Greenberg Traurig: Deploys CoCounsel Legal AI Firm-Wide

• Greenberg Traurig has deployed the next generation of Thomson Reuters CoCounsel Legal AI across all its offices, involving over 3,000 attorneys.
• This extensive Greenberg Traurig AI adoption follows years of beta testing and collaboration with Thomson Reuters, integrating trusted legal content and agentic intelligence.
• Thomson Reuters strategically developed its own legal AI model, Thomson 1.0, and rebuilt CoCounsel, emphasizing independence from larger foundational models.
• The platform features a 'human-in-the-loop' design, making lawyer involvement psychologically inviting throughout the workflow, rather than just at the end.
• CoCounsel Legal adheres to a 'Fiduciary-Grade AI™' standard, prioritizing transparency and accountability, and anticipates a shift towards legal AI consumption pricing in the industry.

The platform features a 'human-in-the-loop' design, making lawyer involvement psychologically inviting throughout the workflow, rather than just at the end.

Greenberg Traurig has embarked on a significant technological advancement, deploying the next generation of Thomson Reuters CoCounsel Legal AI across its vast network of offices. This widespread Greenberg Traurig AI adoption encompasses the firm's more than 3,000 attorneys, who practice in highly diverse legal environments ranging from New York to Tallahassee and Riyadh.

This extensive rollout follows years of collaborative effort, during which Greenberg Traurig lawyers actively participated in beta testing the project. Their feedback and insights were instrumental in helping Thomson Reuters refine and develop the platform, ensuring its suitability for a global legal practice. The new CoCounsel Legal system is designed to transform legal insights into actionable outcomes, integrating trusted legal content, advanced agentic intelligence, and streamlined workflow execution within a unified experience.

Central to this deployment is the platform's adherence to a Fiduciary-Grade AI™ standard, emphasizing transparency and accountability in its operations. This commitment reflects a strategic approach to law firm AI integration strategy, ensuring that the technology supports, rather than replaces, the critical judgment of legal professionals. The firm's deep engagement in the development process underscores a deliberate and thoughtful approach to integrating artificial intelligence into its core operations.

The deployment of Thomson Reuters CoCounsel Legal AI is underpinned by a strategic decision made by Thomson Reuters, as highlighted by CEO Steve Hasker at ILTACON last August. Hasker revealed the company's move to acquire a team of expert scientists dedicated to building a more focused and manageable legal AI model. This approach stood out amidst a prevailing industry trend where many firms and vendors were primarily emphasizing their integrations with large foundational models from companies like OpenAI and Anthropic.

Hasker's vision was to cultivate a degree of independence in AI development, foreseeing the potential benefits of a proprietary backstop should foundational models encounter unforeseen challenges or limitations. This strategy aligns with a broader concept of developing more economical AI models that deliver substantial productivity gains while maintaining factual accuracy, a notion previously described as an 'American DeepSeek.' Following this strategic investment, Thomson Reuters has since launched Thomson 1.0, the result of this expert team's work, and has concurrently rebuilt its CoCounsel platform from the ground up, setting the stage for its advanced capabilities.

A critical differentiator of the new CoCounsel Legal platform, particularly as implemented by Greenberg Traurig, is its innovative approach to human-in-the-loop legal AI. Unlike some industry trends that promote 'agentic' AI as an endless automation train, leaving lawyers to untangle complex outputs at the final stage, the Thomson Reuters workflow is specifically engineered to facilitate easy and frequent intervention by legal professionals throughout the process.

Matthew Beekhuizen of Greenberg Traurig noted that the CoCounsel interface is designed to be 'psychologically inviting of lawyer involvement,' ensuring that human oversight is not an afterthought but an integral part of the workflow. This design philosophy addresses concerns that merely auditing a lengthy log of agent actions at the end of a process, while technically 'auditable,' is not a realistic or effective form of human-in-the-loop engagement. Instead, the system prioritizes direct lawyer engagement, reinforcing the platform's Fiduciary-Grade AI™ standard by embedding transparency and accountability at every step.

The widespread adoption of advanced legal AI, exemplified by Greenberg Traurig's deployment, signals a significant shift in the legal technology landscape, echoing themes discussed at recent industry conferences. A key theme at ILTACON centered on the idea of various platforms coexisting and meeting lawyers where they are, a departure from previous years' focus on a 'single-pane' world where one provider might control a lawyer's entire digital workday. This new competitive environment emphasizes access to crucial context across multiple platforms.

Looking ahead, the legal industry is bracing for what some term the 'Tokengeddon,' a projected shift in AI pricing models. As AI tools become more efficient, reducing the time required for certain tasks, the traditional billable hour faces increasing pressure. Consequently, the AI universe is expected to transition from flat fees to legal AI consumption pricing out of necessity. This impending change will require law firms to develop strategies for leveraging AI to perform actionable work in a cost-effective manner, making efficient integration and transparent pricing models paramount for future success.

This development signals a significant law firm's commitment to integrating AI with a focus on human oversight and accountability through 'human-in-the-loop' and 'Fiduciary-Grade AI' standards. Lawyers and compliance officers should analyze this approach as a benchmark for responsible AI adoption, considering its implications for ethical practice, data integrity, and potential shifts in billing models due to consumption-based AI pricing.

Source: Original reporting via Above the Law