Hardly any other technology has as much potential as that artificial intelligence. Intelligent, learning machines – from chatbots in customer service to product recommendations in online shops to cancer detection in MRT – bring massive innovations. They increase companies’ competitiveness and innovative strength in digital markets and will conquer more and more areas of application in the future. In combination with human expertise, AI becomes a decisive market advantage.
While some companies are seizing the opportunities that artificial intelligence offers them and using this technology to improve their business processes, others are missing out on this enormous value creation potential. But where exactly does this potential lie?
Table of Contents
AI Creates Added Value.
- New, improved analysis: Machine vision allows machines to simulate how the human brain processes information in a fraction of a second. If, for example, components in industrial plants are broken, AI can detect this at an early stage before a costly failure occurs.
- Optimized pattern recognition Allows the evaluation of very, very large data sets.
- Precise forecasts for the future: Predictive analytics, i.e. forecasts based on data, are a challenge on the one hand but are of immense interest for companies that want to become market leaders.
- Natural Language Processing: Describes the interaction of intelligent machines with human language. This clever technology behind chatbots has made progress in recent years due to the development of deep learning.
- Speech recognition: AI understands spoken language and converts it into written text. With natural language understanding and intent analysis to determine what someone wants, speech recognition is the driving force behind Alexa, Siri and Co. But it can also be used for therapeutic purposes.
AI Predicts The Future.
Artificial intelligence can make predictions: They use machine vision and learning to calculate the probabilities of an event occurring based on what they have learned from the past and the associated data. This strategy is used in marketing to make forecasts about customer decisions. For example, AI identifies patterns in user behaviour and increases the relevance of certain ads for certain users accordingly. On Netflix, Amazon Prime and Co., they create personalized series suggestions and thus give customer recommendations. This strategy can also help small companies to recommend customized services or products. On the other hand, if companies want to automate repetitive tasks, machine learning is used in various ways.
However, because AI uses computer vision to recognize, understand and classify images and videos in seconds, it is also used in financial monitoring and network security. AI identifies suspicious behaviour by examining data patterns, which is how they catch scammers.
Predictive maintenance, in turn, is an application area of machine learning derived from predictive analytics. While predictive analytics describes a forward-looking analysis method based on data and statistics that develops, tests and applies prediction models, predictive maintenance already describes the next step. This form of application gives recommendations on how to react to an occurring event. They are used in particular in industry.
With the help of predictive maintenance, the condition of a technical device or component can be transparently displayed and analyzed using the data from numerous built-in sensors. In this way, even the most minor deviating data can be recognized as a sign of an error, which can be addressed preventively. Preventive maintenance of worn parts and failure-sensitive machines makes it possible to predict whether and when preventative maintenance is required – before a time-consuming and costly failure occurs—using artificial intelligence benefits you from enormous future-oriented and competitive potential.