Nearly 40% of Enterprises Surveyed by expert.ai Are Planning to Build Customized Enterprise Language Models

Successful adoption of enterprise language models will need to overcome significant challenges to effectively, responsibly and securely train them.

BOSTON, May 11, 2023 /PRNewswire/ -- At a time when the hype surrounding Open AI's ChatGPT has prompted 45% of executives to increase their investments in artificial intelligence (AI)*, the new expert.ai research Large Language Models: Opportunity, Risk, and a Path Forward reveals that more than one-third of enterprises (37.1%) are already planning to train and customize language models to meet their business needs.

A significant majority of enterprises (78.5%) realize that the efforts required to effectively train a usable and accurate enterprise-specific language model is a significant undertaking which will require dedicated resources and budget. Almost three-quarters of enterprises surveyed have budget or are discussing adding budget to support large language model (LLM) adoption.

"Enterprise specific language models with a human-centered approach are part of the future," says Marco Varone, founder and CTO of expert.ai. "Business natural language use cases always require some degree of domain-specific training applied to existing proprietary or open-source LLMs. Specific enterprise models can be smaller, more efficient, faster and less resource-hungry while still maintaining high performance. Having subject-matter experts monitoring and refining data and inputs throughout the process ensures accuracy, transparency and accountability."  

The study shows that while only a few surveyed favor a LLM training moratorium (21.2%), the majority of AI professionals and practitioners (70.6%) point to the need for commercial and malicious use in AI regulations. Top adoption challenges include: data privacy and security (73.1%), accuracy and quality for production model deployment (51.2%) and knowledgeable resources on how to build and train LLMs (40.7%).

For companies that are prioritizing AI transparency and responsibility, generative AI and LLMs may bring real risks for their ESG objectives and performance, with truthfulness (69.8%), bias (67.3%) and leaks of proprietary data (62.6%) as the top concerns.

Regardless of the direction an organization chooses, basic AI data governance principles still apply to generative AI and LLMs. While 24.0% of survey respondents indicate that further restrictions need to be put in place to test LLMs and provide clear communication of applied policies, 38.8% feel some additional degree of freedom should be encouraged, and 34.3% cite that current principles are adequate.

Download the expert.ai's e-book Large Language Models: Opportunity, Risk, and a Path Forward.

* Gartner Poll Finds 45% of Executives Say ChatGPT Has Prompted an Increase in AI Investment – May 3, 2023, link

About the survey study

The expert.ai "Large Language Models: Opportunity, Risk, and a Path Forward" report summarizes survey results from 300+ business, technical and academic natural language AI experts from around the world. The interviews were conducted online by expert.ai in April 2023 with the goal to explore potential opportunities and risks associated with generative AI and provide recommendations for a path forward that enterprises can use in their development and deployment of LLMs.

About expert.ai

Expert.ai (EXAI:IM) is a leading company in AI-based natural language software. Organizations in insurance, banking and finance, publishing, media and defense all rely on expert.ai to turn language into data, analyze and understand complex documents, accelerate intelligent process automation and improve decision making. Expert.ai's purpose-built natural language platform pairs simple and powerful tools with a proven hybrid AI approach that combines symbolic and machine learning to solve real-world problems and enhance business operations at speed and scale. With offices in Europe and North America, expert.ai serves global businesses such as AXA XL, Zurich Insurance Group, Generali, The Associated Press, Bloomberg INDG, BNP Paribas, Rabobank, Gannett and EBSCO. For more information, visit https://www.expert.ai

SOURCE expert.ai