From my experience, this could be done in about 7 steps:

Overall, deploying AI in an Excel spreadsheet requires a combination of technical expertise, data preparation skills, and problem-solving abilities. With the right tools and approach, however, AI can help you unlock valuable insights and make more informed decisions in your work. I hope this works out for you. Good luck. However, you may also want to look into Python.

Two questions. 1. Please define what you mean by AI. Do you mean something like what Herb Simon spoke about, do you just mean doing statistics (or more specifically unsupervised learning), or something else? 2. Can you can why you are restricting answers to Excel? Not that you can't do interesting things with it, but it is not what most people would use for what many people call AI.

Deploying a Python deep learning or AI model to work with MS Excel can be done with the PyXLL library, which allows you to run Python code in Excel as a user-defined function (UDF). Here are the general steps to deploy a Python deep learning model to work with MS Excel using PyXLL: Write Python Code: Write the Python code for your deep learning model using a library such as TensorFlow, Keras, or PyTorch. Make sure to include a function that takes the input data and returns the output of the model. Register Python Function as UDF: Use PyXLL to register the Python function as a UDF in Excel. This will allow you to call the Python function from within Excel, passing in the input data and receiving the output of the model. Run Model in Excel: Once the Python function has been registered as a UDF, you can run the model in Excel by calling the function and passing in the input data. Here's a link to the PyXll guide for more detailed information. https://www.pyxll.com/docs/userguide/udfs/introduction.html#:~:text=Calling%20your%20Python%20Function%20from%20Excel&text=You%20can%20use%20the%20PyXLL,check%20the%20PyXLL%20log%20file