The article also highlights the potential of large language models (LLMs) in KOL discovery. LLMs can provide additional insights beyond just a list of names, such as areas of shared interest and connections between employees. However, the author notes that for AI to be effective in KOL discovery, it must be built on structured and machine-ready data. Once a robust foundational data infrastructure is in place, organizations can use AI to augment their internal headhunting efforts.
Key takeaways:
- Advances in artificial intelligence (AI) and machine learning (ML) can accelerate key opinion leader (KOL) identification in organizations by structuring data for easier search and retrieval.
- Techniques like ontologies, text analytics and mining, document annotation, and semantic search can be used to create a machine-readable and interoperable dataset for efficient internal headhunting.
- Generative AI capabilities, such as large language models (LLMs), can provide additional insights during a KOL search, such as areas of shared interest and overlap, and reveal previously unknown connections between employees and experts.
- AI and LLMs can significantly enhance KOL discovery, but they must be built on structured and machine-ready data. Once a robust foundational data infrastructure is in place, organizations can use AI to augment their headhunting process.