People ask me all the time what to do if they don’t have paid Copilot or Power Automate or any of the other “new wave” Microsoft tools. Usually it comes from two groups: analysts who genuinely want to learn this stuff, and managers who are getting asked about it and don’t want to make a blind commitment.
The funny thing is: not having Copilot isn’t really the barrier people think it is. Most teams have bigger, older problems that no AI tool is going to magically solve. And honestly, getting those things sorted out now will make life a lot easier once you do turn these tools on.
Start by improving the data you already have
As an Excel trainer and MVP, I see the same patterns across scores of organizations: the data people rely on every day is held together by luck and muscle memory. Columns shift around, naming is all over the place, refreshes break, and everyone has a slightly different version of the same file.
People want Copilot to fix that. It won’t. It can’t. But you can fix quite a bit of these broken workflows right now, no Copilot required:
- Turn your ranges into proper Excel Tables.
- Move the weekly cleanup steps into Power Query.
- Stop hard-coding your data sources (pasting CSVs on top of last week’s data, pointing to someone’s Downloads folder, etc.).
- Keep your raw data intact instead of overwriting it every cycle.
- If the data comes from an external system, pull it the same way every time. Don’t manually export one week and copy/paste the next.
These small, boring steps are what make a dataset reliable enough for anything downstream: formulas, PivotTables, automation, or Copilot.
If you need a place to start with this, begin with my book Modern Data Analytics in Excel:
It walks through everything from tables to Power Query to building data models the right way. Once the foundations are in place, the rest of the “AI stuff” starts behaving a lot more predictably.
And even before Copilot arrives, remember that if you’re on Microsoft 365, you already have the Analyze Data button in Excel. It’s free, built-in, and a great way to practice asking AI questions about your dataset, without exposing anything sensitive to an external model:
While you’re waiting, build the skills Copilot works best alongside
Additionally, if you have access to Python in Excel, this is a great time to start getting comfortable with it. I don’t mean jumping into machine learning or trying to become a data scientist overnight. I just mean learning the basics: generating clean sample data, reshaping messy tables, doing simple transformations, or sanity-checking calculations.
You don’t need Copilot for any of that. And once Copilot is turned on, having even a tiny amount of Python literacy goes a long way. You understand more of what it’s suggesting. You can verify its logic. You can use Python for the heavy lifting and Copilot for the explanation layer. The two complement each other really well.
And there’s a larger reason Python matters so much here: Python in large part is the language of modern AI. Almost every major AI model you’ve heard of was trained with Python. The entire machine learning ecosystem—TensorFlow, PyTorch, scikit-learn—lives in Python. Copilot’s Advanced Analysis feature uses Python behind the scenes:
That means when Copilot generates Python for you, you’re speaking the same language the model understands natively. A little Python knowledge lets you sanity-check the code, extend it, and know when something looks off. It’s one of the highest-ROI skills you can build while waiting for Copilot to arrive.
The same goes for Office Scripts and Power Automate if your organization already has them. I’m not suggesting you run out and try to replace Copilot with these tools (you won’t, because again, it’s not meant to replace them). But knowing the basics now means you’ll eventually have a much cleaner handoff between what you do manually, what Copilot helps you with, and what you automate later. Even something as simple as learning how to record an Office Script and look under the hood will make Copilot’s script-generation features feel far less mysterious when they land.
I explain this a lot in my courses: Copilot isn’t a standalone solution. It’s part of a larger ecosystem. A little familiarity with Python, Power Query, and Office Scripts makes your prompts clearer and your results better.
And a quick note on using free AI tools responsibly
If you’re leaning on the free versions of Copilot or ChatGPT while you wait for the paid version at work, If you’re leaning on the free versions of Copilot or ChatGPT while you wait for the paid version at work, that’s completely fine and not a bad idea. But a quick reminder I tell all my corporate clients: don’t paste anything sensitive into them.
Keep it to synthetic data, scrubbed examples, structure and logic, formulas, and generic versions of your workflow. Save the real business data for the paid, enterprise-secured tools when they arrive.
Conclusion
Ultimately, getting “AI-ready” takes far more than purchasing a Copilot license. It requires getting your data into shape, building a few adjacent skills, and creating an environment where Copilot can actually help you once it arrives. Most of the heavy lifting happens long before the AI shows up. Teams that take the time to clean up their inputs now are the ones that see the fastest payoff later.
If you want help getting your team ready for all of this—data foundations, Python, Copilot, Power Query, Office Scripts, or anything in between—I teach this every week for organizations of all sizes. Reach out if you want to talk through what a practical, non-disruptive path to AI-powered Excel looks like for your team: