Finding the Right AI Workflows for Contract Management—Webinar

While artificial intelligence promises unprecedented speed in contract management, relying on unguided prompts often creates more operational friction than value.

In a recent webinar with Today’s General Counsel, LawVu’s Senior Product Manager Maarten Truyans and Customer Experience Lead Sene Mennes discussed how in-house teams can effectively integrate AI into their contract drafting and reviewing workflows. The session, “Drafting and Reviewing Contracts with AI: What Works, Where It Breaks, and How to Use It Effectively,” outlined why relying on AI to freewheel large tasks creates operational bottlenecks and how legal teams can ground AI in institutional context to achieve reliable, high-value outcomes.

Mennes highlighted the core limitation of applying broad AI prompts to complex legal work:

“Generative AI is a Swiss Army knife. It can do a whole lot of different things, but when it comes time to nail a hammer into a wall, you need to still rely on a hammer,” he said.

Key takeaways from the session:

• Distinguish between full drafting and document automation: Generating full contracts from scratch using general AI prompts introduces unpredictability, structural errors, and inconsistent terminology. For creating standardized contracts at scale, legacy document automation tools (smart templates with interactive questionnaires) remain far more reliable, while AI is best reserved for supplementary drafting tasks.
• Mitigate risks by redlining provision-by-provision: Expecting AI to redline an entire long-form contract in one pass leads to the “lost in the middle” phenomenon—where accuracy drops significantly in central clauses—and risks over-editing in ways that damage counterparty negotiations. Lawyers achieve far better results by executing redlines provision-by-provision to keep human judgment in control.
• Enforce “closed reviewing” with institutional playbooks: Open-ended reviews asking AI to find “what’s wrong” yield vague, inconsistent responses due to lack of business context. Legal departments should instead utilize “closed reviewing”—feeding AI explicit rules, hard stops, and standard playbook terms so it can evaluate third-party contracts against specific corporate standards.
• Solve formatting bottlenecks with embedded tools: Exporting AI-generated clauses into external documents frequently corrupts Word styling, headers, and numbering. Deploying dedicated legal add-ins directly inside Microsoft Word ensures that AI-generated language immediately adapts to document styling and context.

Balancing legal precision with rapid execution requires choosing the right technology for the right task. Watch the full recording to learn how your team can implement structured AI workflows while avoiding common technological pitfalls.