What is Artificial Intelligence (AI)?

Artificial intelligence (AI) is an interdisciplinary field of computer science that deals with the development of machines and software that mimic human-like cognitive abilities. This includes processes such as learning, problem-solving, logical thinking, decision-making, and language processing. A central component of AI is machine learning (ML), in which algorithms recognise patterns from large amounts of data and independently develop solutions without being explicitly programmed. Particularly advanced forms of AI use deep learning, which is based on artificial neural networks and is capable of analysing complex contexts. According to Fraunhofer IKS, AI can be used, especially in safety-critical areas, to detect risks at an early stage and optimize processes.

How to use AI?

1. Automation of routine tasks

   AI can take over simple, repetitive tasks, thereby saving time and increasing efficiency. In companies, for example, it is used to process large amounts of data, provide automated customer support (chatbots) or automatically process invoices. Especially in industry, AI ensures the optimization of production processes and quality assurance.

2. Personalised customer approach

   Companies are using AI to provide personalized recommendations to customers. By analyzing buying behavior and preferences, they can create tailored advertising or product recommendations. Online retailers like Amazon or streaming services like Netflix are using AI to generate personalized suggestions.

3. Medical diagnostics and research

   AI is playing an increasingly important role in medicine, especially in diagnostics. It is used to evaluate X-ray images, MRI scans or blood tests, and helps doctors detect diseases early. In addition, AI supports the development of new drugs by analyzing large amounts of biomedical data and identifying potential drugs.

4. Autonomous driving

   Autonomous vehicles are based on AI technologies that can recognize road signs, obstacles and other vehicles. Sensors and algorithms help make driving decisions that contribute to road safety. Companies like Tesla and Google are developing vehicles that can drive largely autonomously.

5. Fraud detection and cybersecurity

   Financial companies and banks are using AI algorithms to detect fraudulent transactions. AI can identify unusual patterns in payments and thus prevent fraud. AI also plays a major role in cybersecurity by detecting and fending off potential attacks early.

Goods of AI

1. Efficiency and productivity gains

   AI can automate work processes and analyze large amounts of data faster than humans. This allows companies to optimize their processes and work more productively. Especially in the industrial sector, AI leads to higher production efficiency and lower operating costs.

2. Error reduction and higher precision

   Human error is a common cause of problems in many industries. AI can help minimize errors, especially in complex calculations or precise tasks such as medical diagnostics or manufacturing control.

3. 24/7 availability and constant performance

   AI systems can work around the clock, without breaks or fatigue. As a result, they improve customer satisfaction in areas such as customer service (e.g. chatbots) or monitoring machines and systems in industry.

Bads of AI

1. High implementation costs

   The development and implementation of AI systems is expensive. Companies need to invest heavily in research, development, and infrastructure. Especially for small and medium-sized enterprises (SMEs), the adoption of AI can be a major financial hurdle.

2. Job losses due to automation

   Many traditional occupations could be replaced by AI, particularly in manufacturing, logistics or accounting. Studies show that AI could displace some jobs in the long term, bringing with it social and economic challenges.

3. Data protection and security risks

   AI is based on the analysis of large amounts of data, which often comes with the collection and processing of sensitive personal data. This creates risks of data abuse, identity theft and unauthorized access. Compliance with data protection regulations such as DSGVO is a major challenge.