Please enjoy this blog authored by Christine Livingston, Managing Director and Global Leader of Artificial Intelligence practice, Protiviti and Joel Wuesthoff, Managing Director, Protiviti.
Artificial intelligence (AI) is leaving its mark on every industry, and the legal sector is no exception. The rapid expansion and adoption of AI has created unique opportunities and challenges for legal professionals, demanding swift adaptation from litigators to maintain their effectiveness.
Like so many businesses contemplating AI, law firms and their litigators are asking crucial questions like:
• What constitutes “AI,” and what does it mean for our business?
• How can we determine the best use cases for applying it?
• How can we have confidence in the solutions we identify and their outputs?
• How do we stay abreast of the rapidly changing environment, both from a legal and regulatory standpoint, and from developments in the technology itself?
The legal industry's embrace of AI is not without precedent. The field saw a major transformation more than a decade ago, when eDiscovery, augmented by predictive coding and machine learning, brought advanced analytics into the courtroom. These technologies paved the way for today's AI breakthroughs, changing the emphasis from cost control to strategic gains. This reflects a larger industrial trend: AI is used not only to improve efficiency but also to stand out from the competition.
How the litigator’s role and toolkit is changing
Litigators facing complex cases with mountains of data to interpret and synthesize are finding AI incredibly timely and useful. AI can process both structured and unstructured data, making it actionable and understandable for human interpretation. This transformation is one of AI's primary value propositions, enabling legal teams to leverage data more effectively.
In addition, AI has improved knowledge capture and distribution among legal teams. It is accelerating the learning curve of less experienced attorneys by giving them access to valuable insights that seasoned professionals bring to the table. This democratization of information ensures consistency and enhances the overall effectiveness of legal services. Additionally, the traditional law-firm model, heavily reliant on junior associates to handle routine legal tasks, is being disrupted. AI technology is increasingly performing many of these tasks, prompting firms to rethink how they allocate resources and structure their workforce.
Traditional billing structures in the legal profession are also changing. As AI tools streamline processes and reduce the need for extensive billable hours, some law firms are looking to adjust their fee structures to remain competitive. Some general counsels predict [or anticipate] lower legal fees because of AI adoption by law firms. This shift mirrors trends observed in other professional services industries.
Impact on Cases
On the operational side, law firms are integrating various AI tools to enhance their operations.
Here are a few legal-work AI use cases:
- Chatbots and automated tasks, powered by AI, enhance case management and client interactions.
By analyzing past cases and settlement data, AI improves case assessments and forecasts potential outcomes.
AI-powered fraud detection helps law firms attract clients and reduce risks by identifying fraudulent claims.
Automating billing and document analysis with AI reduces errors and ensures accurate invoicing.
Here are a few legal-work AI use cases:
The need for legal teams to understand AI's role in meeting business demands and adapting traditional models is more crucial than ever.
Impact on regulatory and judicial processes
Recently, headlines were flooded with news about a murder victim who came back to speak in a courtroom in Arizona, delivering a statement about the impact of the crime, thanks to AI-driven cloning technology.
The appearance of a cloned-murder victim in court marked a rare yet significant introduction of AI technology into the legal system. But it's only an escalation of an increasing trend of legal professionals using AI technologies, like ChatGPT, to create case citations.
Many fear this is a harbinger of things to come, and litigators must be ready. Regulators undoubtedly have reservations regarding AI's role in legal matters. A federal judges' panel recently put forward a plan to control how AI-created evidence is presented in court.
The panel advanced a draft rule designed to ensure that evidence produced by generative AI technology meets the same reliability standards as evidence from human expert witnesses. This proposal subjects AI and machine-generated trial evidence lacking expert witness support to Rule 702 of the Federal Rules of Evidence—the same reliability standards applied to expert testimony. The significance of upholding rigorous standards for AI applications in law is emphasized by this decision.
The panel also wants legal teams to disclose AI's role in decision-making processes and maintain transparency to uphold ethical standards.
Looking ahead: Litigators should focus on strategic implementation
Driven by AI, the legal industry is undergoing a transformation comparable to an industrial revolution. The numerous opportunities the technology presents also come with challenges that require careful navigation. Legal professionals must focus on strategic integration, while ensuring AI's ethical and effective deployment in their work.
What does strategic integration mean? It requires establishing a responsible AI framework aligned with organizational values and industry standards. This framework should also guide firms’ AI vendor selection and implementation strategies, ensuring that AI tools are effectively integrated into legal operations.
Additionally, law firms and litigators should embrace the concept of “AI for All” by making generative AI capabilities accessible to their employees at scale, for general-purpose interactions (similar to those possible with publicly available tools such as ChatGPT, Gemini, and Claude) but built on a secured backend that protects communications and prioritizes data privacy and security.
There’s also a need for litigators to transform and diversify AI tools in their expanding toolkit quickly. Legal teams are advised to experiment with various models, recognizing that different models excel at different tasks.
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