How Firms Can Transform AI Investments into Real Value

Legal industry professionals are increasingly focused on distinguishing genuinely useful applications of artificial intelligence from adoption undertaken merely to keep pace with competitors. Writing for Relativity, Sam Bock gathers lessons from eDiscovery experts, partners, and technical specialists on how legal teams can extract measurable value from AI tools while avoiding superficial implementation.

As generative AI use becomes more pervasive, Bock warns against treating technology adoption as a symbolic gesture. For institutions that rely on public trust, especially public sector organizations, change should be deliberate and built on a solid foundation rather than introduced for novelty’s sake. Thoughtful adoption requires evaluating a team’s skills, use cases, and risk appetites, acknowledging that generative AI is a specialized tool to complement existing workflows rather than a wholesale replacement for them.

Practitioners emphasize that meaningful AI capability is built through direct, iterative problem-solving rather than passive experimentation. Real understanding comes from wrestling with actual legal and data challenges. Industry experts highlight a wide variety of successful applications, ranging from automating technical coding tasks for data issues and querying document sets using natural language, to analyzing image files, flagging inconsistencies in testimony, and piloting agentic AI tools to assist investigative teams.

Throughout these applications, human oversight remains indispensable. High-quality outcomes depend on skilled prompting, sound legal judgment, and an understanding of how AI fits into broader workflows and legal defensibility. Because technological developments move rapidly, AI adoption cannot be treated as a one-off project. It demands ongoing attention to ethical duties like privacy, transparency, and fairness, alongside continuous learning through technical publications, industry communities, and knowledge-sharing.

Ultimately, firms build trust and adopt these tools effectively when they understand client concerns, address them thoughtfully, and clearly explain how AI trade-offs are managed.