Generative AI - examples of applications in everyday working life

Generative AI increases performance and customer satisfaction through more efficient and automated processes.

‍

Examples of AI applications in sales:

• Preparation of optimal offers for specific customer inquiries or processing of tenders.
• Data-based qualification and prioritization of leads.
• Deriving and predicting customer behavior, e.g. for measures in the area of cross- or up-sales.

Generative AI can lead to an improvement in service quality, e.g. shorter response times and higher availability.

‍

Examples of AI applications in support:

• Increased availability of customer support, e.g. through a 24/7 approach.
• Individual customer support, based on existing data and experience.
• Simple scaling or processing of a large number of requests at peak times.

Generative AI boosts productivity and increases employee satisfaction by taking over routine tasks.

‍

Examples of AI applications in HR:

• Automation of repetitive tasks, e.g. the formulation of job advertisements.
• Individual onboarding of new employees by providing customized training content.
• Automatic evaluation and summary of internal surveys.

The use of generative AI can significantly increase efficiency and productivity in the processing of standard tasks.

‍

Examples of AI applications in the legal sector:

• Automatic checking of contracts or other documents according to specific criteria.
• Filling in documents or forms with existing data or information.
• Comparison of content in documents, e.g. for contract amendments.

Generative AI makes the acquisition and provision of knowledge much more efficient, e.g. through automatic knowledge extraction and organization.

‍

Examples of AI applications in knowledge management:

• Analysis of unstructured data and conversion of relevant information into structured formats.
• Dynamic updating of knowledge through continuous integration of new information.
• Provision of personalized knowledge for effective knowledge transfer.

The use of generative AI increases operational efficiency through optimized processes, both at departmental and cross-departmental level.

‍

Examples of AI applications in process management:

• Automated process modeling and visualization.
• Creation of process models based on information from process descriptions.
• Automatic creation of documentation for processes or individual process steps.

Generative AI can be used to improve innovation processes and develop new solutions that humans might miss out on.

‍

Examples of AI applications in R&D:

• Accelerated innovation through automatic evaluation of large volumes of data.
• Creation of problem analyses with the help of existing reports.
• Resource efficiency through the automatic creation of documentation.

By supporting generative AI, marketing performance can be increased, e.g. through automated content and creative processes.

‍

Examples of AI applications in marketing:

• Creation of content and media, such as product descriptions or videos.
• Personalization and individualization of interaction with customers for a better customer experience.
• Automatic provision of product suggestions, based on data and customer behavior.

Increasing operational efficiency and optimizing supply chains demand forecasting or reducing waste.

‍

Examples of AI applications in production and logistics:

• Optimization of production planning and control, e.g. with AI agents.
• Quality assurance and error detection with the help of image processing.
• Optimization of supply chains, e.g. by analyzing suppliers and disruptions that occur.