AI and Generative AI (GenAI) are revolutionizing the business landscape. AI analyzes historical data to forecast outcomes, while GenAI utilizes advanced deep-learning models to create novel content from the data and prompts it's trained with. The evolution of computer science enhances our capability to interpret data and make informed decisions, especially as computer integration deepens and data pools expand. This emphasizes the importance of thoughtfully incorporating GenAI solutions into life sciences businesses, underlining the crucial need for a validation-centric approach for this industry.

 How can we validate GenAI solutions? 

• A good understanding of the business process and intended use of the AI model is critical for validation 
• Most AI models are validated using the traditional validation approach, i.e., best practices in development or engineering and maintenance 
• Data management is where it starts to diverge