Pie charts are the first visual most teams reach for when they want to answer simple but important questions: Who are our top customers? Which channels drive revenue? How is budget split across campaigns? In Excel and Google Sheets, a pie chart turns a flat table into a quick story about proportions, helping founders, marketers, and operators align decisions around what is actually moving the needle.
But building those charts by hand gets old fast. Every new CSV, every weekly report, every client dashboard means re-cleaning columns, re-creating summaries, and reformatting colors and labels. That is where an AI agent shines. Instead of spending your time clicking through Insert > Pie again and again, you define the pattern once and let an autonomous computer agent repeat it reliably at scale, so every dataset becomes a visual in minutes, not hours.
If you run a business, agency, or sales team, you live in spreadsheets. Revenue by product, leads by source, spend by channel – all of it usually lands in Excel or Google Sheets. A pie chart is often the simplest way to answer: what slice of the whole does each category own?
The problem is not making one pie chart. It is making the fiftieth this month, across different files, clients, and campaigns. That is where combining manual skills with AI agents gives you leverage.
1. Prepare your data
2. Select the data
3. Insert the pie chart
Excel will immediately render a pie with each slice sized by the values in column B.
4. Format labels and percentages
5. Tidy colors and layout
Pros (Manual Excel)
Cons (Manual Excel)
The flow in Google Sheets mirrors Excel, which is perfect when your team is remote or client data lives in Drive.
1. Structure your sheet
2. Insert the chart
3. Customize for clarity
Pros (Manual Sheets)
Cons (Manual Sheets)
Now imagine you never touch Insert → Pie again.
An AI computer agent running on a platform like Simular Pro can behave like a power assistant sitting at your keyboard:
You define the workflow once – 'for every new weekly performance sheet, create three pie charts: revenue by channel, leads by source, and spend by campaign' – and the agent executes it across desktop, browser, and cloud.
Pros (AI Agent Automation)
Cons (AI Agent Automation)
If you only build a chart once a month, keep it manual. But if you:
then it is time to let an AI agent handle the drudgery while you focus on interpreting what each slice of the pie is really telling you.
Put categories in one column and numeric values in the next, with a single header row (for example, A1:B6). Avoid blanks or text in the value column. Pie charts expect one data series, so do not include multiple rows of totals. Once structured, highlight the full table including headers before inserting your pie chart so Excel can correctly map labels to slices.
After creating your pie chart, click it once to select, then click the plus icon (Chart Elements) beside it and enable Data Labels. Next, right-click a label and choose Format Data Labels. In the pane, check Category Name and Percentage, and uncheck Value if you want a cleaner look. Set Label Position to Center so the percentage appears inside the slice for easier reading.
Excel and Google Sheets cannot chart text directly. First, count how many times each answer appears. You can use COUNTIF or a pivot table: list unique responses in one column, then use COUNTIF to tally occurrences in the next. This summary table (answer plus count) becomes your chart data. Highlight it, insert a pie chart, and format labels to show each option’s share of responses.
Avoid pie charts when you have many categories (more than 6–7), values that are very close to each other, or negative or zero values. In those cases, a bar or column chart in Excel makes it much easier to compare differences. Also, if you care about trends over time rather than proportions at one moment, use a line chart instead of building multiple pies that are hard to compare.
An AI computer agent can open new Excel or Google Sheets files, clean and group data, create standard pie charts, and apply your preferred colors and labels automatically. You define the workflow once – for example, 'from this CSV, summarize revenue by channel and build a pie' – and the agent repeats it whenever new data arrives, saving your team from repetitive clicks each reporting cycle.