Beyond Email Edits: The Experiment That Transformed How I Use AI in Project Management

When ChatGPT launched in late 2022, the market flooded with AI tools promising to revolutionize project management. Every software platform added their own AI chat feature; tools for automated note-taking, calendar scheduling, and resource optimization multiplied overnight.

As a project manager, I was skeptical. These solutions seemed focused on replacing the administrative parts of our job—parts that, honestly, we already had decent systems for. The tools were either unreliable or didn’t fit our workflow, and none of them addressed the complex problem-solving that makes project management challenging.

I wasn’t particularly encouraged about AI’s future in our field until one project challenge completely changed my perspective…

The Problem: An Ambitious Idea Meets Reality

We’d just started working with a high-stakes client (think Alphabet-backed—big vision, bigger expectations) to launch and manage their social media and digital campaigns.

As part of our strategy, we pitched a content approach that relied on stunning, illustrated assets and each one taking a whopping 20 hours to create. These weren’t quick-turn graphics—these were detailed, intricate, award-worthy pieces. And the client? They loved them.

We knew this would be a stretch for our design team, so I did what any good PM would do: add a second designer, split up the work, and adjust their workloads in hopes we’d find the perfect balance.

Spoiler alert: We didn’t.

Come delivery day, the big impact assets weren’t ready. The week had been a blur of me running up and down the office between the desks of our designers trying to reshuffle priorities and carve out extra time, but still, it wasn’t enough.

We walked into that client meeting promising delivery of the final assets by the end of the week. Not ideal, but manageable; we had content to work with for now that was approved, and the illustrations would come soon enough.

But, then it happened again the following month.

I tried shifting things around—working with the strategists to push these big creative pieces to later in the calendar cycle and give the team more breathing room—but nope, same problem. And at this point, it was clear: we didn’t just need a better schedule. We needed a system.

The Lightbulb Moment: AI to the Rescue

Could we have just told the designer to work faster? Maybe. But when you’re aiming for award-winning creative, you don’t cut corners—you figure out a better way to make it work.

So, I did what any desperate PM does when staring down a problem…pulled up a spreadsheet! We already had the basic data—time estimates for each content type and monthly content calendars—what we lacked was a way to automatically translate content decisions into resource impacts.

Here’s what I envisioned:

1. A system where designers could be assigned specific content buckets monthly
2. Real-time visibility into how content calendar changes affected designer workloads
3. Automatic calculations that would eliminate manual hours tracking

It seemed simple enough and I knew that this was the way to confidently assign them their hours and trust the work could get done.

Now, I’m no math wizard, but I do love a good spreadsheet. The problem? I had no idea how to create the formula I actually needed. So, I threw the challenge at ChatGPT, described what I was trying to do, and, after a fair amount of back-and-forth, ended up with a working solution.

The final result? A beautifully simple, AI-assisted spreadsheet with two tabs:

• Tab 1: The content calendar, where strategists could select content types from a dropdown menu.
• Tab 2: A reference sheet listing each content type and its associated design hours.

The formula linked the two, so as soon as a strategist added content to the calendar, the spreadsheet automatically calculated the total design time for the month, per designer.

The strategists could see exactly how their decisions impacted each team member’s available hours. No more guessing. No more last-minute scrambles. Just a clear, data-driven resourcing plan.

The Outcome: A Happy Team, a Happy Client, and a Converted PM

The difference was immediate:

✔️ The big, high-effort assets got delivered on time.

✔️ The design team was no longer drowning.

✔️ The content plan actually worked.

But for me, the biggest shift was personal. Up until that point, I’d seen AI as a tool for small things—email edits, meeting recaps, the occasional “reword this so I don’t sound passive-aggressive” request. But this? This was different. AI had helped me solve a problem I wouldn’t have been able to fix on my own.

AI in Project Management Today

This experience changed my perspective on AI’s role in project management. Since then, we’ve integrated AI tools across our entire workflow:

Meeting Intelligence (Otter.ai or Circleback)

• Records meetings and creates summaries, transcripts, and action item notes
• Provides a reference to quickly find answers to the “what did the client say about that logo option again?” questions
• Validates decisions made in meetings through the AI chat feature

Project-Specific AI Assistance (ChatGPT)

• Allows team-collaboration on projects with all relevant project materials stored to provide them with the account and scope context they need as they work on deliverables
• Gives Project Managers a database to store decisions, scope changes, and feedback so that their client comms can be tailored to the account as the project progresses
• Helps all disciplines prepare their deliverables with strategic insights brought through the stored files into stakeholder interview questions, design ideas, content calendars, and more

Account Specific Messaging (Claude and ChatGPT)

• Creative writing with an assistant, tailored to a project’s demographic or target audience
• Problem-solving for complex email explanations to find clearer answers in less time
• Smarter responses for busy project managers

Task Optimization (Asana)

• Adding Smart Rules to projects based on recent project actions
• Using Smart Summaries to provide status updates within projects
• Relying on Smart Projects to quickly create new projects from scratch

Yes, we’re still using ChatGPT to edit emails—but now, it’s doing the heavy lifting. It’s generating solutions, vetting ideas, and validating our thinking so we can walk into every meeting (or hit send on every email) knowing we’re making the right call.

Looking Forward: The Future of AI-Enhanced Project Management

The transformation I’ve witnessed in just two years has completely shifted my understanding of AI’s role in project management. It’s not about asking the Asana AI chat to pull project hours or having Otter pull action items from meetings—features that often promise more than they deliver.

Instead, AI serves as the brain we sometimes wish we had—handling complex calculations, storing vast amounts of project context, and processing information in ways humans simply can’t.

For project managers wondering if AI is worth the investment, I offer this advice: look beyond the obvious administrative use cases. My journey began with skepticism about basic AI features and evolved into discovering how AI could solve problems I didn’t even know could be solved.

The key isn’t to replace your project management skills with AI, but to let it handle the cognitive heavy lifting while you focus on what humans do best—building great teams and delivering exceptional work.

Your next breakthrough might be just one spreadsheet formula away. But more importantly, it might come from realizing that AI isn’t here to replace the project manager—it’s here to give us capabilities we never had before.

A few years ago, AI felt like just a gimmick for project managers. Now? I wouldn’t work without it.