items, next steps, meeting minutes and status reports.
Agree ?

Thanks Sergio, 95% is a BIG deal !! Since it is based on your experience, I would be interested to know more on the nature of project and the key use cases, appreciate any insights !

I partially agree. Give me a template and all the data I need and I can pump out a project charter or kick-off presentation in significantly less time than 2-4 days, too. I'm not saying I can synthesize all the information faster than AI, but the main bottleneck isn't typing.

I don't want to spend too much time talking about (or capturing) meeting notes. If I had to capture a transcript, I'd likely use AI. At a minimum I'd record it and have Word transcribe the recording - I could do this before I had AI tools. Fortunately, it's been over 20 years since I've had to capture a full transcript of a meeting. I capture key points, decisions, and action items during the meeting. That's it. Yes, AI can do this, too, but I've found I learn more about the project when I'm synthesizing the information, asking questions as needed, and writing it down as it's being discussed. It also keeps my mind from wandering (some meetings can just drag on). AI can't replace the knowledge and context I've gained through doing this.

I'm glad you brought up analyzing project data and specifically mentioned Jira. It's one of the handful of work/project tracking tools where the AI is more than a GenAI writing assistant. The real power here is not that it speeds up the production of project management artifacts, it's that it has the potential to help speed up effective decision-making.

I think we're mostly on the same page - that you have to have access to the right kind of AI capabilities and know when, where, and how to use them effectively. A project manager that works in a heavy artifact-driven project environment is likely to get more benefit from using GenAI than a project manager with less administrative burden, which is what too many conversations about AI usage focus on. To your point, this only scratches the surface of the various AI capabilities, which extend far beyond GenAI.