Extract from Onna’s article “What is Retrieval-Augmented Generation (and why should every legal professional know about it)?”
Generative AI (GenAI) has quickly emerged as a top investment priority for many companies, a trend underscored by the recent EY Reimagining Industry Futures Study. This study showed that 43% of the 1,405 enterprises surveyed are investing in GenAI technology. Another study from Infosys estimates a 67% increase in company investments in GenAI over the next year. However, while excitement about GenAI remains high, so does the uncertainty surrounding it.
A global study by MIT Technology Review Insights revealed that as many as 77% of participants see regulation, compliance, and data privacy as significant hurdles to the swift adoption of GenAI. Legal teams investing in GenAI face additional challenges, such as a lack of specialized knowledge, mistrust, and fear of producing “hallucinations” — inaccurate or misleading information.
However, the outlook for GenAI is not all doom and gloom.
A viable strategy for overcoming these obstacles is to augment Large Language Models (LLMs) with unique, proprietary data. This approach not only improves the accuracy, relevance, and overall integrity of the outputs but also mitigates many concerns related to regulation, compliance, and privacy.
