  Large Language Models (LLMs) as chatbots have drawn remarkable attention
thanks to their versatile capability in natural language processing as well as
in a wide range of tasks. While there has been great enthusiasm towards
adopting such foundational model-based artificial intelligence tools in all
sectors possible, the capabilities and limitations of such LLMs in improving
the operation of the electric energy sector need to be explored, and this
article identifies fruitful directions in this regard. Key future research
directions include data collection systems for fine-tuning LLMs, embedding
power system-specific tools in the LLMs, and retrieval augmented generation
(RAG)-based knowledge pool to improve the quality of LLM responses and LLMs in
safety-critical use cases.
