Is Excel Still Worth Learning in 2026, Now That AI and Python Exist?
Copilot can write your formulas and Python can crunch millions of rows. So is Excel still worth your time? Here is the honest answer, backed by real numbers.
A student asked me last week, "Why learn Excel in 2026? Copilot writes the formulas, and real analysts use Python anyway." It is a fair question, and it deserves a fair answer, not a sales pitch.
Think of it like a kitchen knife
A professional chef owns fancy equipment. Sous vide machines, blast chillers, industrial mixers. But every single day, before any of that gets touched, the chef picks up a basic knife to chop an onion. Nobody skips the knife because they own a mixer. The knife is just the fastest tool for that one job.
Excel is that knife for data work. It is not the most powerful tool in the kitchen. It is the tool you reach for first, every single day, because it is already open, everyone around you understands it, and it gets small jobs done in minutes.
What is actually happening
Excel has not disappeared, and it has not stood still either. Microsoft has been adding Copilot features that suggest formulas, summarize a sheet, spot trends, and build charts from a plain English request. In parallel, Excel now supports 30 plus additional file types for analysis and can pull in data from emails, Teams, and the web, not just your spreadsheet.
At the same time, real job market numbers tell a clear story. Excel shows up in well over half of data analyst job postings, right alongside SQL, Power BI, and Python. It is not fading from job descriptions. It is still one of the first things listed.
So no, Excel is not being replaced. It is being upgraded while it keeps doing the same daily job.
The honest nuance
Here is where I will not oversell it. Excel does have real limits, and pretending otherwise does you no favors. It struggles past roughly a million rows. Tracing exactly what a complex formula did six sheets ago is genuinely hard. Copy-paste mistakes in spreadsheets have caused real, expensive errors at real companies. And if you need to repeat the same analysis every week without manual clicking, a spreadsheet is the wrong home for that.
That is exactly where Python or SQL take over. Bigger data, repeatable pipelines, and analysis that needs to be traceable and testable belong in code, not in a workbook full of hidden formulas.
Think of it as a size problem, not a competition. Most working analysts still start in Excel for a quick look at data, then move to Python or SQL once the job needs scale or automation. Excel and code are not rivals. They are different tools for different sized jobs, and most analysts use both in the same week.
What this means for you as a learner
If you are starting out, Excel is still the right first stop, not because it is impressive, but because it teaches you how to think about data before code gets involved. Sorting, filtering, pivot tables, and basic formulas teach you what "clean data" even means. Skip that step and jump straight to Python, and you will spend your first months confused about concepts that Excel would have taught you in a week.
Copilot changes what Excel work looks like, not whether you need to understand it. It can write a formula for you, but if that formula quietly grabs the wrong column or wrong range, you need to notice. That only happens if you already know what a correct answer should roughly look like.
A simple test for yourself: open any spreadsheet you use for work and try to explain, out loud, what every column and pivot table on it is actually doing. If you can, you understand your data. If you find yourself saying "I am not sure, someone else built this," that is your sign to go back and learn the fundamentals properly, before leaning harder on AI shortcuts inside Excel.
Where to go from here
Excel is not going away in 2026, it is just getting a smarter assistant sitting next to it. The people who benefit most from that assistant are the ones who already understand what good, clean data looks like underneath it. If you want an honest read on where your own skills stand right now, our free AI Readiness Assessment is a low-pressure starting point, and our Labs give you hands-on practice at your own pace.
Ready to turn reading into a career?
Get your free data-readiness score and a personalised roadmap in 10 minutes.
🎯 Take the free assessment📖 Keep reading
7 Excel Formulas That Save You Hours Every Week
You do not need to be an Excel expert, just these seven friendly formulas. SUM, IF, COUNTIF, VLOOKUP and more, each with a plain-English example.
Read article →How Does AWS Athena Actually Work? A Simple Guide for Data Beginners
AWS Athena keeps showing up next to S3 and Glue in data job posts. Here is what it actually does, how its pricing works, and whether it is worth learning, explained without the jargon.
Read article →Is SQL Still Worth Learning in 2026 Now That AI Can Write It For You?
AI chatbots can write SQL queries in seconds now. So does that mean you can skip learning SQL? Here is the honest answer, backed by real numbers.
Read article →