OpenAI recently introduced GDPval which evaluates how well AI performs on real-world, economically valuable tasks across 44 occupations, including legal. GDPval examines the work professionals do every day, from drafting legal briefs to analyzing compliance documents. Nick Whitehouse, Chief Artificial Intelligence Officer at Onit, explains the results and what this means for legal operations.
How GDPval Works
OpenAI designed GDPval by asking seasoned professionals to create 1,320 specialized, real-world tasks. Each task is based on real work that goes beyond a simple text prompt. These tasks come with reference files and context, and the expected deliverables come in the form of documents, slides, diagrams, and spreadsheets. The tasks were then completed by experts in the field and AI models. To evaluate performance, expert graders (a group of experienced professionals from the same occupation represented in the dataset) reviewed both outputs in blind comparisons. The results were scored on quality, accuracy, and usefulness, making GDPval a more realistic test than academic benchmarks because it reflects the actual deliverables professionals produce every day.
What the Results Said
Leading models are already producing work that approaches expert quality in certain tasks. In some cases, AI completed structured tasks up to 100 times faster than human experts. For the legal field, this means AI is proving its ability to draft, summarize, and analyze with surprising efficiency. But GDPval also underscores the limits. Real-world legal work requires judgment, iteration, and client nuance, qualities AI cannot replicate.
How to Utilize the Results
For legal teams, GDPval is a call to use AI as a force multiplier, not a replacement. Practical applications include:
- Accelerating contract review and summarization
- Enforcing billing guidelines more consistently
- Reducing hours spent on initial research
By shifting repetitive or structured work to AI, lawyers and legal ops professionals can focus on higher-value contributions like risk assessment, negotiation, and client strategy. The opportunity lies in designing workflows where human judgment and AI speed complement one another.
The Gist of It
AI is getting closer to expert-level performance on real-world legal tasks, but it is not a substitute for legal expertise. The advantage for legal and legal ops teams is: let AI handle the repetitive, structured work so people can spend more time on strategy, judgment, and client trust. The challenge is not whether AI is capable, but how quickly teams can adapt to use it wisely.
