Focusing AI Workflows on the People, Not the Technology

Artificial intelligence (AI) workflows are all about the people, not the technology, writes Sam Bock for Relativity. Legal AI adoption often falters not because the technology falls short, but because organizations fail to integrate it into people’s everyday work. 

The foundation of an effective AI workflow is defining the problem before selecting a solution. Rather than encouraging broad, undefined experimentation, legal teams should identify specific, repetitive tasks where AI can deliver measurable value. Clear objectives help eliminate uncertainty, while carefully crafted questions improve the quality of AI outputs. Strong search logic and precise prompts are necessary for reliable results. After identifying suitable use cases, legal teams should begin with a limited proof of concept. Starting small allows teams to validate AI against known outcomes, compare results with existing human work, and demonstrate measurable performance. This evidence-based approach builds trust, reduces skepticism, and reinforces AI as a tool that supports, rather than replaces, human judgment. As confidence grows through demonstrated success, the legal department can expand adoption with greater credibility.

Bock asserts that training, change management, and ongoing communication are essential elements of successful implementation. Developing internal champions of this workflow encourages meaningful engagement, while practical training and real-world examples help employees understand how AI can improve daily work. Continuous learning is supported by maintaining collaborative relationships with providers as AI continues to evolve. 

The greatest long-term value comes from applying AI where repetitive work and inconsistent decision making create inefficiencies. This allows legal teams to increase capacity for high-value, human-centered work while remaining adaptable to technology advances, supporting the concept that AI workflows are all about the people.