Artificial intelligence (AI) refers to systems or machines that mimic human intelligence when performing certain tasks. They are subject to a continuous learning and improvement process in which they analyze data and derive insights from it. (Kaplan, 2017)
The central sub-areas of AI include machine learning, natural language processing and robot-supported automation. At their core, AI systems are based on algorithms that process large amounts of data, recognize patterns and make predictions. The use of neural networks and deep learning methods enables these systems to overcome complex challenges – from facial recognition to understanding natural language.
Wide range of applications
The areas of application for AI are extremely diverse:
- Personalized marketing: AI algorithms analyze customer data to create individually tailored recommendations.
- Customer support: Chatbots provide quick and efficient answers to customer queries – 24/7.
- Automation in production: AI helps to optimize production processes and identify deviations. (Kreutzer, 2023)
AI is also showing its potential in the areas of market research and customer experience. Not only can it efficiently process and summarize large amounts of data or text, but it can also convert freely formulated queries into specific searches. This makes it possible to perform targeted analyses of existing data. (Maier, 2022)
Advantages and limitations
The integration of AI into data processing and analysis procedures results in significant time and cost savings. Spontaneous questions can be addressed directly to the AI without the need for specialized knowledge in statistical analysis. Nevertheless, the final assessment and evaluation of results remains a task for qualified experts.
An important aspect of using AI-based tools is ensuring data protection. Confidential data should not be fed into open AI models to avoid unwanted further processing.
We at TEMA-Q also focus on the step-by-step development of AI applications. While the initial focus was on automated translations and transcriptions, we are now working on AI-supported tools to efficiently summarize large volumes of original customer quotations. However, data security remains our top priority.
Take a look at our LinkedIn profile at https://www.linkedin.com/company/tema-q/ to gain exciting insights into the world of customer and employee experience in the future.
If you have any questions about these or other topics, or would like a live demo version of ClaralytiX via video conference, click here to make an appointment or contact us.
Kaplan, Künstliche Intelligenz: Eine Einführung, 2017
Kreutzer, Künstliche Intelligenz verstehen, 2023
Maier, Datenintegration vor Datenanalyse, 2022