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The Playbook for AI-Driven Legal Intake in 2025

Most in-house legal teams still triage requests in inboxes and chats. Here’s a practical, AI-powered intake and triage playbook that upgrades speed, control, and data—without adding headcount.

Jarryd Strydom

September 12, 2025
Hero image for article on AI-driven legal intake and triage
Hero image for article on AI-driven legal intake and triage
The Playbook for AI-Driven Legal Intake in 2025
In-house legal work starts at intake—but for many teams, more than half of requests still land as unstructured email or Slack messages. That creates response lag, unclear priorities, and invisible risk. In 2025, AI agents can convert that chaos into a controlled, data-rich flow without forcing the business to learn a new tool.
[6–7 min read] Audience: Legal Ops, GC, Procurement partners

The Hidden Cost Of Unstructured Intake

When intake lives in inboxes, you lose time and signal. Requests don’t include the right context, approvals get re-asked, and work disappears into one-off threads. Legal leaders can’t forecast demand, prove cycle-time improvements, or justify headcount because the data isn’t there.
Common symptoms:
  • Repeated questions to requesters for basics (counterparty, value, dates, data processing).
  • Ad hoc triage by whoever notices the email first.
  • SLA misses because priority and risk are unclear.
  • Fragmented knowledge—answers and positions trapped in threads, not playbooks.
The fix isn’t yet another form no one uses. It’s intake that meets the business where they already work, captures structured data, and routes requests using living playbooks.

What "Good" Looks Like: Controlled, Predictable Flow

A mature intake and triage layer does three jobs, consistently:
  • Captures the right fields the first time, tailored by request type (NDA, DPA, order form, vendor review).
  • Classifies and routes using rules you control (deal size, data sensitivity, jurisdiction, security posture).
  • Answers common questions instantly from approved playbooks and positions.
On Sandstone, this looks like AI agents sitting behind your Slack, email, or web form. They extract key terms, enrich requests (e.g., link the Salesforce opportunity, pull vendor security info), and auto-apply your approval matrix. Every interaction strengthens the knowledge layer—your playbooks evolve as decisions get made.
A Practical AI Intake Workflow You Can Pilot In 30 Days
Start small. Use a narrow, high-volume workflow to prove value and earn adoption. Here’s a concrete path:
  1. Define the request types and required fields
  • Pick 2–3 types (e.g., NDA, vendor DPA, marketing review).
  • For each, list must-have fields: counterparty, contract value, data categories, region, need-by date.
  1. Encode playbooks and positions
  • Add your fallback clauses, negotiation boundaries, and approval rules.
  • Map an approval matrix: deal value thresholds, data risk triggers, exec sign-offs.
  1. Connect to where work already happens
  • Enable Slack or Teams intake; keep email intake for external requesters.
  • Integrate Salesforce/Jira to auto-link context and reduce duplicate entry.
  1. Let AI handle triage—not judgment
  • Sandstone’s agents classify requests, check completeness, and nudge for missing info.
  • They propose routing and draft first responses from your playbooks; humans approve.
  1. Track the right KPIs from day one
  • Cycle time by request type and risk band.
  • First-touch-to-complete rate (no back-and-forth).
  • Auto-resolve rate (questions answered with no human).

Pro tip: Keep the pilot visible. Publish a simple SLA and a dashboard so stakeholders see the improvement.

Controls, Risk, And Change Management—Without The Drag
Legal’s concern isn’t automation—it’s control. AI intake should amplify your guardrails:
  • Human-in-the-loop for escalations and exceptions.
  • Versioned playbooks with review workflows; nothing ships unapproved.
  • Audit trails for every recommendation, edit, and decision.
  • Data residency and access controls aligned to your privacy posture.
Because Sandstone is the knowledge layer, changes to positions cascade instantly—no vendor tickets, no custom debt. You keep crafted precision while moving fast.
KPIs That Prove It’s Working
Choose measures that matter to Legal and the business:
  • 40–70% reduction in back-and-forth to "ready to work."
  • Intake completion rate: % of requests with all required data on first submission.
  • Auto-classification accuracy: AI vs. human override rate.
  • SLA attainment by risk tier—green means trust, not just speed.
  • Playbook reuse: how often positions answer questions without bespoke advice.
Publish a monthly summary to your stakeholders. When Sales sees cycle time drop and Marketing gets same-day guidance, adoption follows.

Actionable Next Step: Ship A Lightweight Intake Starter

This week, deploy a "good enough" intake starter for one use case:
  • Create a 6–8 field form for NDAs (counterparty, signatory, governing law, template vs. third-party, need-by date).
  • Connect Slack intake; turn on AI classification and missing-field prompts.
  • Load a one-page NDA playbook with fallback positions and approval rules.
  • Set a 24-hour SLA for first response; measure cycle time from first touch to signature.
Want a template? Get a 15-minute walkthrough and leave with a deployable NDA intake pack tailored to your approval matrix.

Close: Build The Bedrock For Speed And Trust

Intake is where legal work begins—and where trust is won or lost. With AI agents layered on top of your playbooks and approvals, Sandstone turns unstructured requests into a predictable, auditable pipeline. Every intake, triage, and decision compounds your institutional knowledge, so legal stops being a bottleneck and becomes the connective tissue of the business.
See how teams like yours implement AI intake in 30 days—and turn legal ops into a scalable foundation for growth.

About Jarryd Strydom

Jarryd Strydom is a contributor to the Sandstone blog.