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Why Legal Teams Are Choosing AI Intake Over Legacy Ticketing in 2025

Email and portals are where cycle time goes to die. Here’s how AI-driven intake and triage shorten time-to-value, boost adoption, and turn CLM and workflows into a living system.

Jarryd Strydom

September 6, 2025
Legal ops leaders tell us 30–50% of cycle time disappears before real work begins—lost in intake, back-and-forth, and manual triage. That waste compounds across NDAs, vendor reviews, DPAs, and playbooked work. In 2025, teams aren’t accepting it. They’re replacing email queues and static portals with AI intake that asks for the right details up front, routes with context, and keeps institutional knowledge in play.

The Old Intake Loop: Email, Forms, and Rework

Most “intake” is still a shared inbox, a generic form, or a ticketing tool built for IT—not legal. It creates predictable friction:
  • Missing information and rework: requesters guess; legal follows up; clocks keep running.
  • Context loss: contracts arrive without commercial terms, data flows, or risk flags.
  • Brittle routing: static forms can’t reflect nuanced playbooks or exceptions.
  • Low adoption: business users bypass portals because they don’t help them get to “done.”
Bottom line: legacy ticketing treats legal as a black box. You don’t get faster; you just get a prettier queue.

What AI Intake Looks Like in Practice

AI intake doesn’t mean a chatbot pasted onto your inbox. Done right, it’s a thin, smart layer that speaks your policies and playbooks—and works where your business already works.
Here’s how it runs on a platform like Sandstone:
  • Capture anywhere: Slack, email, or a lightweight request page. No login hurdles.
  • Structured on arrival: AI extracts entities (counterparty, term, data types), classifies matter type, and maps to the right playbook or clause set.
  • Required info, not rework: If pricing, data flows, or security posture are missing, the agent asks targeted follow-ups.
  • Smart routing: Assigns by product, region, or risk profile; auto-invites procurement, security, or finance when rules trigger.
  • CLM-ready: Opens the right record in your CLM, drafts from the approved template, applies fallback positions based on the playbook.
  • Knowledge compounds: Every intake, Q&A, and decision enriches your knowledge layer so the next request is faster.
The result is less swivel-chair work for legal and clearer, faster paths for the business.
Metrics That Move in 30 Days
AI intake isn’t a multi-quarter transformation. Teams see early gains when they start with one high-volume workflow (often NDAs or vendor intake):
  • First-response time: From days to minutes with automatic acknowledgments and targeted follow-ups.
  • Cycle time: 25–40% reductions by eliminating rework loops and parallelizing approvals.
  • Rework rate: Fewer clarifying emails because the agent collects what your playbook actually needs.
  • Adoption: More business users stay in-channel when they get guidance, not a form.
  • Time-to-value: Go live in weeks, not months—no monolithic reimplementation.
  • Reporting you can use: Intake data becomes clean metrics—volume by business unit, request type, risk tier, blockers, and SLA performance.
These are the levers your GC and CFO care about: speed, predictability, and clear ROI on legal tooling.

Start Small: A 4‑Week Rollout Plan

You don’t need a big-bang CLM overhaul to get these wins. Stand up AI intake alongside what you have.
  • Week 1: Pick a use case and define “required to start.” Common picks: NDA, vendor + DPA, or low-risk sales order forms. Convert your playbook into decision rules.
  • Week 2: Connect systems. Hook into Slack/email, your CLM or document system, and matter management. Map fields so data flows cleanly.
  • Week 3: Configure the agent. Teach it your fallback positions, approval paths, and escalation criteria. Draft tailored follow-up prompts.
  • Week 4: Pilot with one business unit. Measure first-response, cycle time, and rework. Tighten prompts and routing. Then expand.
This modular approach respects how legal teams actually operate—and boosts adoption because it meets people where they work.

Actionable Next Step

Pick one workflow and script the “must-have” questions your team asks every time. Load those as required fields and AI follow-ups in intake. If requesters can’t answer, guide them to the right policy or data owner. Measure rework rate for two weeks; aim to cut it by 30% before expanding to a second workflow.

The Foundation for Trust and Growth

When intake becomes intelligent, legal stops being a bottleneck and starts acting like connective tissue across sales, procurement, security, and finance. Each request strengthens your operating system: layered data, modular workflows, and decisions that build on each other. That’s Sandstone’s philosophy—crafted precision that blends naturally into how you already work, turning institutional knowledge into action.
If you’ve outgrown legacy ticketing or can’t unlock value from a monolithic CLM, start with AI intake. It’s the fastest path to measurable speed, higher adoption, and a living legal foundation the business trusts—at scale.
Learn how teams are cutting cycle time with modular intake and playbook-driven automation.

About Jarryd Strydom

Jarryd Strydom is a contributor to the Sandstone blog.