Legal AI Pilot Plan Template for UK Law Firms: Phases, Roles, Controls, Success Metrics
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Legal AI Pilot Plan Template for UK Law Firms: Phases, Roles, Controls, Success Metrics

A legal AI pilot plan is a short, governed implementation process designed to prove measurable workflow impact and produce a clear scale decision, not just usage.

Most firms run pilots as a sprint. Some want shorter cycles, some want longer, depending on team size, risk posture, and which workflows they are testing. The calendar matters less than the process: controls first, real work second, measurement throughout, decision at the end.

If you want the measurement model this plan plugs into, see: Legal AI ROI for Contract Drafting

If you only remember one thing: a pilot succeeds when it produces a scale decision backed by evidence, not a collection of demos.

Two practical maxims:

  • A pilot is a decision, not a demo.
  • Controls first, then velocity.

Jump to the templates and checklists

What templates are included?

These copy-paste templates help you run a governed pilot and produce an evidence pack leadership can trust.

  • Pilot charter template (scope, exclusions, decision rules)
  • Roles and responsibilities table
  • Legal AI implementation checklist (controls pre-flight)
  • Success metrics scorecard (definitions included)
  • Weekly status report template (one-page)
  • Go, extend, stop decision grid
  • Pilot ROI tracker (aligned to the ROI model)

It is a structured test of real legal workflows under clear controls, with measurable outcomes and a decision at the end.

A pilot is not "let a few lawyers try it." A pilot is a controlled change program with three outputs:

Pilot output What it is Why it matters
Governance pack Controls, policy, training, monitoring, escalation path Prevents shadow AI and reduces risk
Measurement pack Baseline vs pilot metrics, with definitions Makes ROI defensible
Scale decision memo Go, extend, or stop, plus constraints and rollout plan Converts pilot into action

A pilot is a decision, not a demo.

What UK governance expectations should shape your pilot?

Run pilots with leadership oversight, documented controls, training, and monitoring, because professional responsibility and data protection obligations still apply.

Source-backed claims you can quote internally

  • According to the SRA, firms remain responsible for their services when using technology, and should have appropriate governance including policies, training, and monitoring. (See Sources.)
  • According to the ICO, organisations using AI should consider data protection requirements, and its AI and data protection guidance is a practical reference point for compliance work. (See Sources.)
  • According to the Law Society, generative AI introduces technology and data risks as tools and use cases evolve, and firms should approach adoption thoughtfully. (See Sources.)

Regulatory expectations vs practical recommendations

Category What it means How to treat it in your pilot
Regulatory expectation Your professional and legal obligations still apply Document oversight, supervision, and controls
Practical recommendation What improves adoption and reduces risk in day-to-day use Keep scope narrow, measure outcomes, iterate

Controls first, then velocity.

It should deliver controlled rollout, measurable workflow impact, and a clear recommendation to scale, extend, or stop.

A practical end-of-pilot checklist:

Deliverable Minimum viable version Strong version
Adoption evidence Weekly active users plus tasks completed Adoption by workflow and role
Outcome evidence One metric improved with sampling Draft time, rework time, sign-off time tracked
Governance evidence Policy plus escalation log exists Monitoring cadence plus investigation path validated
Scale plan Clear recommendation Rollout plan with constraints and training

Law firm AI adoption plan: what is the repeatable pilot process?

Use four phases: align, control, run real work, then decide.

This process works whether your sprint is shorter or longer. It also makes it easy to extend responsibly if the sample is small.

Phase Goal What "done" looks like
Align Decide scope and success metrics Pilot charter signed off
Control Put governance in place Policy, access, training, escalation path
Run Execute real work and capture evidence Steady weekly usage plus weekly reporting
Decide Produce evidence pack and scale decision Go, extend, or stop memo plus rollout constraints

Before meaningful use, define scope, allowed content, supervision rules, access, training, and how issues are investigated.

This is the part most pilots skip. It is also the part that makes pilots procurement-friendly.

Control area Decision you make Artifact you produce
Scope Which teams, matters, and doc types are included Pilot charter
Allowed content What is allowed, what is excluded Usage policy appendix
Supervision When outputs must be reviewed Supervision rules card
Access Who gets access, least privilege Access list
Retention and investigation What is logged, how to retrieve, who handles incidents Investigation path doc
Training Minimum training required Training record
Escalation What "stop and review" means, who decides fixes Escalation log template

Pilot charter template (copy/paste)

Field Your answer
Pilot objective
In-scope workflows
Out-of-scope workflows
In-scope teams
Contract type (if applicable)
Success metrics (top 3)
Governance owner
Supervision expectation
Decision rules Go, extend, stop criteria
Evidence pack owner

Who should be on the pilot team, and what are their roles?

A pilot succeeds when responsibilities are explicit, legal ops runs the program, and compliance and IT are engaged from the start.

Minimal team structure:

Role What they own Typical time
Partner sponsor or practice lead Business outcomes, scale decision 30–45 mins per week
Legal ops pilot lead Pilot management, metrics, reporting 2–4 hours per week
COLP or compliance lead Supervision expectations, policy review 1–2 hours per week
IT and security Access controls, monitoring, investigation path 1–2 hours per week
Knowledge / PSL / precedent lead Templates, standards, playbooks 1–2 hours per week
Finance or MI lead Rate choice, ROI framing, capacity reporting About 1 hour per week
Fee-earner champions (2–5) Real usage, feedback, adoption 10–20 mins per day

Track adoption, productivity, rework, sign-off speed, and governance signals, with definitions you can repeat next quarter.

If you only track "usage," you cannot prove impact. Track outcomes tied to supervision burden and sign-off confidence.

Metric Definition Direction How to capture
Weekly active users Users completing meaningful tasks weekly Up Usage analytics
Tasks per user Drafting, review, research tasks per user Up Usage analytics
Time to first reviewable draft Hours from intake to first draft sent for review Down Sampling plus timestamps
Material rewrite time Hours spent on substantive edits after review Down Tracked changes sampling
Sign-off cycle time Days from first draft to approval Down Tracker or CLM
Evidence coverage (if applicable) Percent of material edits verifiable via excerpts or sources Up Review sampling
Policy compliance Percent usage within agreed scope Up Admin review plus spot checks
Escalations Number of "stop and review" incidents Down Escalation log

If you need one headline metric: use sign-off time, and pair it with material rewrite time.

How do you measure outcomes without time tracking?

Use sampling and keep definitions consistent, especially for material rework.

Two practical methods:

  • Sampling for draft time: pick a small set of matters, record time to first reviewable draft, repeat during pilot.
  • Tracked changes for rework: compare the first draft sent for review to the next reviewed version, and count only material edits.

A simple rework standard:

Edit type Plain English Count as rework?
Cosmetic Clarity, formatting, grammar No
Material Risk position, obligations, definitions, fallbacks Yes

Consistency matters more than perfection.

What is the pilot ROI tracker template?

Track tasks and minutes saved by category, then compute hours saved and value recovered using explicit assumptions.

For the full method, see: Legal AI ROI for Contract Drafting

Pilot ROI tracker (copy/paste)

Category Task count Minutes saved per task Hours saved Notes
Drafting =(B2*C2)/60 Conservative assumptions
Research and analysis =(B3*C3)/60 Define query types
Review workflows =(B4*C4)/60 Material effort only
Matter history and reuse =(B5*C5)/60 Knowledge recall
Total =SUM(D2:D5)
Field Your value Formula
Pilot hours saved =Total hours saved
Rate (£/hour) Input
Pilot value recovered (£) =Pilot hours saved * rate

What does a go / extend / stop decision look like at the end of the pilot?

Decide based on evidence: adoption is real, outcomes improve, and governance is credible.

Criterion Go Extend Stop
Adoption Steady weekly usage Some usage, needs coaching Sporadic novelty use
Productivity Draft or research time improves Mixed signals, more sampling No measurable change
Rework Material rewrite time decreases Stable, needs more data Worse or unchanged
Sign-off Cycle time improves or variability drops Needs longer horizon No improvement
Governance Controls stable, low incidents Minor policy gaps Repeated escalations
Repeatability Method repeatable next quarter Needs metric cleanup Not measurable

A good outcome is "extend with tighter scope" when the method is solid but the sample is small.

Why Qanooni fits a UK firm pilot

Qanooni is designed to fit legal workflows in Word and Outlook and support measurable, governed adoption rather than tool switching.

Pilots fail when lawyers have to change how they work. Qanooni is embedded where drafting and email-based coordination happens.

For pilots that need credible measurement, Qanooni supports workflow-level attribution, helping teams map usage to outcomes like reduced rework and faster sign-off.

Frequently Asked Questions

How long should a legal AI pilot run? Long enough to capture real work and produce stable measurement. Some firms want a short sprint, others need more time for governance, templates, and sampling. The process matters more than the calendar.

How many users should be in a pilot? Start with 5–15 users, including 2–5 champions who will use it daily. Too many users early increases noise and governance complexity.

What if we do not have time tracking? Use sampling and tracked changes review. Keep definitions consistent, especially for material rewrite.

Should we include risk in pilot ROI? Only if assumptions are defensible. Most firms justify a scale decision using adoption, time saved, reduced rework, and sign-off time first.

Author: Qanooni Editorial Team

Sources

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