Chapter 3. Choosing your first AI project
- Selecting AI projects that are matched to your organization’s AI capabilities
- Prioritizing your AI projects and choosing which AI project to run first
- Formulating a research question that’s related to a business problem
- Pitfalls to avoid when selecting AI projects, and best practices of such projects
To develop a sustainable analytical organization, you shouldn’t start with an AI project that involves complex technical challenges. Instead, you should choose your initial project so it provides clear and actionable results quickly. Your whole process should be organized to optimize time to success.
This chapter shows you how to select your first AI project. It also teaches you how to check if the research question that your AI project uses correctly reflects the business concerns it’s supposed to address. Finally, it presents a list of common pitfalls that young AI teams might fall into.
I assume that your long-range goal is to build an AI team that will help the success of your parent organization by delivering a series of successful AI-related projects. To achieve that, you need to understand the journey that a successful AI team will take. This section explains that journey.
Tip
If you’re after a one-off AI project, you might be better off buying an off-the-shelf solution or contracting with an outside partner to do it for you.