Breaking the ‘Bottleneck’: How Legal Teams Use AI-Ready Playbooks to Drive Business Impact

In-house legal teams are no strangers to pressure—short turnaround times, long queues of contracts, and limited resources are the norm. The traditional approach to contract review, while familiar, is wearing thin.

According to a recent survey by LegalOn and In-House Connect, legal teams spend an average of 3.2 hours per contract. Multiply that across hundreds of contracts per quarter, and it’s easy to see how teams get buried. What’s harder to see is how much value gets left on the table—strategic initiatives delayed, product work sidelined, cross-functional partnerships put on hold.

The good news? A better path is emerging. In a recent webinar featuring Luis Tovar (FloQast), Bari A. Williams (LegalOn), and Daniel Lewis (LegalOn), the panel made a clear case for how AI-powered playbooks can unlock speed, structure, and scale for in-house legal teams.

Why Traditional Playbooks Fall Short

Legal teams have long used playbooks to ensure consistency in contract negotiations, but traditional formats—often Word or Google Docs—are static, inconsistent, and difficult to maintain. Each attorney may interpret clauses or fallback positions differently. And in fast-paced deal cycles, there's rarely time to consult and cross-reference manual guides.

The result? Inconsistencies, slower turnaround times, and a higher risk of missing key terms. This issue is magnified when SLAs demand same-day or 24-hour turnarounds.

To address this, many legal teams are turning to generative AI. But AI alone isn’t enough. The real power lies in pairing AI with structured, enforceable playbooks—playbooks that go beyond static PDFs or Excel sheets and become dynamic guidance systems.

Turning Internal Standards into Scalable Systems

The next evolution of contract review isn’t just about automating tasks—it’s about operationalizing your legal team’s standards. Instead of keeping fallback language, preferred terms, and negotiation boundaries locked away in docs or institutional memory, leading teams are encoding those preferences directly into the tools they use.

By cascading internal standards on AI tools, legal teams can create a consistent, scalable way to apply judgment at speed. This turns playbooks from passive references into active participants in the review process—highlighting deviations, suggesting edits, and helping ensure that every contract reflects your organization’s risk tolerance and priorities.

This is exactly what the team at FloQast has done with LegalOn. By layering their company-specific rules alongside LegalOn’s attorney-drafted built-in playbooks, they’ve created a powerful framework that reduces review time while enhancing alignment, precision, and legal confidence across the board.

The Payoff: Speed, Consistency, and Strategic Capacity

The shift to AI-ready playbooks is already demonstrating measurable impact for the legal team at FloQast.

“NDAs that used to take 1.5 to 2 hours now take 15 to 30 minutes,” said Luis Tovar, Senior Legal Operations Manager at FloQast. 

“Procurement contracts? We’ve saved 1 to 2 hours minimum.” Multiply that across hundreds of contracts per quarter, and the time savings are substantial.

But the true value isn’t just in time saved—it’s in what that time enables.

Tovar shared that with contract review becoming faster and more automated, attorneys now have the breathing room to focus on higher-value work: product counsel, expansion planning, and cross-functional collaboration. These are the initiatives that often get postponed due to bandwidth constraints—but with AI handling first-pass review, legal teams can finally lean into strategic contributions.

It has also greatly improved and increased consistency and knowledge sharing. Manual review often depends on who’s holding the pen. One attorney might flag a clause that another misses. AI-ready playbooks bring structure and repeatability to the process. When the AI is trained on clearly defined rules, every contract is reviewed against the same standard, —whether it’s being handled by a tenured GC or a newly onboarded counsel.

That standardization also enables better onboarding. New team members don’t have to learn everything from scratch—they can lean on playbooks that encode institutional knowledge, fallback positions, and risk tolerances.

Finally, the structure of AI-powered playbooks surfaces previously hidden risks like clauses that deviate subtly from the norm or get buried deep in third-party paper. Rather than relying on gut instinct and late-night clause comparisons, legal teams can trust the system to flag what matters and explain why.

In short, the payoff is threefold:

• Speed: faster review cycles and quicker deal velocity
• Consistency: fewer misses, clearer standards, smoother handoffs
• Strategic capacity: more time for the work that moves the business forward

Watch the full on-demand webinar for insights, examples, and best practices.

Getting Started: A Practical Playbook

If your team is just getting started, Bari Williams suggests beginning with your most common agreements—NDAs, MSAs, vendor contracts—and focusing on what she calls “the Great 8” clauses:

• Limitation of liability
• Indemnification
• Confidentiality
• IP/ownership
• Warranties
• Data security
• Payment terms
• Termination (including transition clauses)

From there, teams can layer business-specific guidance on top of prebuilt playbooks from tools like LegalOn—customizing alerts, fallback positions, and redlines to reflect their own standards and risk appetite.

A New Operating Model for Legal

Ultimately, this isn’t just a better way to review contracts. It’s a new model for how legal teams work. One that’s faster, more consistent, and more strategic.

As Daniel Lewis put it, “Imagine what your legal team could do with a few more hours back every week. AI lets you redesign how your time is spent.”

Curious about LegalOn’s playbook library and how to tailor it for your team? Learn more about LegalOn Playbooks and how you can get started today.