AI Adoption Is Not a Technology Problem. It’s an Operational Problem | Association of Certified E-Discovery Specialists (ACEDS)
https://www.jdsupra.com/legalnews/ai-adoption-is-not-a-technology-problem-9394209/
Publish Date: 2026-05-29 16:46:00
Source Domain: www.jdsupra.com
The firms that get lasting value from AI won’t necessarily be the ones that moved first, they’ll be the ones that built the operational foundation to use it consistently.
The Pattern Behind AI Adoption Challenges
Over the past several years, the legal industry has experienced a rapid increase in interest surrounding artificial intelligence. Law firms are evaluating vendors, investing in platforms, and exploring ways to integrate AI into legal work. Conversations often focus on features, model performance, and demonstrations of what the technology can do. The excitement is understandable because many of these tools produce impressive results when placed in controlled environments with well-structured, high-quality data. The promise is compelling: faster drafting, deeper analysis, more efficient research, and lower operating costs.
After spending almost three decades working at the intersection of legal services and technology — across large firms, mid-size practices, and legal services organizations — I have seen similar waves of enthusiasm before. New technologies always arrive with the promise of transforming legal work. Electronic discovery platforms, knowledge management systems, collaboration tools, and analytics solutions all generated significant excitement upon their introduction. Each offered meaningful value, and many eventually delivered on that promise. However, almost all encountered the same obstacle after the initial excitement faded.
The challenge was rarely the technology itself. It was the environment into which the technology was introduced. Technology can improve a process, but it generally does not create one. When organizations lack structure, clear ownership, and repeatable methods of execution, new technology often amplifies those weaknesses rather than solving them. Much of what firms are experiencing with AI today is simply a new version of a familiar problem.
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