LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A
  Survey
Ashok Urlana Charaka Vinayak Kumar Ajeet Kumar Singh Bala Mallikarjunarao Garlapati Srinivasa Rao Chalamala Rahul Mishra
Large language models (LLMs) have become the secret ingredient driving
numerous industrial applications, showcasing their remarkable versatility
across a diverse spectrum of tasks. From natural language processing and
sentiment analysis to content generation and personalized recommendations,
their unparalleled adaptability has facilitated widespread adoption across
industries. This transformative shift driven by LLMs underscores the need to
explore the underlying associated challenges and avenues for enhancement in
their utilization. In this paper, our objective is to unravel and evaluate the
obstacles and opportunities inherent in leveraging LLMs within an industrial
context. To this end, we conduct a survey involving a group of industry
practitioners, develop four research questions derived from the insights
gathered, and examine 68 industry papers to address these questions and derive
meaningful conclusions.