Not everything needs an LLM: A framework for evaluating when AI makes sense

Question: What product should use machine learning (ML)?
Project manager answer: Yes.

Jokes aside, the advent of generative AI has upended our understanding of what use cases lend themselves best to ML. Historically, we have always leveraged ML for repeatable, predictive patterns in customer experiences, but now, it’s possible to leverage a form of ML even without an entire training dataset.

Nonetheless, the answer to the question “What customer needs requires an AI solution?” still isn’t always “yes.” Large language models (LLMs) can still be prohibitively expensive for some, and as with all ML models, LLMs are not always accurate. There will always be use cases where leveraging an ML implementation is not the right path forward. How do we as AI project managers evaluate our customers’ needs for AI implementation?

The key considerations to help make this decision include:

1. The inputs and outputs required to fulfill your ...