Bloomberg Reports AI Is Forcing Big Law to Rethink Business Model as Kirkland Hints at Fine-Tuning Open-Source LLMs for Proprietary Legal AI

A Bloomberg feature published today examines how artificial intelligence (AI) is forcing major law firms to fundamentally rethink their business models, from billing structures to staffing ratios and technology investment. Separately, Kirkland & Ellis — which committed $500 million to build a proprietary AI platform — has signalled through its hiring activity that its project may involve fine-tuning open-source LLMs (large language models, the technology underlying tools like ChatGPT) on its own legal data, rather than simply licensing existing commercial platforms. Two newly posted AI Infrastructure Director roles at Kirkland require experience with 'on-premise GPU environments' — specialist computing hardware used to train and adapt AI models locally rather than via the cloud — indicating the firm may be building a model tailored to its specific practice needs. Kirkland's job adverts also reference familiarity with existing legal AI tools including Harvey, Legora, CoCounsel, and Lexis+ AI, suggesting the firm is using commercial platforms as a benchmark while building a proprietary alternative. The Bloomberg piece frames this as part of a broader industry reckoning: as AI absorbs more routine legal work, firms are being forced to decide whether to buy, build, or partner on AI infrastructure — a choice with significant implications for firm economics and junior lawyer pipelines.