In the spring of 2017, a prediction was made by an AI expert that one day there would be a company with a market cap of one trillion dollars, based on the firm’s wide use of AI. That prediction was correct in some regards as Apple became the first trillion-dollar company just a year later.

Apple uses AI in a very extensive way. For example, according to what you listen to the most, Apple Music creates a playlist. The data from an Apple Watch is used by Apple Fitness+ to help them build health. Siri is able to give iPhone users reminders based on their location by combining speech recognition with expert systems.

Over the decades, the company has created and developed entirely new product arenas in many different fields, such as music sales (iTunes), cloud storage (iCloud), app subscriptions (the Appstore), as well as digital payments (Apple Pay).

There are many reasons for us to think that Apple’s innovations and success are based neither on data analysis nor on AI, but on creativity.  Creative leaders like Steve Jobs and Jony Ive have built an entirely new way to listen to music and that accomplishment wasn’t anyhow related to an algorithm. The idea of creating services like the Appstore and iTunes originated from the company’s commitment to entirely new and useful experiences for the consumers. That’s why it is not AI, but innovation, which raised the outcome of Apple.

These days, one of the most reliable AI technologies is the GPT-3 “few shot” learning model, which has developed the ability to generate synthetic new articles and computer code. Although its domain is mainly limited to natural language processing, it uses a model with 175 billion parameters.

Despite the fact that AI can be very useful, it can also cause damage. Companies have been facing the danger of an over-emphasis on AI and quantitative tools can potentially complicate breakthrough innovation, which usually occurs due to ideas sparkled by an insignificant conversation or an expected finding in a lab.

The bandwidth for business improvement of a firm can be consumed by the use of analytical tools. Trying to commercialize AI has put huge pressure on researchers whose job is to produce systems that work ‘well-enough on narrow tasks. Quantitative tools can even dominate a firm by keeping it focused on narrow tasks to the detriment of breakthrough innovation.

On the other hand, data tools are used to improve and develop already existing technological products. The use of AI in Apple adjoins software, hardware engineering and other business areas such as graphic design.

However, as much as AI is important for the development of technology, breakthrough innovation is of great importance as well. Companies, such as Amazon and Microsoft, have benefited from analytical capabilities, but their success is also influenced by human ingenuity.