3.5 General AI vs Legal AI

Do "purpose-built" Legal AI Assistants outperform general-purpose ones?

Our findings suggest that while general-purpose tools can match legal AI tools in raw accuracy, purpose-built legal AI assistants often deliver more value where it matters most: in usability and workflow integration.

Their advantage lies not just in what they generate but in how well they support the way legal teams actually work.

General-purpose AI tools can match or exceed legal AI tools in the accuracy of the generated text.

General-purpose LLM chatbots like ChatGPT and DeepSeek performed just as well as the legal AI Assistants on the accuracy of the Info Extraction Tasks. NotebookLM, a productivity AI Assistant not specifically optimized for legal use, achieved the highest accuracy score overall.

Legal AI tools offer stronger usability features for legal workflows.

Legal AI Assistants like GC AI and Oliver stood out by offering source-linked answers, multi-document support, and structured outputs tailored for legal review, features that streamline in-house workflows beyond just providing an accurate text output.

Notably, GC AI delivered the answers with the most appropriate length and the overall most helpful answers out of all the AI Assistants, and when all 3 Usefulness Factors were considered together, the 2 legal AI assistants (GC AI and Oliver) scored the highest and outperformed the general LLM applications.

As accuracy gaps narrow, usability and integration will drive the next wave of legal AI adoption.

While current differences in accuracy between AI Assistants are still visible, these gaps are likely to close quickly as vendors adopt more advanced and powerful LLMs. As accuracy becomes a baseline, the real differentiators will shift to usability, workflow integration, and support. Features like an intuitive interface, integration with email or document systems, strong data security, and responsive support will increasingly define which tools deliver real value to legal teams.

In-house legal teams evaluating AI tools should look beyond model accuracy performance today and focus on which platforms will streamline legal work and scale with their needs tomorrow.