A great debate seems to be rearing its head–is it better to conduct document review with traditional machine learning or with generative AI? This article examines traditional machine learning and generative AI in the context of review for production in litigation matters. While each party seeks to improve efficiency and defensibility, they differ meaningfully in workflow, transparency, human involvement, and overall impact on legal practice.
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Most firms are aiming their newest tools at the work they already do — pouring their most powerful technology into running the same tasks a little faster. But when everyone automates the same tasks at once, no one pulls ahead. That reaches the future a little faster while leaving a firm’s largest opportunity untouched — and that opportunity isn’t doing more of the existing work, but transforming how the high-value work gets done.
AI is becoming both an accelerant and a distraction for cybersecurity. In many respects, AI is acting as a stress test for existing security operations by exposing how difficult many organizations still find it to enforce basic controls consistently at scale.
Artificial intelligence is rapidly embedding itself into legal workflows, but much of the conversation treats all use cases as if they carry the same level of risk, even if they do not. The more useful question is not whether AI works, but where it can be safely applied and where it cannot.
AI-savvy lawyering is already something that clients are starting to demand. The technology is capable; the challenge now is cultural and organizational change.
