Normalized claim
Time: 11 hours decrease
Anticipated time savings of up to 11 hours per week per lawyer with AI-enabled research tools.
Last evidence check: Jun 1, 2026
Clayton Utz, one of Australia's largest law firms, has implemented a comprehensive suite of legal automation tools using Microsoft Azure OpenAI Service, RelativityOne, and Lexis+AI. The firm automates tasks including research, document drafting, contract review, regulatory reporting, and litigation strategy support. Specialized tools such as an ESG content extraction tool, developed in partnership with Microsoft Azure OpenAI Service, and the AcCUrate compliance auditing solution have streamlined case law review and employment law compliance auditing respectively. Through the integration of generative AI, the firm has achieved significant efficiency gains in producing first drafts, conducting research, and automating document collation for government projects. Proprietary safeguards have been implemented to ensure client data confidentiality and document accuracy. These innovations allow Clayton Utz's lawyers to spend less time on manual tasks and deliver improved outcomes to clients, while continuing to evaluate and advance AI capabilities across legal domains.
Reported outcomes
11 hours
timeTime & speed
Strategic outcomes
Normalized claim
Time: 11 hours decrease
Anticipated time savings of up to 11 hours per week per lawyer with AI-enabled research tools.
Last evidence check: Jun 1, 2026
Deployed Microsoft Azure OpenAI Service to build an ESG tool for extracting and structuring insights from climate change case law
Primary read
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The system utilizes multiple AI components: Microsoft Azure OpenAI Service powers an ESG tool extracting and summarizing extensive legal case law; RelativityOne automates document collation and review for infrastructure projects; Lexis+AI and Lexis+ are used for research and automated drafting, providing generative AI-driven support; the AcCUrate tool analyzes payroll and compliance data using AI. All these tools are monitored and managed by an internal AI working group to ensure data confidentiality and accuracy.
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Measures whether this deployment's public evidence persists — not whether the system is still in production.
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