How I Actually Use AI in Excel To Analyze Data Faster (From a Regular Office Worker’s View)

Background: When Excel Starts Owning Your Life

Most of my workdays look like some version of this:

• A manager pings me on Teams: “Can you send a quick analysis of sales by region for the last six months… in the next 30 minutes?”
• Finance drops a giant Excel file into my inbox with 40,000 rows and a name like Final_v7_real_final_latest.xlsx.
• HR shares a survey file that mixes numbers, free‑text comments, blanks, and random merged cells.

For years, my “analysis workflow” was:

1. Copy the raw sheet.
2. Spend forever cleaning data.
3. Build a PivotTable.
4. Stare at it, try a chart, delete it, try again.
5. Realize I’m out of time and send whatever I have.

I’m not a data scientist. I’m just someone who lives in Excel more than I’d like to admit. When AI quietly crept into Excel itself and into add‑ins, I was skeptical. I’d tried random AI tools before that sounded magical but either:

• Broke on messy real‑world data
• Or took longer to configure than just doing the work myself

Over the past year, though, I’ve actually changed how I work with Excel. Between Microsoft’s own AI features and a few third‑party tools, I now lean on AI for a big chunk of my data analysis… with some clear rules and boundaries.

This is my honest experience of what actually helps, what’s overhyped, and what I’d recommend if you just want to get your work done without becoming a formula guru.

1. The AI Already Inside Excel: Analyze Data & Copilot

Analyze Data: The “What’s Interesting Here?” Button

In modern Microsoft 365, there’s a button in Excel called Analyze Data (it used to be called Ideas). It lives on the Home tab. You select a clean data table, click it, and a pane opens on the right with suggested insights and charts. You can also type questions in normal language, like “Total sales by region” or “Which product is growing fastest?” ¹

From a normal user’s perspective, it feels like this:

• You highlight your sales data.
• Click Analyze Data.
• Excel proposes charts and summaries you probably would have built… eventually.
• You click a suggestion you like, and Excel inserts the chart or PivotTable into your sheet.

The big catch: it really wants the data to be clean and in a proper table with clear headers, no merged cells, and no weird multi-row headings. ¹

In real life, I use it like this:

• Monthly sales report from different regions I cleaned the sheet a bit, converted it to a table, and hit Analyze Data. It immediately gave me:
  • Top regions by total revenue
  • A trend chart for revenue over time
  • A breakdown of revenue by product category

It wasn’t fancy analytics, but it gave me a solid starting point in about 30 seconds. I didn’t have to remember how to build every PivotTable from scratch.

How it feels to use: Like having a curious intern sitting beside you saying, “Hey, I noticed this pattern” and already having the chart ready.

When it fails for me:

• When the data is messy (text mixed with numbers, merged headers)
• When I want something very specific, like a niche KPI formula it doesn’t suggest
• When the dataset is huge or oddly structured

At that point, I either clean more or move to Copilot.

Copilot in Excel: Chatting With Your Workbook

In newer Microsoft 365 setups with Copilot, Excel gets a Copilot icon on the ribbon. You click it, a chat pane opens on the right, and you can literally talk to your sheet. ²

You can ask things like:

• “Highlight rows where margin is below 10%.”
• “Summarize revenue by region for the last 6 months.”
• “Create a new column that categorizes deals as Small, Medium, Large based on amount.”
• “Explain the formula in this cell.”

Copilot can:

• Generate and explain formulas
• Highlight, sort, and filter data based on your instructions ²
• Build PivotTables and charts
• Answer questions about trends, outliers, and summaries

There’s also a newer =COPILOT() function that lets you use AI directly in cells, like entering =COPILOT("Summarize this feedback", A2:A200) to categorize comments or summarize text. It’s rolling out gradually and still labeled as limited and beta. ³

Microsoft itself warns not to use this AI function for anything that absolutely must be precise and reproducible, such as formal financial reporting or legal documents. ⁴ That lines up with my experience.

A real example from my work:

• I had a sheet of 500+ customer feedback lines.
• I asked Copilot to:
  • Group comments into themes (pricing, product quality, delivery, support)
  • Give me a quick summary per theme
• It created a helper column with tags and produced a neat summary paragraph I pasted straight into a slide.

I did spot check it. It mis‑tagged a few comments, but the overall picture was correct and saved me an afternoon.

How it feels to use:

• Amazing when it works: “Oh wow, I don’t have to remember that formula anymore.”
• Occasionally a bit “magical” in a worrying way: “Wait… how did you calculate this? Is it right?”

My personal rule: AI is allowed to suggest and draft. I still check and own anything with real-world impact.

Copilot + Python “Think Deeper” Mode

If your Excel has Python in Excel enabled, Copilot can use Python behind the scenes for more advanced analysis. There’s an option called “Give a unique insight using Python” and a deeper mode called Think Deeper that creates a separate sheet with Python-generated analysis. ⁵

From a non-technical user view:

• You describe the kind of deeper analysis you want in plain language.
• Copilot generates Python code, but you mostly see the results: extra charts, more complex comparisons, etc.

I don’t use this daily, but for large, messy datasets where normal Excel feels like it’s choking, this has impressed our analysts. For me, it’s more “push-button advanced mode” than anything I actively configure.

The New “Agent Mode” Vibe

Microsoft has also started talking about a more agent‑like mode in Excel, where Copilot breaks down tasks into steps and shows the plan in a sidebar. The idea is: you ask for something big (like “build a budget tracker from last year’s data and highlight risk areas”), and it walks through subtasks more transparently. ⁶

This is still evolving, but the direction is clear: Excel wants to be less of a manual toolbox and more of a conversation partner.

2. Third‑Party AI Add‑ins That Live Inside Excel

Native tools are great, but there are also add‑ins that plug directly into Excel and feel like “supercharged helpers.” Two that have stood out for me are Formula Bot and ChatGPT for Excel / TwistlyCells.

Formula Bot: Turning Plain Language Into Formulas and Insights

Formula Bot started as a “generate Excel formulas from text” tool and now offers an Excel add‑in that sits in a side pane. ⁷

From inside Excel, it can:

• Turn instructions into formulas (“Calculate year-over-year growth in this column.”)
• Explain existing formulas
• Classify and extract information from text (like sentiment or categories)
• Convert PDFs to Excel and help with data cleaning

In one project, I had:

• A column of long support tickets
• A request to “tag each row as Billing / Technical / Product / Other”

I asked Formula Bot in its pane to categorize each row into those buckets. It generated a formula and/or filled a column for me. I still cleaned a bit, but it shortened the job from a few hours to under one.

How it feels:

• Very focused on formulas and practical tasks
• Less “chatty,” more “give me what I need in cells”

I like it when I’m stuck on a complex formula or need to mass-tag text.

ChatGPT for Excel (TwistlyCells): AI Functions Directly in Cells

Another route is the ChatGPT for Excel add‑in (also called TwistlyCells). It gives you AI-powered custom functions like AI.FILL, AI.FORMAT, AI.EXTRACT, AI.LIST, AI.CHOICE, and so on. ⁸

You install the add‑in, and suddenly you can write formulas like:

• =AI.FILL(A2:A500, "Fill missing city names based on patterns")
• =AI.FORMAT(A2:D500, "Standardize phone numbers and dates")
• =AI.EXTRACT(A2:A500, "Pull out the company name")
• =AI.LIST("Generate 10 sample product categories")

The tool connects to models like GPT‑4 and Claude, but that’s transparent for normal usage. ⁸

A real moment it saved me:

• I had a mixed list of job titles and departments in one column.
• I used an AI function to separate them into two clean columns.
• It wasn’t perfect, but it handled 90% correctly, far faster than manual splitting.

How it feels:

• Very “Excel-ish” — you stay in the grid and just call AI like another function.
• Best when you know roughly what you want, but don’t want to write complex formulas.

Claude for Excel (Early Days)

Anthropic has also started rolling out Claude for Excel, where Claude runs in a sidebar and can read, edit, and generate spreadsheets, fix formulas, and explain what it’s doing cell-by-cell. It’s currently in limited beta mainly for larger organizations and financial workflows, with strong integrations to market data. ⁹

I’ve only seen this in demos so far, not in my own tenant. From what I can tell, it feels more specialized for teams who live in financial models and need real-time external data, not just internal spreadsheets.

3. Using External AI Beside Excel (Export, Analyze, Bring Back)

You don’t always need an add‑in. Sometimes the easiest setup is:

1. Export or copy data from Excel
2. Paste it into an AI chat tool (ChatGPT, Claude, etc.)
3. Ask for summaries, groupings, or formulas
4. Bring the results back into Excel

OpenAI’s newer “agent” features even go further and can create spreadsheets and run multi-step workflows for you, like doing financial analysis or assembling reports. ¹⁰

There are also tools like Zapier that connect Excel to ChatGPT (OpenAI). For example, you can trigger ChatGPT analysis whenever a new row appears in a table. ¹¹

In my actual work:

• I rarely use Zapier for Excel because IT needs to approve it.
• I do often:
  • Copy a small sample of rows,
  • Paste into ChatGPT,
  • Ask things like “Give me categories and suggested formulas to calculate key metrics.”

It’s low-tech but surprisingly helpful.

4. A Simple Comparison: What’s Good For What?

Here’s how these options feel to me in daily work.

Table: How I Choose Between Excel AI Options

5. Practical Workflows That Actually Save Me Time

Workflow 1: “I Need a Quick Insight Before a Meeting”

Scenario: Your boss sends a sales dump and asks, “Anything interesting in here before the 2pm call?”

How I handle this efficiently:

• Clean just enough:
  • Make sure there’s one header row.
  • Convert the data into an Excel table.
• Use Analyze Data:
  • Let it suggest top trends and charts.
  • Insert one or two useful charts (like revenue by region or by product).
• Ask Copilot:
  • “Summarize the main trends in this table in 3 bullet points.”

Result: I often walk into the meeting with:

• A simple chart or two
• A short summary like:
  • “Region West grew 15% quarter‑over‑quarter.”
  • “Product line B is flat despite overall growth.”
  • “Average discount increased in Q4.”

Even if I don’t fully trust every detail Copilot suggests, it gives me a solid starting narrative.

Workflow 2: Cleaning a Disaster Sheet

Scenario: You inherit a sheet with:

• Mixed date formats
• Empty cells
• City and state jammed into one column
• Random capitalization

What I do:

• Use a tool like ChatGPT for Excel / TwistlyCells:
  • =AI.FORMAT to standardize dates and phone numbers
  • =AI.FILL to fill missing entries based on patterns
• For text splitting:
  • Either ask Copilot “Split this column into city and state”
  • Or use an AI function to extract just the city or just the state

Yes, I could do all this with classic Excel functions, but:

• Remembering the correct TEXTSPLIT, LEFT, RIGHT, FIND combinations is not my idea of fun under time pressure.
• The AI options feel more like “describe what you want in normal words.”

I still scan the results for obvious errors, but it often gets the bulk of the work done.

Workflow 3: Making Sense of Survey Comments

Scenario: HR sends you 1,000 employee survey comments and asks:

• “Can you summarize the main themes?”
• “How many are positive vs negative?”

My go‑to setup:

• Keep comments in one column in Excel (e.g., column B).
• Use Copilot or an AI add‑in to:
  • Create a new column with sentiment: Positive / Negative / Neutral
  • Create another column with themes: Pay / Workload / Management / Culture / Other
• Ask Copilot:
  • “Count how many comments fall into each theme.”
  • “Summarize each theme in 2–3 bullets in plain English.”

This used to be a two‑day chore with color highlighting and manual tagging. With AI, it becomes:

• An hour of setup and checking
• Enough structure to give HR a clear story

Do I trust it 100% on each individual comment? No. Do I think it gives a solid, honest picture overall? Yes, as long as I sanity-check a sample.

Workflow 4: “I Don’t Know What to Measure”

Sometimes the hardest part is deciding what to analyze.

When I feel lost, I:

• Copy a small anonymized sample of my data to ChatGPT in the browser.
• Ask:
  • “If you were a manager, what KPIs would you build from this data?”
  • “What kind of Excel formulas could help track performance here?”

It usually suggests:

• A few obvious metrics I forgot
• Some formula ideas
• Sometimes even natural-language suggestions I can feed back into Copilot or an add‑in

This is more about idea-generation than automation, but it’s surprisingly helpful for building dashboards or reports that make sense to managers.

6. A Few “Gotchas” I’ve Learned The Hard Way

• AI doesn’t get office politics. It can’t know that your VP hates stacked bar charts or that Finance insists on a particular definition of “gross margin.” You still need to adapt its output to your culture.
• You can’t skip understanding your data. It’s tempting to just ask AI “What’s interesting?” and copy‑paste the answer. That’s how you get burned in a review meeting. I still spend time understanding the columns and basic logic.
• Licensing is messy. Some of these tools require:
  • A Microsoft 365 Copilot license
  • Add‑in subscriptions
  • Or approval from IT You might not have everything available in your company, so part of the job is just seeing what you’re allowed to use.
• Data privacy matters. Built‑in Microsoft tools in your tenant follow Microsoft’s enterprise privacy model. ² Third‑party tools often say they’re secure, but I still avoid sending highly sensitive personal or financial data anywhere external without checking policy.
• Speed vs. control. Sometimes it’s actually faster to write a simple formula yourself than to argue with AI over the prompt. I try AI first, but if it starts hallucinating or giving weird results, I drop back to normal Excel.

7. My Honest Take: Is AI in Excel “Worth It”?

For me, the answer is yes — with expectations in the right place.

Where it’s absolutely worth it:

• Quick initial analysis on new datasets
• Cleaning ugly real‑world sheets
• Summarizing large blocks of text
• Getting unstuck on formulas
• Preparing “good enough” charts and talking points before meetings

Where I still go manual:

• Final numbers in board decks
• Anything that gets audited
• Complex models where I want to understand every cell

Emotionally, I’ve moved from:

“This is a gimmick, I don’t trust it.”

to:

“This is a very helpful junior colleague who works fast but needs supervision.”

If you already spend big chunks of your week in Excel, it’s worth trying:

• Analyze Data for quick wins
• Copilot (if your org has it) for conversational analysis
• One solid add‑in (Formula Bot or ChatGPT for Excel) for formula help and text work

Give it a couple of real projects, not just toy examples. You’ll notice the time savings most when you’re under a deadline and still manage to send something that actually looks thoughtful.