How a comprehensive AI and LLM framework helps prepare companies

A thorough AI framework that evaluates readiness and addresses potential issues before investing can help organizations get on the right path. For example, some private equity firms are experimenting with LLMs to analyze market trends and patterns, manage documents and automate some functions. They are also considering how GenAI may impact their investing strategy. The following four-step analysis can assist an organization in deciding whether to build its own LLM or work with a partner to facilitate an LLM implementation.

1) Define the use case for adopting an LLM

There is a lot of hype around GenAI and all that it can do. Although it’s a powerful technology, it may not be suitable for addressing some problems and could be costly if deployed without defining the specific use case. Use cases related to lower-level customer support, content creation and document analysis tend to be best suited for GenAI experimentation.

2) Evaluate AI readiness

The next step is to assess the organization’s AI and machine learning (ML) readiness across three categories: AI capabilities, data and data practices, and analytics capabilities. If companies don’t take this step, there’s a risk of going in unprepared and not being able to successfully achieve the service’s goals.