AI finds structure and regularities in data so that the algorithm acquires a skill: the algorithm becomes a classifier or a predictor. So, just as the algorithm can teach itself how to play chess, it can teach itself what product to recommend next online. And the models adapt when given new data. Back propagation is an AI technique that allows the model to adjust, through training and added data, when the first answer is not quite right.
When algorithms are self-learning, the data itself can become intellectual property. The answers are in the data; you just have to apply AI to get them out. Since the role of the data is now more important than ever before, it can create a competitive advantage. If you have the best data in a competitive industry, even if everyone is applying similar techniques, the best data will win.
In most cases, AI will not be sold as an individual application. Rather, products you already use will be improved with AI capabilities. Automation, bots and smart machines can be combined with large amounts of data to improve many technologies in the workplace, from security intelligence to investment analysis.