Fulfilling the Promise of Generative AI 12 Balancing In-house Models With Third-party Models Organizations can approach supporting generative AI initiatives using large language models (LLMs) from different angles, whether that be leveraging third-party proprietary models, utilizing open source models as a starting point, or developing a net-new in-house proprietary model. And Enterprise Strategy Group research highlights that there is still a fair bit of uncertainty with which approach is best. While there is plenty of opportunity for third-party vendors and service providers in the GenAI market to provide proprietary pretrained models, it is clear that many organizations will rely on open source models to some extent. In fact, nearly one-third of organizations (30%) have plans to utilize an open source LLM as a starting point to develop their own GenAI solution in-house.9 This represents a set of organizations that might want more control, have their own data, and/or have in-house expertise. In addition, nearly 1 in 4 organizations (23%) plan to go the open source route but anticipate working with a third-party provider to help move development forward, while more than 1 in 4 (28%) will look to a third-party provider that offers access to a proprietary model via prompt or API.¹0 Figure 5. Approaches Organizations Are Actively Taking in Their Pursuit of GenAI 30% 28% 23% 9% 30+70+T 28+72+T 23+77+T 9+91+T We will utilize an open source We will work with a third- We will work with a third-party We will develop a net-new LLM and develop a generative party provider that offers provider that offers access to LLM entirely in house. AI solution in house. access to a proprietary an open source LLM and allows model via prompt and/or us flexibility to customize. API. © 2024 TechTarget, Inc. All Rights Reserved. 9Source: Enterprise Strategy Group Research Report, Beyond the GenAI Hype: Real-World Investments, Use Cases, and Concerns, August 2023. Back to contents 10Ibid.