RESEARCH REPORT

The State of Enterprise LLM Preparedness & Adoption

We surveyed over 500 senior tech professionals about the status of their GenAI projects, which models and inference providers they're using and considering, their top deployment challenges, and how they expect LLMs to impact their business.  This report provides a comprehensive overview of LLM adoption in the enterprise and why AI projects get stuck in experimentation.
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The Revolutionary Power of LLMs is Undeniable

Not only are organizations now incorporating strategies to leverage AI to drive efficiency and productivity by automating time-consuming workflows, but AI-driven data analysis, along with communication, collaboration, and personalization tools are also starting to transform business operations across all sectors.

However, while LLM adoption is gaining momentum, most enterprises are still in the early experimental stages of integrating these into business solutions, laying the foundations for bona-fide LLM use in the coming years.

As they explore this groundbreaking technology, tech teams are beginning to understand that relying on just one AI tool will not afford them the true benefits of integrating LLMs with their business applications.

In other words, the time for single model generative AI experimentation is over, and organizations must prepare themselves for a world in which managing multiple AI models and inference providers is the norm.

Highlights from the survey

FINE-TUNING

90%
of respondents

 

say fine-tuned LLMs would bring value to their organization

MULTIPLE MODELS

94%
of respondents

 

expect to run more than one model in the next two years

MULTIPLE INFERENCE PROVIDERS

67%
of respondents

 

say they will have more than one inference provider

PREPAREDNESS

70%
of respondents

 

are not prepared to run LLM projects for enterprise solutions

WHAT'S INSIDE

Read this report to understand:

  • The difference between very prepared tech teams and unprepared tech teams when it comes to initiating LLM projects

  • Why AI projects get stuck in experimentation

  • Which foundational models are of interest or being tested by senior tech professionals

  • Why enterprise tech teams expect to run more than one model and inference provider

  • Priority use cases and business areas that are expected to be augmented with LLMs

This report reveals who is most prepared to fully integrate LLMs into their business applications and what they are doing to ensure success as they test and deploy multiple models and providers.

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