Though artificial intelligence (AI) has been the technical buzzword in recent years, the field of AI is far from new: The first pioneer projects were already conceived back in the 1950s. But what developments have taken place to make almost every industry think about using AI? Let us have a look at the historical development of the technology to this day.

 Looking at artificial intelligence, one is quickly confronted with the question of ethics. This topic is also much discussed in recent media reports on artificial intelligence – the voices range from euphoric to anxious, from hopeful to warning. The questions posed in this context show that there are limits for AI and for the developers.

 An increasing number of companies want to use artificial intelligence to improve their internal processes across industries. At first glance, initiating and setting on track AI projects seems simple: Just implement some AI-based software, and the company will promptly start to benefit from the latest technology! In reality, however, it is not quite so easy. The preconditions for a truly successful implementation are thorough preparations, well-targeted realization, and permanent monitoring and testing. See the following seven tips for a successful start of an AI project:

Machine learning (ML) provides support not only for the service staff in the call center: Intelligent algorithms also make everyday work easier for the field service employees.

Companies with happy customers are more successful: Nowadays, a positive customer experience is as important as the quality or the price of a product. Customer service can greatly contribute to a good customer experience – and, supported by machine learning, it can make customers happy.

In the course of digitalization, the Internet of Things, Big Data and Industry 4.0, the amount of available data is growing constantly. But at the same time, it becomes more and more difficult to use these huge amounts without automation. Machine learning can support you here: Producing high-quality data analysis, it can help you make better decisions.