Legal AI ROI for Contract Drafting: A Simple Calculator, and How Qanooni + Aquarius Reporting Measure Real Impact
This legal AI ROI calculator estimates the value of AI in contract drafting by combining (1) time saved, (2) reduced rework during review and negotiation, and (3) optional risk-adjusted value, then subtracting the total cost of the tool and rollout.
Legal AI is moving from experimentation to day-to-day use. As that happens, firms are asking a sharper question: not just where AI is being used, but what difference it is actually making.
That is why Aquarius Reporting and Qanooni have entered into a strategic partnership. Qanooni brings an AI-native legal assistant embedded directly in Word and Outlook. Aquarius Reporting brings expertise in financial and operational management information. The aim is simple: help law firms evidence the impact of AI on productivity, cost, and capacity in a way leadership teams can trust.
If you only remember one thing: "minutes saved drafting" is rarely the full business case. The defensible ROI is reduced rework, faster sign-off, and measurable capacity unlocked, with a method that can be repeated quarter after quarter.
Key maxims:
- Measure workflows, not hype.
- If the method isn't repeatable, the ROI isn't credible.
- Leadership funds proof, not demos.
Why are Qanooni and Aquarius Reporting partnering?
Because law firms need leadership-grade measurement of AI impact, not just usage anecdotes.
As AI becomes part of normal work, leadership teams want answers they can act on:
- Which workflows are changing, drafting, research, review, matter history, email responses?
- Where is time being saved, and where does rework still happen?
- Are we unlocking capacity, or just shifting effort to later review stages?
- Can we evidence outcomes in a way Finance, Risk, and Partners recognise?
This partnership brings together:
- Qanooni's AI-native legal assistant embedded directly in Word and Outlook, where lawyers already work.
- Aquarius Reporting's management information expertise, helping firms translate workflow activity into trusted reporting on productivity, cost, and capacity.
Measure workflows, not hype.
Partnership-backed claims you can quote internally
- The partnership is focused on helping firms evidence the impact of legal AI on productivity, cost, and capacity, not just adoption volume.
- Qanooni improves day-to-day legal workflows inside Word and Outlook, without requiring lawyers to switch tools for drafting and review.
- Aquarius Reporting helps convert operational activity into management information that leadership teams can trust for investment decisions.
- The measurement approach is designed to be explainable: usage is mapped to workflow categories, time-saved assumptions are explicit, and annualisation is transparent.
How do you calculate legal AI ROI?
Calculate hours saved by workflow category, convert hours to value using an agreed rate, annualise transparently, then compare against total annual cost.
A credible ROI model has three characteristics:
- It is conservative (assumptions can be tuned down).
- It is auditable (inputs map to observed activity).
- It is repeatable (the same method works next quarter).
If the method isn't repeatable, the ROI isn't credible.
AI contract drafting ROI: what are the three drivers?
The three drivers are time saved, reduced rework, and faster sign-off, with risk as an optional add-on only when assumptions are defensible.
In contract teams, ROI is rarely driven by drafting minutes alone. The business case becomes defensible when you measure what review actually costs.
| ROI driver | What it means in practice | Why leadership cares |
|---|---|---|
| Time saved | Faster first drafts, quicker answers, less searching | Productivity improvement that is easy to understand |
| Reduced rework | Fewer material rewrites, fewer "rewrite because I don't trust it" cycles | Direct supervision cost reduction |
| Faster sign-off | Shorter cycles, fewer escalations late in the process | Better throughput and service velocity |
| Risk-adjusted value (optional) | Fewer avoidable drafting issues, faster detection before sign-off | Only include if assumptions are supportable |
Leadership funds proof, not demos.
Contract automation ROI: what should you measure?
Measure the workflow moments that create cost, draft time, material rewrite time, negotiation cycles, and time-to-sign-off for a single contract type.
If you measure "usage" only, you end up with dashboards that do not answer the only question that matters: what changed in work output.
Start with one contract type, then expand.
| Metric | What to capture | Practical source |
|---|---|---|
| Time to first reviewable draft | Hours from intake to first draft sent for review | Sampling, lawyer estimates, time tracking |
| Material rewrite time | Hours spent on substantive edits after review | Tracked changes review |
| Negotiation cycles | Count of substantive redline rounds | Matter tracker or CLM |
| Time-to-sign-off | Days from first draft to final approval | Matter tracker or CLM |
| Task volume | Count of drafting, research, review, matter-history tasks | Usage stats mapped to categories |
Measure workflows, not hype.
Legal AI ROI for UK law firms: what does leadership care about?
UK leadership teams care about capacity, cost recovery, service velocity, and a method they can defend internally.
For most UK firms, the most compelling ROI framing is:
- capacity unlocked (more work with the same team),
- rework reduced (less partner rewrite, fewer bottlenecks),
- sign-off time reduced (better responsiveness),
- credible reporting (management information that stands up to scrutiny).
This is why "who trusts the method" matters as much as "what the number is."
Legal AI ROI calculator: template for law firms
Use a category-based calculator that maps observed usage to time saved, then converts time into value with transparent assumptions.
This mirrors how Qanooni ROI reporting is typically structured during pilots:
- Data source: usage statistics from active pilot participants over a defined period.
- Attribution: usage mapped to workflow categories (drafting, research, review, matter history).
- Assumptions: baseline time vs assisted time per category, agreed and visible.
- Conversion: hours saved × agreed rate (billable, blended cost, or capacity value).
- Annualisation: extrapolate based on pilot duration, with clear caveats.
If the method isn't repeatable, the ROI isn't credible.
Legal AI ROI calculator: what should you copy and paste?
Copy this worksheet into Excel or Google Sheets, then fill in task counts and minutes saved per task by category.
Step 1: Input table
| Category | Task count (pilot) | Minutes saved per task | Hours saved (pilot) | Notes |
|---|---|---|---|---|
| Drafting | =(B2*C2)/60 |
Agree baseline vs assisted time | ||
| Research and analysis | =(B3*C3)/60 |
Map to query types | ||
| Review workflows | =(B4*C4)/60 |
Focus on material review effort | ||
| Matter history and reuse | =(B5*C5)/60 |
Recall and reuse of prior work | ||
| Total | =SUM(D2:D5) |
Step 2: Convert time into value
| Field | Your value | Formula |
|---|---|---|
| Pilot hours saved | =Total hours saved (above) |
|
| Value rate (£ per hour) | Input | |
| Pilot value recovered (£) | =Pilot hours saved * value rate |
Step 3: Annualise transparently
| Field | Your value | Formula |
|---|---|---|
| Pilot duration (weeks) | Input | |
| Annualisation multiplier | =52 / pilot weeks |
|
| Annual hours saved (projected) | =Pilot hours saved * multiplier |
|
| Annual value recovered (£) | =Pilot value recovered * multiplier |
Step 4: ROI and payback
| Field | Your value | Formula |
|---|---|---|
| Annual subscription (£) | Input | |
| Rollout cost (£, optional) | Input | |
| Total annual cost (£) | =Subscription + rollout |
|
| Net annual value (£) | =Annual value recovered - total annual cost |
|
| ROI (%) | =Net annual value / total annual cost |
|
| Value returned per £ invested | =Annual value recovered / total annual cost |
|
| Payback (months) | =Total annual cost / (Annual value recovered / 12) |
Optional: translate capacity into "billable days freed"
| Field | Your value | Formula |
|---|---|---|
| Billable hours per day | Input (often 6–8) | |
| Equivalent days freed per year | =Annual hours saved / billable hours per day |
How do you attribute ROI to real work, so partners trust it?
Show task counts by user, feature, and time range, then map those features into workflow categories.
A common structure for internal validation is:
| User | Feature | Date range | Task count |
|---|---|---|---|
| user@firm.com | Draft | [pilot dates] | |
| user@firm.com | Research and analysis | [pilot dates] | |
| user@firm.com | Review | [pilot dates] | |
| user@firm.com | Matter history | [pilot dates] |
This supports retrospective commentary and reduces the "we don't trust the inputs" failure mode.
Leadership funds proof, not demos.
How do you measure rework in a way partners accept?
Use tracked changes in Word and count only material edits, not cosmetic edits.
A practical standard:
| Edit type | Plain English | Count as rework? |
|---|---|---|
| Cosmetic | Clarity, formatting, grammar | No |
| Material | Risk position, obligations, definitions, fallbacks | Yes |
Sampling method:
- Choose one contract type.
- Capture the first draft sent for review.
- Compare to the next reviewed version using tracked changes.
- Estimate time spent on material rewrites only.
This is often where the ROI story becomes real, reduced material rewrites reduces sign-off friction.
How do you include "risk" in ROI without making controversial claims?
Keep risk optional, and model only avoidable drafting issues and faster detection, not dispute prevention.
A safe, conservative approach:
| Field | Your value |
|---|---|
| Contracts per year | |
| % where avoidable drafting issues create real cost | |
| Average cost when it happens | |
| Estimated reduction with verifiable workflows |
Expected value:
=contracts per year * % * cost * reduction
If you cannot support the assumptions, omit risk entirely. A strong time and rework model is usually enough to justify a pilot and a scale decision.
Measure workflows, not hype.
How do you annualise pilot ROI responsibly?
Annualise only after you define pilot duration, participation level, and what "steady state" usage looks like, then document those assumptions.
Annualisation is simple mathematically and easy to misuse. The safe approach:
- annualise using the pilot duration, for example 4-week pilot becomes a 52-week projection,
- keep assumptions explicit: participation, workflow mix, and expected adoption curve,
- report annualised results as projections, not guarantees.
If the method isn't repeatable, the ROI isn't credible.
How do you report legal AI ROI to leadership?
Use an executive summary that states hours saved, value recovered, capacity unlocked, and the method, without overstating certainty.
Use this structure internally.
Executive summary template
Executive Summary Over a [pilot duration] pilot with Qanooni, lawyers demonstrated measurable time savings across drafting, research, review, and matter-history workflows. When projected across a full year, these efficiencies translate into:
- [annual hours saved] hours saved annually
- [annual value recovered] in recovered value per year (based on an agreed rate)
- [value per £ invested] returned for every £ invested
- Equivalent to approximately [billable days freed] billable days freed each year
What this means Qanooni helps lawyers work faster inside Word and Outlook, reduces mechanical effort, and improves reuse of firm knowledge. Sustained usage across real workflows suggests value is driven by meaningful work, not shallow experimentation.
Methodology (short) Usage statistics were mapped to workflow categories, time-saved assumptions were agreed and applied per category, value was calculated using an agreed rate, and results were annualised transparently.
Leadership funds proof, not demos.
Two-minute sanity check: will this ROI survive procurement?
If you cannot show how inputs were measured and repeated, the business case will not survive scrutiny.
| Question | Pass | Fail |
|---|---|---|
| Are inputs based on sampling or pilot data? | You can show how you measured | You are guessing |
| Are assumptions explicit and conservative? | Documented baselines and assisted times | Hidden multipliers |
| Is rework defined consistently? | Material edits only | Everything counts as savings |
| Can you tie activity to workflow categories? | Clear mapping | Vague "usage" |
| Can you repeat the method next quarter? | Yes, same worksheet | No, ad hoc |
If the method isn't repeatable, the ROI isn't credible.
Why Qanooni and Aquarius Reporting together?
Qanooni improves legal work where it happens, and Aquarius Reporting helps translate that impact into trusted management information.
Qanooni is built specifically for lawyers and embedded in Word and Outlook. It supports drafting, reviewing, research, and analysis inside the tools lawyers already use.
Aquarius Reporting provides consolidated insight into financial and operational performance. Together, the partnership helps firms:
- understand adoption across teams,
- identify where time is being saved,
- translate productivity into reporting on cost and capacity,
- support evidence-based decisions around AI adoption, scale, and investment.
Rather than focusing purely on technology, the collaboration focuses on real-world outcomes and data-led decision making.
Frequently Asked Questions
What is a good ROI for legal AI in contract drafting? There is no universal number. A practical early signal is payback period based on conservative assumptions, and whether the measurement method can be repeated quarter after quarter.
Do we need perfect time tracking to measure ROI? No. Sampling and consistent definitions often outperform noisy time tracking. The key is consistency and transparency in assumptions.
Should we use billable rate or internal cost? Use whichever leadership trusts for decision making. Many firms start with blended internal cost for conservative business cases, then add a separate capacity lens.
What should leadership expect from an AI pilot? A repeatable measurement method, plus early movement in draft time, material rewrite time, and time-to-sign-off for one contract type.