In the wake of the ChatGPT and the large language model
("LLM") boom, most companies are focused
on deploying generative AI tools within their enterprises. However,
after going through a due diligence process and procuring a
specific generative AI product(s) for internal use, companies often
find that that the AI product does not yield a viable return on
investment ("ROI") as the AI product is
not aligned to the enterprise's use case. In this article, we
explore both generative and extractive AI and the benefits which
can be harnessed through the use of extractive AI.
Generative AI
The main application behind generative AI products is the
generation of content based on a user prompt or set of
instructions. Generative AI is efficient at generating content and
tailoring such content to the user's query or instruction.
However, generative AI systems are prone to hallucinations and data
biases, which can lead to incorrect or inaccurate outputs. Some of
the use cases
