The Secrets of AI Value Creation

3Four Types of AI Value Creation

What all of us have to do is to make sure we are using AI in a way that is for the benefit of humanity, not to the detriment of humanity.

—Tim Cook (CEO of Apple)

Although the three‐factor approach presented in Chapter 2 can help to create clarity about the value creation potential of use cases, it lacks insight on where to find areas of AI application with high potential business value. Various perspectives have been used to classify areas of AI application in the past. From a technical perspective, AI can be seen in the form of chatbots and natural language processing, computer vision and image recognition, pattern recognition, and robotics. However, neural networks, random forests, and gradient boosting machines are some of the algorithms that have been used to create value analytically. From a business perspective, AI's use cases can range from network optimisation in the telecommunications sector to drug discovery and diagnostics in health care, to budget optimisation for media departments to lead generation for sales teams.

We have identified four distinct ways in which AI can create value: process optimisation, decision‐making augmentation, decision‐making automation, and AI products and services. By mastering these AI value creation types, businesses can develop a road map for sustainable value creation. Each type of AI value creation presents unique opportunities and also carries its own feasibility and adoption risks. It is critical ...