Cleared up: the most common AI misconceptions
(Video)

In this article you will read about,

• which are the most common misconceptions about the use of artificial intelligence,
• why pre-trained applications make it easier to get started,
• and when the technology starts to pay off.

The solution to all problems or just one technical solution among many? Business-enhancing investment or overly complex and without a real return on investment (ROI)? Artificial intelligence is polarizing. There are as many opinions as there are use cases. While the technology is being used by more and more companies, some doubts persist. For example, in the 2019 VDE Tec Report survey of 105 member companies, 43 percent said data protection and regulatory hurdles prevented the introduction of AI. For 36 percent, there was a lack of business models; every third company (33.3 percent) has no budget for artificial intelligence. No wonder, since the necessary computing power and new infrastructure are expensive, and there is also a lack of skilled workers.

But is that true? Anyone considering introducing artificial intelligence in their company often encounters similar hurdles. But at the same time, the benefits cannot be dismissed out of hand. Higher productivity, more efficient processes, increased quality, and more satisfied customers are just a few of the major benefits named in a survey by Bitkom. And the market has long since responded to companies' concerns and the hurdles with new services and business models, such as public cloud resources, pre-trained AI models, and new services like data structuring. This makes it easier for companies to get started and increases the chance that even the first AI project will pay off. In subsequent projects, the ROI is usually even higher.

In the new video from the A.I.-Team, Torsten Deutsch explains why many of the inhibiting factors are long-outdated misconceptions and myths. And he shows how the right cooperation partner can help overcome them.