3 Mapping the AI solution space

 

This chapter covers

  • Constructing a map of the AI solution space
  • Data modalities and labeled versus unlabeled data
  • Predictive, generative, and agentic AI
  • Degrees of automation in AI
  • Types of AI user interfaces

It’s easy to get lost in the space of AI solutions. New AI models and tools are launched daily, and anyone who has ventured into serious technical discovery for AI knows that many of these tools fall short of their marketing promises. Unfortunately, many product teams only realize this after investing significant time and resources. In addition, given that the current hype mainly turns around generative AI, they tend to forget about other forms of AI—such as more traditional predictive algorithms. These challenges can slow down your solution discovery and put you at a disadvantage to competitors who choose more appropriate and efficient AI tools and methods. They can also affect communication with stakeholders—for example, your engineers might not take you as seriously if they think you’re not “getting” what AI is about.

3.1 Data

3.1.1 The modality of your data

3.1.2 Unlabeled vs. labeled data

3.2 Different types of intelligence

3.2.1 Rule-based AI

3.3 User experience

3.3.1 Basic types of AI interfaces

3.3.2 Assisted, augmented, and autonomous intelligence

Summary