Tips, tricks, and strategies for smart AI communication
According to the Chemical Industry Association, the chemical and pharmaceutical industry invested 16.5 billion euros in research and development in 2025 — a record figure that shows how crucial innovation is for the future of the industry. At the same time, research teams are under increasing pressure. Data volumes are growing, regulatory requirements are increasing and the time until new drugs or materials are ready for the market is to become ever shorter. However, a large part of the existing knowledge is distributed in laboratory journals, reports or publications and often remains unused in everyday working life.
Artificial intelligence opens up new opportunities here. It can combine knowledge from various sources, support research processes and help teams make well-founded decisions more quickly.
Quick access to research knowledge
Learn how AI combines information from laboratory journals, reports and scientific publications and makes it accessible to research teams in a contextual manner.
Better decisions in the research process
Learn how AI recognizes relationships in data, supports hypotheses and helps teams plan experiments in a more targeted manner.
More efficient research through intelligent assistance
Discover how AI as a digital research partner supports scientists in research, experiment evaluation and knowledge management.
A pragmatic introduction to AI in R&D
Understand how companies successfully integrate AI into their research processes with clear use cases, pilot projects and a structured roadmap.
Most people currently use AI for simple queries. This is sufficient for many applications, but when it comes to more complex tasks, these approaches quickly reach their limits. At the same time, the use of AI in everyday working life is increasing significantly. This also increases the need to control results in a targeted manner and make them reproducible.
Effective prompting structures communication with AI in such a way that results are more precise, consistent and can be better integrated into existing work processes.
This white paper shows which principles are decisive and how they can be applied in practice.
Better results through clear prompts
Learn how to achieve significantly more relevant and immediately usable AI results using simple principles such as context, precision, and goal orientation.
Structure instead of trial and error
Understand how to use frameworks such as RACE to systematically build prompts and ensure consistent results for repetitive tasks.
More efficient content and analysis processes
Use proven prompt patterns for texts, reports, brainstorming and planning — and save time while maintaining higher quality.
Prompting for images and new AI tools
Discover how to specifically control image generators and create realistic visuals and mockups with precise prompts.
Getting started with AI agents and automation
Understand how entire workflows can be developed from individual prompts and how AI agents take on tasks independently.
Thursday 11th June from 18:00
Practical impulses & exchange on data and AI
