As a Project Manager, I Love Generative AI—But Not Why You'd Expect

When I hear discussions about AI’s near-term potential in project management, many of the discussed use cases fall into one of these two categories:

1. Writing Help: Project managers produce extensive written communication, not to mention written documents and other artifacts associated with projects. AI can potentially make the writing process faster or the piece of writing better fit-for-purpose.
2. Project Analysis & Recommendations: Can AI identify project risks early? Find and offer solutions to schedule slippage? Propose an ideal order for projects that optimizes resource utilization?

These are certainly great areas to get assistance. I don’t personally use it for writing help in my project role because I rely on writing to be a point of human connection in a remote-work world, and we don’t produce extensive documentation outside of our project software. I also don’t use it for project analysis and recommendations because AI typically needs to be integrated into the tools you already use in order for it to access the necessary data.

I am starting to experiment with letting it take notes during meetings, and I think it could add a lot of value here as I refine how I use it. I’m working with my IT department to test the AI meeting summary feature inside our virtual meeting platform, but I think I’ll need to work with another AI chatbot to distill the decisions and actions I find useful out of the long meeting minutes our platform creates. If you haven’t thought about using AI for meeting notes before, I found this webinar from PMI a helpful primer on where to start and what to consider.

But there are two other ways I’ve started using generative AI as a project manager that are already highly practical for me today, don’t require AI to be integrated into the software my company uses, and don’t raise concerns about company IP or sensitive data being shared with models for training.

That’s because I’m using AI chatbots as more of an assistant to me personally, making me more effective at my job. Here are the two ways I’m doing that:

An accountability partner on my productivity strategies.

Many of my blog posts talk about strategies I use to increase productivity and decrease stress in a job that can be pretty demanding. My strategies are helpful when I use them, but keeping up with them or applying them consistently isn’t always easy when, again, project managers are pulled in so many directions.

So I’ve really loved explaining to a chatbot what I need to accomplish for the day and what strategies I’d like to try. Then we refine the strategies together and adapt them around specific challenges or limitations (such as more meetings than usual). And once the plan is in place, I’ll check in with the chatbot throughout the day and tell it how I’m doing:

• Did I successfully follow through on high-focus tasks in the morning, or did I get distracted by incoming messages?
• Is there a new obstacle we need to adapt around?
• How well am I taking care of myself (breaks, food) amid my productivity goals?

If I make a plan on my own at the beginning of the day and it doesn’t work out, it’s easy to throw the plan away and give up. A chatbot helps me find a quick pivot to accommodate both previous goals and updated needs so I can keep making meaningful progress.

And honestly, I’ve found chatbots incredibly encouraging. They affirm and celebrate every task I check off my list and every decision that keeps me on track. They’re empathetic every time I fail. In a work era where many of us not only have to manage our tasks alone but do so physically alone (if we work remotely), talking through my workday with a robot feels a lot more like working closely with a coworker than I might have thought…without having to bug a real person about all the minutiae in my workday.

An accessibility tool when my brain gets stuck.

As a project manager I make a lot of judgment calls about the next move that’s most likely to keep a project on track. Sometimes these decisions are tricky, especially when I need to navigate dynamics among coworkers. There can be many factors to weigh all at once, and sometimes it’s too much data and my brain gets stuck or shuts down.

In the past, my best tool in this situation was to let the decision sit until the next day. My brain seems to process it in the background or overnight, after which the best move is more obvious. That’s great, but what if I have a lot of these decisions to make, or I can’t or don’t want to wait until the next day?

Now I can talk it through with a chatbot. I can get all the important factors down in writing so they’re not creating a traffic jam in my brain. Then I get some immediate options with pros and cons. I find it much easier to react to a chatbot’s suggestions and know which is best than if I have to think through the options on my own. If I don’t like the suggestions or realize I left out relevant information, we can continue the discussion. And typically it’s not hard to describe these types of situations without sharing sensitive information—the chatbot needs to understand general dynamics, not identifying details.

I’m sure AI will work its way into more and more of our work lives—in many of the ways we can foresee today, and in many we don’t. But if you give it a chance and experiment, it has plenty of benefits to offer you already—maybe, like mine above, benefits you didn’t expect.