Microsoft To Do now supports natural language for creating tasks on Windows

Microsoft To Do Windows 10
Microsoft To Do Windows 10 (Image credit: Windows Central)

What you need to know

  • Microsoft To Do now allows you to create reminders and tasks using natural language.
  • When creating an item, you can use words such as "tomorrow," "daily," and "noon" and the app will automatically add those details to your entry.
  • You can choose to turn off smart date and time recognition on a case-by-case basis.

Microsoft To Do recently gained support for natural language. Users of the app can now type details for a task and have To Do extract important information for an entry. For example, you could enter "submit project report tomorrow" and the app would set the due date for the next day.

Natural language supports adding a due date, creating a reminder, and setting a task to recur on a regular basis. Microsoft shares some examples of how to use the new functionality in a Tech Community post.

In some cases, a word may have two meanings, which could lead Microsoft To Do to create a reminder when you don't want it to. The app supports turning off smart date and time recognition on a case-by-case basis. For example, you may type a reminder that says "buy food for April" referring to a dog named April rather than the month.

If you press the backspace key on a highlighted word, you can have Microsoft To Do unrecognize that word.

At the moment, natural language support only works in the Windows version of Microsoft To Do. The feature is also restricted to those who have their language set to English (EN-).

Sean Endicott
News Writer and apps editor

Sean Endicott is a tech journalist at Windows Central, specializing in Windows, Microsoft software, AI, and PCs. He's covered major launches, from Windows 10 and 11 to the rise of AI tools like ChatGPT. Sean's journey began with the Lumia 740, leading to strong ties with app developers. Outside writing, he coaches American football, utilizing Microsoft services to manage his team. He studied broadcast journalism at Nottingham Trent University and is active on X @SeanEndicott_ and Threads @sean_endicott_.