BY ROBBIE PHILBRICK, RACHEL WILKA & MICHAEL CALLIER
Generative AI (GenAI) has emerged as a groundbreaking subset of artificial intelligence (AI) with the potential to revolutionize virtually every industry, including the legal field. GenAI is capable of creating new and original content, rather than simply processing or analyzing existing data. For legal teams, this presents both exciting opportunities and unique challenges that can vary depending on the type of user.
The landscape of AI users in the legal industry can be viewed through various lenses. One way to categorize users is into developers, content creators, and everyday users. Developers leverage AI to design and build technological solutions. Content creators, including lawyers and paralegals, use AI tools to generate legal documents like contracts, briefs, and memos. Everyday users interact with AI through common tools like email auto-complete, web searches, and voice command agents like Amazon’s Alexa.
This article represents the first in a series that will help legal teams of content creators better navigate their GenAI journeys. To get started, we clarify terminology, then share key factors to consider before implementing GenAI to help teams find and implement tools for their specific needs and use cases.
Key Terminology
Working effectively with GenAI requires legal professionals to understand and adopt new vocabulary. The following terms are critical on that learning journey:
Artificial Intelligence (AI): Computer systems that can perform tasks that typically require human intelligence, such as natural language processing (defined below), recognizing patterns, or making predictions.
Generative AI (GenAI): A type of AI specifically designed to create new content—such as text, images, audio, video, code, or other data types—using generative models based on patterns learned from existing data.
Foundation Models: An AI model trained on vast amounts of text data, capable of performing a wide range of natural language processing tasks including text generation, summarization, translation, and human-like question-answering (e.g., ChatGPT, Claude, Titan).
Machine Learning (ML): A type of system that learns and improves from experience by inferring patterns beyond explicit programming.
Natural Language Processing (NLP): A branch of AI focused on enabling computers to understand, interpret, and generate human language.
7 Key Considerations for Implementation
When considering GenAI implementation, legal teams should follow a structured decision-making process aligned with their organization’s strategic goals and operational realities. A few considerations to keep in mind when starting:
1. Objectives and Use Cases
- Specify what you expect AI to help with (e.g., contract drafting, legal research, due diligence).
- Set measurable goals for efficiency gains or cost savings.
- Prioritize use cases based on potential impact and feasibility.
As you define objectives, evaluate how the AI solution will integrate with existing platforms and workflows. Seamless integration is key to ensuring successful adoption and maximizing the technology’s benefits.
2. Your Team’s Needs and Readiness
- Identify pain points and inefficiencies in your current processes.
- Evaluate the complexity and volume of your legal work.
- Assess your team’s technical skills and openness to new technologies.
- Review your current technology infrastructure.
- Review your knowledge infrastructure to ensure available knowledge meets the desired use cases.
When assessing your team’s needs, consider the specific efficiencies an AI solution can provide, such as accelerating contract review or enhancing the depth of legal research. Also, evaluate what optimal processes for reviewing and validating AI-generated content would look like for your team.
3. Off-the-Shelf (OTS) or Custom Solutions
- Research existing GenAI solutions that cater specifically to legal teams.
- Assess your organization’s data availability and quality.
- If considering a custom solution, determine if your organization has adequate internal technical resources to build and maintain it.
When considering potential solutions, develop robust requirements to help base your decision on concrete metrics, such as number of users, price, and technical requirements. Ensure solutions meet your specific needs and scale to align with your long-term goals.
4. Resource Requirements
- Determine the budget available for AI implementation.
- Identify any necessary upgrades to your technical infrastructure.
- Plan for staff training and change management.
As part of resource assessment, determine specific training needs for your team to effectively use and manage the AI tools. Consider how to ensure both ongoing IT support and that users remain proficient with the evolving technology.
5. Applicable Risks and Risk Management Strategy
- Identify potential risks, including data privacy and ethical concerns.11 Mark Fucile, “The Chatbot Made Me Do It!” Washington State Bar News, November 2023, https://wabarnews.org/2023/11/16/the-chatbot-made-me-do-it/.
- Consider the scope of impact that could result from incomplete, inaccurate, or discriminatory model outputs.
- Create protocols for human oversight and quality control.
- Ensure compliance with relevant regulations and company policies.
6. Scalability and Future Needs
- Consider how the AI solution can grow with your legal department.
- Anticipate future use cases or expansion into new legal areas.
- Plan for ongoing evaluation and iteration of your AI implementation.
7. Key Indicators of Impact and Progress
- Time saved on routine tasks.
- Reduction in outside counsel spend.
- Increased capacity for high-value work.
- Improved accuracy in contract review or legal research.
- User satisfaction among your legal team.
Conclusion
GenAI represents a significant opportunity for legal teams to enhance their efficiency, accuracy, and strategic value to their organizations. By following a structured decision-making process, carefully considering the unique needs and constraints of your legal department, and proactively managing risks, you can harness the power of AI to transform your legal operations.
Successful AI implementation is an ongoing process. To increase the likelihood of success, stay informed about emerging trends in legal AI, continue to refine your use cases, and maintain open communication with your team about the role of AI in your work. By leveraging GenAI’s capabilities, your legal department can transform its operations, tackling complex challenges with greater speed and insight while freeing up valuable time for high-level strategic work to support your organization.
. . .
COMING SOON
The next article in this series will cover the importance of data in your GenAI journey and steps to leverage it for more accurate results when using GenAI tools.
About the authorS
Robbie Philbrick is an operations-driven attorney and project consultant specializing in digital transformation and strategic process implementation. At Epiq, he architects quality control systems and resolves complex class action registrant conflicts arising from a $5.5 billion antitrust settlement. He received his J.D. and Technology Entrepreneurship Certificate from the University of Washington.
Rachel Wilka is an experienced product attorney and chief of staff with a decade of experience advising companies on their strategy and use of emerging technologies. She received her J.D. from the University of Washington.
Michael Callier leads UHY Prime’s San Francisco office. He is a corporate lawyer, information scientist, and consultant with over 20 years of experience working in law firms, legal departments and ALSPs. He guides organizations and legal departments through complex change. Callier received his J.D. from the University of Oregon and M.S. in Information Management from the University of Washington. He is fluent in English and Mandarin Chinese.
NOTE
1. Mark Fucile, “The Chatbot Made Me Do It!” Washington State Bar News, November 2023, https://wabarnews.org/2023/11/16/the-chatbot-made-me-do-it/.