1 Creating better products with AI

AI offers a huge potential both for the automation of repetitive tasks, but also for stupefying creativity. As in most innovation areas, some companies are quick to jump on the train: AI features such as chat, personalization, and tailored recommendations are becoming ubiquitous in software products.[1] On the other hand, the “laggards” - those companies who miss out on the relevant developments - most likely will stay behind as they watch their peers go from their first attempts in AI to more mature strategies, acquiring relevant AI expertise and building their moats along the journey. And then, there are a bunch of innovators and enthusiasts that try to use AI for the sake of AI, squeezing it into their products without validating the market opportunity and the actual value it provides to the users.

1.1 How AI can enhance your products

1.1.1 What is the role of AI in your product?

1.1.2 Vertical and horizontal use cases for AI

1.1.3 Examples of AI products

1.2 Starting your AI journey

1.2.1 Competing on data

1.2.2 Understanding your learning problem

1.2.3 Exclusion criteria

1.3 The mental model of an AI system

1.3.1 Opportunity

1.3.2 Value

1.3.3 Data

1.3.4 Intelligence

1.3.5 User experience

1.3.6 Non-functional requirements

1.4 Setting up your team for AI success

1.4.1 Team composition

1.4.2 Managing interfaces

1.5 The process

1.5.1 Identifying opportunities

1.5.2 Discovering solutions

1.5.3 Developing the feature

1.5.4 Launching to users

1.5.5 Operating and optimizing your AI

1.6 Summary