How Companies Can Use LLM-Powered Search to Create Value – HBR.org Daily

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by Ege Gurdeniz, Ilana Golbin Blumenfeld and Jacob T. Wilson
Soon, searching through links may be replaced by conversational interfaces that will allow users to refine queries and deepen their understanding through follow-up questions — and audio, video, and images are all part of this new search and retrieval paradigm. Consider how those powerful capabilities might translate across your business: chat-based tools that allow employees to easily query policy documents, conduct quick Q&As with the organization’s latest sales data, or have meaningful conversations with all manner of institutional knowledge. To implement this technology effectively, organizations should consider following several steps: 1) clearly define use cases, 2) establish intake processes that consider risk as well as value, 3) invest in practices surrounding data collection, testing and validation so you have effective ground truth, 4) incorporate standardized testing practices, 5) establish monitoring capabilities, and 6) roll out training, awareness, and communication campaigns.
As large language models (LLM) continue to advance at a dizzying pace, many business leaders are still grappling with how to put this technology to work. On one hand, they’re looking for areas where these generative AI tools can quickly prove their value. On the other, they want to lay a foundation for broader-scale and long-term transformation.
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