AI Legal Post-Deployment: What Every Legal Team Must Do Next

AI is reshaping legal departments—but are you truly ready for what happens after implementation? Too often, legal teams focus only on pre-deployment checks, ignoring the high-stakes work required once the tools are live. AI legal post-deployment is where the most critical challenges begin, and your success depends on what happens next.

This blog draws from a recent workshop featuring legal tech leaders Olga Mack and Kassi Burns, who emphasized that post-deployment oversight is just as important as tool selection. In fact, this phase can determine whether your AI investment delivers value—or becomes a liability.

Watch the full conversation with Olga Mack & Kassi Burns here:

Deploying AI into legal workflows is just the beginning. Once in use, AI tools face unpredictable data, shifting legal contexts, and evolving compliance requirements. Without a post-deployment strategy, your team risks blind spots that can lead to misinformation, bias, or security breaches.

The workshop highlighted how legal teams often underestimate this phase. AI legal post-deployment must include governance structures, feedback loops, and continuous monitoring to ensure the tool’s output aligns with your department’s ethical and legal standards.

A major cause of AI failure post-deployment isn’t the technology—it’s human error. Users may misunderstand how the system works, overtrust its recommendations, or lack proper training. That’s why ongoing education and usage protocols are essential.

Olga Mack and Kassi Burns both emphasized that legal professionals must remain in the loop. Even with sophisticated AI, humans are the final gatekeepers of legal advice, risk management, and ethical boundaries.

AI systems evolve once deployed—and sometimes degrade. Regular performance checks, output validation, and quality reviews should be baked into your AI legal post-deployment plan. Set specific benchmarks for success and assign accountability for regular audits.

This validation process not only reduces risk but also allows legal departments to recalibrate AI use based on real-world feedback. Continuous performance review ensures that your tools stay effective, accurate, and compliant over time.

Not all legal AI tools are created equal. A document review assistant has different risks than a litigation research engine. That’s why a blanket policy won’t work. Each use case demands tailored protocols for ethical usage, data governance, and escalation procedures.

During the workshop, both experts agreed: responsible AI use begins with knowing the tool’s limitations. Tailoring your post-deployment policies to each function ensures legal integrity while allowing room for innovation.

Finally, successful AI legal post-deployment requires structure. Establishing a dedicated oversight team—whether full-time or as part of your existing operations—can help manage concerns before they become crises. This team can monitor tool performance, handle escalations, gather feedback, and serve as the bridge between legal, compliance, and technology.

Without this support, issues may go unnoticed or unresolved. With it, your AI tools can become a trusted extension of your legal team—agile, accountable, and aligned with your mission.

Watch the full conversation here:  Notes to My (Legal) Self: Season 6, Episode 15 (ft.Olga Mack & Kassi Burns)

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