The emergence of Generative AI and Large Language Models (LLMs) is transforming how competitive intelligence is gathered, analyzed, and applied across industries. In pharmaceuticals—where regulation, data sensitivity, and scientific complexity are paramount—these technologies offer unprecedented opportunities and novel risks. This panel will explore how CI professionals can harness AI to gain actionable insights, maintain compliance, and stay ahead of market trends. Panelists will also discuss the strategic and operational implications of integrating these tools into CI workflows.
- How is GenAI currently being used in competitive intelligence within the pharmaceutical industry? What are currently observed benefits, and what are the limits of these solutions?
- What are the regulatory and compliance challenges when deploying GenAI in pharmaceutical CI processes?
- How can CI teams ensure data quality, bias mitigation, and transparency when using GenAI-generated insights?
- How to validate the results and differentiate reliable insights from AI hallucinations?
- What organizational changes are needed to effectively integrate GenAI tools into CI functions?
- How to organize and how to prepare the data for (any model of) AI?
- Where and with which data should different AI/ML-based tools be used ideally – internally, externally or in a hybrid way?
&nsbp;
