That gap matters more than it might seem. Without data, the capacity problem stays a feeling. With it, it becomes a business case. And business cases are what unlock the budget, the leadership support, and the organisational permission to actually change how a legal function operates.
The good news is that the data already exists inside your team. You just have not collected it yet.
This article walks through the time audit methodology Plexus has used across 340 in-house legal teams, the four categories of legal work the audit reveals, and how to use your findings to build an internal case for automation. The headline finding from that body of work: 56% of total lawyer time sits in categories with high automation potential. For most teams, the number is not a surprise. What surprises them is seeing it in writing.
Before running your own audit, you need a framework for categorising what you find. Not all legal work carries the same automation potential, and conflating high complexity advisory work with routine contract execution will make your data useless.
Analysis across 340 in-house legal teams identifies four categories:
|
Work category |
% of lawyer time |
Automation potential |
What this includes |
|
Contracts and procurement |
38% |
HIGH |
NDAs, supplier agreements, standard commercial contracts, renewals, approval workflows |
|
Regulatory and compliance |
18% |
HIGH |
Regulatory tracking, policy updates, compliance queries, marketing review, promotional approvals |
|
Employment and governance |
12% |
HIGH |
Standard employment contracts, policy queries, board resolutions, routine governance documentation |
|
Litigation and disputes |
17% |
LOW |
Requires human judgement, strategic reasoning, and relationship management |
|
Corporate and M&A advisory |
15% |
LOW |
Requires human judgement, strategic reasoning, and relationship management |
The first three categories account for 68% of total lawyer time. Of that, McKinsey analysis identifies 44% of all legal tasks as technically automatable today. When Plexus maps this against actual team workflows, 56% of total lawyer time sits in these high automation categories.
The bottom two categories, litigation and disputes plus corporate and M&A advisory, require human judgement that AI cannot replicate. These are not the problem. They are what your lawyers should be spending their time on.
The audit does not need to be complicated to be useful. A two week snapshot is enough to generate actionable data. Here is the methodology used across the 340 team diagnostic programme:
Use the five categories above as your framework. Add one extra bucket: internal triage and email, which Plexus data shows consumes an average of 29% of lawyer time despite not appearing in any formal work category. This is the invisible overhead that most teams consistently underestimate.
Your final categories should be:
• Contracts and procurement
• Regulatory and compliance
• Employment and governance
• Litigation and disputes
• Corporate and M&A advisory
• Internal triage, email, and admin
There are three practical options depending on your team size and tolerance for process:
Time logging: Ask each lawyer to log their work in 30 minute blocks for two weeks, tagging each block to a category. Calendar blocking tools or a shared spreadsheet work well. Compliance drops off after day three for most teams, which is why two weeks rather than one month is the right window.
Matter tagging: If your team uses a matter management system, tag all open matters by category. Pull a report at the end of the period. This is faster but less granular as it captures volume rather than time.
Calendar analysis: Export lawyer calendars for a two week period and categorise each meeting and block. This captures scheduled time accurately but misses unscheduled reactive work, so it tends to undercount admin and triage.
For most teams, option one gives the best data. The act of logging also tends to surface frustration that supports the case for change.
Aggregate inputs at the end of the two week window. Normalise the data to percentages of total lawyer time rather than absolute hours. This makes the findings comparable to the benchmarks in the Plexus diagnostic and easier to present to a non-legal audience.
Calculate your team total and individual breakdowns separately. Individual variation often reveals more than the aggregate: one lawyer spending 70% of their time on contracts while another spends 20% signals a process problem, not a capacity problem.
Run your findings against the benchmark data. The pattern in high performing legal functions is:
• Contracts and procurement: under 25% of total time
• Strategic advisory and risk oversight: over 40% of total time
• Internal triage and email: under 15% of total time
If your contracts and procurement figure is above 35%, your team has a significant automation opportunity. If your strategic advisory figure is below 20%, that is the core problem the audit should surface.
Across 340 teams, the Plexus diagnostic surfaces a consistent pattern. The stated priorities of GCs and the actual allocation of their team's time are not close.
|
Work category |
Where GCs say they want to spend time |
Where time actually goes |
|
Strategic advisory |
45% |
12% |
|
Risk and compliance oversight |
25% |
18% |
|
Contract execution |
10% |
41% |
|
Internal triage and email |
5% |
29% |
Source: Plexus Legal Function Diagnostic 2025, n=340 in-house teams
The gap between stated priorities and actual time allocation on strategic work is consistently 25 to 35 percentage points. It does not close by working harder. It does not close by hiring more lawyers. It closes by redesigning the function.
69% of GCs spend less than 40% of their time on strategic work. The ones who consistently exceed that threshold are not operating in organisations with lighter workloads. They have automated the categories that do not require a lawyer, and redirected that capacity toward the work that does.
The audit gives you the inputs. The business case converts them into a financial argument that a CFO will engage with. The key is to translate time into cost and cost into risk before you bring it to finance.
Take your automatable time percentage and apply it to your total legal salary cost. If your team spends 56% of its time in high automation categories, and your total annual legal salary bill is $1.2 million, then roughly $672,000 of that cost is going to work that could, in principle, be handled without lawyer time.
You do not need to claim that all of that is recoverable. Even recovering 30% of it, which aligns with the 21 to 40% manual work reduction that 43% of AI adopters are already reporting, produces a compelling number.
The CFO question is not whether automation saves money. It is whether the investment required to automate costs less than the ongoing drain of not doing so. The most effective business cases frame legal technology as a reallocation of existing spend rather than a new budget line.
If your team is currently referring high volumes of standard contracts to external counsel because internal capacity is exhausted, that cost line is your business case. Only 20% of legal matters sent to outside counsel stay within budget (Gartner, 2025). Bringing that work in-house with automation support is a quantifiable saving, not a speculative one.
The hardest number to put in a business case is the cost of opportunity foregone. But GCs who do not attempt it leave the most persuasive argument on the table.
If your team currently spends 12% of its time on strategic advisory work but the business is asking for 40%, the gap is not a headcount problem. It is a workflow problem. Frame the audit findings as evidence that the legal function is structurally unable to deliver the strategic value the organisation needs, and that automation is the mechanism to close that gap.
That is a board level argument, not a procurement level one. It is significantly more likely to get funded.
The question GCs ask most often is not whether automation saves time. They know it does. The question is what happens to that time once it is recovered.
The evidence from teams that have operationalised AI is consistent. The capacity recovered from contract execution and compliance administration does not disappear into more reactive work. When the function is redesigned deliberately, it flows into three areas:
• Strategic advisory work that the business has been waiting for. GCs who automate contracts find they are having conversations with the CEO that they previously had no bandwidth to pursue.
• Risk management that is currently being done reactively, if at all. Compliance monitoring, regulatory tracking, and governance oversight move from retrospective to proactive.
• Business partnering that strengthens the legal function's internal reputation. The GC who can respond quickly to commercial queries because contracts are automated is a different kind of partner than the GC who is always three weeks behind.
43% of GCs using AI are already reporting a 21 to 40% reduction in manual legal work. The teams achieving this are not just running the same function faster. They are running a different function.
The time audit is the first step. It converts a feeling into a number. And a number, in front of the right audience, is the beginning of a business case that actually gets funded.
Download the Plexus Future-Ready General Counsel 2026 report, the data behind the decisions shaping in-house legal today.