Application areas of AI

AI represents a new age

Artificial intelligence (AI) is shaping our everyday lives. For example, it is used for voice control of navigation systems, for face recognition to unlock smartphones and for recommending products during online shopping. AI is capable of recognizing and assessing complex traffic conditions in order to reduce the probability of collisions. In industry, AI is used to control production processes, guide the flow of goods and predict impending machine failures. AI is also helpful in medical diagnostics: For example, machine learning algorithms can detect tumours or strokes based on CT scans, or classify skin lesions.

AI has a nearly unlimited range of potential applications. Anywhere that large quantities of data are processed, AI can be used to great advantage. The technological implications of AI are truly revolutionary, representing a new age.

Application fields for AI


1. Dialogue processes – human to machine

Human-machine dialogues can be in written form or involve spoken language. Examples include voice control of a household appliance, voice guidance on a customer hotline, or interaction with a chatbot in an online shop. As part of the dialogue between humans and machines, the machine must adapt to the natural form of human communication.

2. Machine-to-machine processes

Internet 4.0 supports intelligent interconnection of machines and processes. For example, predictive maintenance allows proactive care of machines and systems in order to minimize downtimes. Machine-to-machine processes are also gaining ground in the private sector, e.g. in smart homes. Radiator thermostats, lamps, shutters, ventilation systems, loudspeakers and other infrastructure can be interconnected with smartphones and tablet PCs.

3. Intelligent automation

Intelligent automation can help to boost the quality of results and foster value creation in a process chain. For example, intelligent robot process automation allows automatic execution of repetitive, time-consuming or error-prone tasks by software robots. By making RPA bots more intelligent through the use of AI, it becomes possible to automate complex processes in an integrated and strategic manner with much better results.

4. Intelligence enhancement/intelligent decision support

Using data and AI algorithms, decision support systems in fields like medicine can suggest suitable preventive steps or therapeutic measures in order to assist doctors and patients with the decision-making process.

5. New application fields

Further development of AI techniques is accelerating – not least through combination of AI components. Thanks to increasing research activities, further application fields are being explored and new developments are rapidly applied to other areas of use.

Sector-specific applications of AI

Today, artificial intelligence is a key technology in the digital transformation with countless application fields. The AI applications commonly used in practice are based on techniques from weak AI. The examples below are intended to provide a brief overview of the different application areas.


Through digitalization of manufacturing and production processes, huge quantities of data are being generated that can be analysed and exploited with AI. Artificial intelligence is one of the key drivers behind the creation of added value in industry.

  • Optical inspections for quality management
  • Error or process analysis: improvement of process quality
  • Energy management: optimization of energy consumption
  • Predictive maintenance: forecasting of failure probabilities, etc.
  • Predictive analytics: forecasting of trends, periodic peaks, etc.
  • Intelligent electricity networks: forecasting of demand based on customer behaviour


AI has the potential to accelerate the digital transformation of management at all levels. AI can automate processes and improve the level of customer orientation as well as the service quality. Employees are relieved from handling routine tasks and can concentrate on their core duties.

  • Customer interface: speech robots and chatbots, analysis of customer correspondence, complaint management
  • Predictive distribution and planning of resources (e.g. staff planning)
  • Training: knowledge management systems
  • Smart cities: digital cities (e.g. electronic records, online portals)


For artificial intelligence, the huge volumes of data are an ideal source of training data. This includes three billion base pairs of the human genome, data sets from all health insurers worldwide, archives with billions of diagnostic images, and much more.

  • Tumour detection and classification
  • Development of drugs
  • Personalized medicine
  • Early detection of diseases (e.g. dementia)
  • Gene editing
  • Surgical robots

Nursing and rehabilitation

An ageing society in combination with the increased prevalence of chronic ailments is causing growing costs within our health system. Artificial intelligence can help to achieve better cost efficiency while compensating for the shortage of specialists in nursing and rehabilitation.

  • Nursing assistant robots
  • Speech recognition (e.g. aphasia, dementia)
  • Nursing documentation
  • Exoskeletons


In the area of E-commerce, AI techniques are being used to personalize the customer experience and accelerate purchasing processes. The result is increased customer satisfaction and loyalty at the same time as internal processes are automated and expenditures are reduced.

  • Product recommendations (e.g. Amazon, Netflix)
  • Chatbots and digital assistants
  • Personalized shopping experiences
  • Text analysis

Everyday technologies

AI is already indispensable in our everyday routines – even if in many cases we are not even aware of its use. For example, how many Internet users know they are helping to train an AI system when they solve an image captcha? Voice assistants, smart homes, music streaming – AI is making our lives more convenient and pleasant in many areas. Even our dishwashers can now save water and energy through the use of AI.

  • Autonomous driving
  • Face recognition on smartphones, etc.
  • Digital language assistants (e.g. Siri and Alexa)
  • Online search engines (e.g. Google)
  • Music streaming services

Integration of emotional intelligence

Artificial intelligence already serves as an impressive complement to the human intellect. In order to achieve more efficient and partner-like cooperation between humans and machines, the next AI evolution stage is now being readied. It involves integration of emotional and social intelligence into AI. Once equipped in this manner, machines will be able to understand the emotional state of their counterpart and respond appropriately. This would represent a key milestone in areas such as rehabilitation and nursing robotics as well as in the field of education.

Robots that can understand human emotions, anticipate human intentions and recognize human social expectations can make more accurate decisions at the right time. This would help to lift communication and cooperation between humans and machines to an entirely new level.