AI in Life Science: From Traditional to Generative AI in Life Science: From Traditional to Generative

AI in Life Science: From Traditional to Generative

About this Content

Uncover the transformative potential of AI in Life Sciences! The new capabilities of AI responding to language prompts and creating different kinds of content not only add new use cases but make the technology accessible to more users than ever, drastically lowering use barriers for non-tech professionals. At the same time, application of AI in Life Science has never been straightforward due to privacy and regulation concerns, data availability and challenges in stakeholder buy-in. The risks connected to patients’ well-being, healthcare professional trust and confidence, and impact on core product pipeline are always the top concerns in the industry.

This report covers 96 high-level AI use cases applicable in Life Science, grouped by topic and place in the value chain. There is often more than one single way to implement a use case, that is why in this report we refrained from diving them into generative and traditional. We also looked at the potential impact and feasibility of the topics, barriers and trends that are present for AI in the industry. While for every organisation the impact of AI may look different, we hope that this overview will provide some inspirational bring more clarity to how AI can transform Life Science.

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Every outcome starts with a conversation