Unlocking the business potential of large language models : real-world applications and obstacles
Year: 2023
Type: article
Abstract: OpenAI’s AI chatbot ChatGPT has already gained over 100 million users within the first two months of its release. This makes this internet service the fastest growing of its kind. In comparison, the runner-up, Tiktok, took a full nine months to reach a similar number of users. The potential of the underlying technology, LLMs, is undisputedly recognized by business leaders. According to a study by Gartner among business executives [1], 45% of respondents have already intensified their investment in artificial intelligence (AI) as a result of the success of ChatGPT. LLMs are extremely large-scale artificial neural networks that are trained with terabytes of textual content to complete texts. LLMs can therefore generate new content and thus belong to the class of generative AI solutions. In contrast, discriminatory AI models can only establish assignments or classifications between different inputs and predefined outputs. LLMs can be used for a variety of purposes, such as text summaries, sentiment analysis, or named entity recognition. Although there are already initial indications of the productivity gains that can be achieved through the use of LLMs, the role of this technology for the business models of industrial companies is still largely unclear. In the following, we present the findings derived from own prototypes and a comprehensive analysis of more than 50 real-world use cases pertaining to the application of LLMs within various companies. A distinction can be made between four mechanisms of how business models are changed with LLMs: - new customer benefits - new sales and communication channels - increased business process automation - improved use of information resources.
Authors: Wulf, Jochen, Meierhofer, Jürg
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7053049157