Sandstone Logo

The 2025 Playbook for Faster Contract Reviews Without Adding Headcount

A practical, modular approach to cut contract cycle times by 30–50% using AI agents and a living knowledge layer—without ripping out your CLM.

Jarryd Strydom

September 14, 2025

Legal Ops Insights

The 2025 Playbook for Faster Contract Reviews Without Adding Headcount
Most in-house teams report rising demand with flat budgets—and contracts still make up the bulk of the work. The surprise? Up to half of contract cycle time is lost before review even starts: intake gaps, unclear risk positions, and manual routing. The fastest teams aren’t throwing people at the problem; they’re layering AI agents on top of a living knowledge base to move faster with less risk.
Sandstone’s take: legal should be the connective tissue, not a queue. Here’s how to turn playbooks, positions, and workflows into a compounding, AI-powered operating system for contract work.
The Real Bottleneck Isn’t Review—It’s the Front Door
Legacy play: open a ticket, attach a doc, wait for a human to triage. If anything’s missing, the ping-pong begins. Multiply that by NDAs, order forms, vendor MSAs, and SOWs, and cycle time balloons.
Modern play: front-load clarity. Use an intake that collects the right metadata (counterparty, contract type, deal value, data flows, governing law), auto-classifies risk, and routes based on playbooks—not gut feel. When your operating system captures business context at the start, review becomes execution, not archaeology.
This is where a knowledge layer matters. If your positions live in scattered docs, AI can’t act responsibly. If they’re codified—preferred clauses, fallback thresholds, approval triggers—agents can triage, draft, and escalate with precision.

Monolithic vs Modular: Layer Intelligence, Don’t Rip and Replace

You don’t need a six-month CLM overhaul to move the needle. A modular approach composes three thin layers:
  • Knowledge: your playbooks, clause library, and risk thresholds as structured, versioned data.
  • Workflow: intake, triage, and approvals encoded as simple, auditable steps.
  • AI agents: task-specific helpers that use your knowledge to act—summarize, redline, route, and checklist.
Sandstone is built for this: layered data and modular workflows that blend into how you already work. Keep your existing CLM for repository/signature if it’s working; layer AI where it creates immediate time-to-value.

Soft CTA: Get the checklist for codifying your top three playbooks. Read more.

A 30-Day Pilot: The Lean Contract Acceleration Loop

Start with your highest-volume type (NDAs, DPAs, or low-risk order forms). Prove value fast, expand later.
  1. Map the truth. Export your current positions: required, preferred, and acceptable fallbacks. Add trigger points (e.g., if data transfer crosses borders, require Privacy sign-off).
  2. Instrument intake. Deploy a smart form that collects deal context and attachments, then auto-tags risk level and contract type.
  3. Agent-assisted first pass. Have an AI agent generate a clean draft from your templates or produce a redline against your playbooks. Require confidence thresholds and show its rationale.
  4. Smart routing and approvals. Send low-risk items straight to business signers; push edge cases to Legal with a one-pager summary (key changes, flagged terms, missing approvals).
  5. Close the loop. On signature, log clause variants and exceptions back into the knowledge layer. Every decision improves the next one.
Worth it if: you need faster cycle times and better consistency without new headcount. Skip if: playbooks are nonexistent or leadership won’t adopt structured intake—fix those first.

Myth vs Fact: Will AI Redlines Let Risk Slip?

  • Myth: “AI is a black box that will accept risky terms.”
  • Fact: Agents are only as risky as your instructions. When they run on a governed knowledge base (roles, thresholds, clause rules) and produce traceable rationales, they reduce variance.
  • So what: Treat AI like a junior analyst with perfect recall. Give it crisp rules, monitor outputs, and let exceptions teach the system.
What good looks like:
  • 30–50% reduction in low-complexity contract cycle time within 60 days.
  • 80% of NDAs and order forms auto-routed without attorney touch.
  • Exception rate under 20% and trending down as knowledge compounds.
  • Approvals tracked to SLAs; zero “mystery stalls.”
Metrics That Matter (and How to Move Them)
  • Intake completeness rate: Percent of requests that require no follow-up. Drive it up with required fields and dynamic prompts.
  • Time-to-first-touch: Minutes from submission to triage decision. Agents should make this near-instant for standard work.
  • Auto-approval coverage: Share of contracts cleared by playbook without Legal review. Expand by clarifying fallbacks and thresholds.
  • Exception taxonomy: Top five reasons for escalation. Use it to refine playbooks and templates monthly.
Pro tip: instrument lightweight analytics from day one. If you can’t see the work, you can’t accelerate it.

Your Next Step

Pick one contract type and run the 30-day pilot. Codify the playbook, instrument intake, and enable agent-assisted drafting or redlining. Measure three metrics: intake completeness, time-to-first-touch, and auto-approval coverage. Iterate weekly.
Sandstone turns that loop into muscle memory: your playbooks become a living, AI-powered operating system; each intake, triage, and decision strengthens the foundation. That’s how legal scales without becoming a bottleneck—and how the business moves faster with clarity, alignment, and trust.

Hard CTA: See how it works.

About Jarryd Strydom

Jarryd Strydom is a contributor to the Sandstone blog.