-: Having a project plan is one thing,
but actually keeping it on schedule,
that's where things get tricky.
Gantt charts are a great way to map out work,
but building them manually is a huge time sink.
In this lesson, we'll use the project management co-pilot
to turn our project plan
into a structured, trackable Gantt chart,
helping us visualize progress, manage dependencies,
and stay on top of deadlines.
In a previous lesson, we used the co-pilot
to create a structured project plan,
breaking it down into phases, tasks,
and estimated timelines.
Now, we're taking that structured plan
and turning it into a Gantt chart
so we can track when each task starts,
what depends on what and how everything fits together.
A Gantt chart gives teams a clear roadmap,
making it easy to see overlapping tasks,
potential bottlenecks,
and how different parts of a project connect.
Normally, you'd have to manually enter tasks, durations,
and dependencies into a spreadsheet
or a project management tool,
which is a slow, tedious process,
but instead of spending hours doing that,
we're letting the Copilot take care of it.
In this lesson, we'll focus on two key steps.
First, we'll use the Copilot
to generate a structured Gantt chart
based on our project plan.
Then we will format the data for export,
so we can use it in Excel, Google Sheets,
or project management tools like Asana and monday.com.
Let's get started.
Since we already have a structured project plan
from our previous lesson,
our next step is to turn it into a timeline,
mapping out when each task starts, how long it lasts,
and what dependencies exist.
Instead of inputting all that manually,
we'll let the Copilot generate it for us.
One thing to check
before running this is that the Copilot
has code interpreter, and data analysis enabled.
This is what allows ChatGPT
to create visual representations of our project.
To generate the Gantt chart, we use this prompt,
"Convert the project plan we created
into a structured Gantt chart,
listing tasks, task descriptions, start and end dates,
durations, task owners, and dependencies.
The Copilot processes the project plan
and outputs the data in a Gantt chart-friendly format.
To do this, it uses Python, along with a few common
data visualization libraries
to organize and structure everything.
Now, each task is assigned a category, description,
start, and end date, and task owner.
With this structure in place,
we can visualize the entire project timeline,
and make sure nothing is scheduled out of order.
But having a structured list isn't enough.
We need to format it
so it can actually be used in a project management tool,
and that's what we'll do next.
Now that we have a structured Gantt chart,
the next step is formatting it for export,
so it can be used in Excel
or imported into project management tools
like Asana, Jira, or monday.com.
Manually formatting this data
would be another time-consuming task,
but again, the Copilot can handle it for us.
To generate an exportable table,
let's use this prompt.
"Convert this Gantt chart structure
into an Excel-compatible table with columns for task name,
task description, start date, end date,
duration, task owner, and dependencies.
Instead of the raw text output,
we now have a clean structured table
that can be imported directly into project management tools.
Once imported, we can decide which columns we need
and where the data should go.
This makes it easy
to quickly set up a project management workspace
based on the structured plan created by the Copilot.
Now let's walk through
how to import this data into monday.com.
First, log in and open the project where you want
to import tasks.
Then click the three dots on the top right corner.
Hover over more actions and select import tasks.
And next, upload the .XLSX file
we just downloaded from ChatGPT.
Choose the column for the task name.
Then map out the other columns
to the corresponding fields in monday.com.
Once everything is lined up, hit Next.
Choose how to handle the duplicates
and start the import process.
Give it a few moments
and you should see all your tasks populated in monday.com.
Now instead of manually entering data,
we have a fully structured project board,
ready to track progress, assign tasks,
and manage dependencies.
Automating this saves hours of work
and ensures teams have full visibility
into their deadlines and deliverables.
We've now taken our project plan from raw text
to a fully structured visual Gantt chart
that's ready for tracking.
Instead of manually building out timelines,
we've let the Copilot do the heavy lifting.
Organizing tasks with start dates, dependencies,
and clear timelines.
But project execution isn't just about scheduling.
It's also about prioritization.
Not all tasks carry the same weight,
and knowing which ones should take priority is key
to making strategic decisions.
In the next lesson, we will explore
how AI can help with project prioritization,
making it easier to focus on high value work
while balancing constraints like time,
resources, and business impact.
Your Copilot is now set up to automate Gantt chart creation
and project tracking.
Start using it to structure timelines,
export task schedules, and manage dependencies.
The more you refine its outputs,
the more valuable it becomes.
Next, we'll dive into AI-powered project prioritization,
learning how to identify high impact initiatives,
balance competing demands,
and make strategic decisions that drive real business value.
I'll see you there.