Your team is working on an AI-enabled chatbot to be placed on the website. The goal of the chatbot is to be able to answer questions 24/7 to service clients around the globe. When evaluating your data you realize you don't have enough data to train the model.
What's the best course of action?

Your team has built a new robot that roams the halls at your organization and helps with various things such as small deliveries. However, you notice that many employees are opting not to use the robot. When you ask them why they tell you that the robot looks "creepy" and they would rather not interact with it.
What's going on here?

You just joined a new company and they want to start their first AI project. Senior management thinks the best approach is to just buy AI from a vendor. You know that AI is something you do, not something you buy.
What is your next best course of action to address this?

A team is getting ready to begin working on a ML project. They need to build a data preparation pipeline and someone on the team suggests they reuse the same pipeline they created for their last project.
What's wrong with this suggestion?

An inexperienced team is training a neural network model on a desktop computer and this is taking a significant amount of time. What would you recommend to them to speed up model training?