What your legal peers are saying about AI adoption.

80% are planning to expand or already scaling

How far along are other legal teams with AI? Are they seeing meaningful benefits? Have they figured out who owns implementation, or are they trying to fit it around everything else?

Lawtrades surveyed legal professionals about their departments’ experiences with AI. The responses offer a look at what peers are doing beyond the demos and announcements.

Of 98 respondents, 58 said their departments were actively planning to expand AI adoption over the next year. Another 20 said they were already scaling initiatives. Eighteen were considering expansion. Only two reported no plans to expand.

That appetite comes alongside reported benefits: 78 respondents said they had observed some level of efficiency improvement.

These are self-reported answers to separate questions; adoption stage and reported gains may not align. The reported answer ranges overlap at 50%.

Base: all 98 respondents. These are self-reported estimates, not independently verified productivity measurements.

If your department is seeing useful results in some tasks while still working out the broader plan, that experience is reflected in the survey.

Regular use is much more common than full automation

Fifty-seven respondents described their departments as actively using AI for specific tasks. Thirty-four were in early exploration, and four had not started.

Just three selected full workflow automation, described in the survey as agentic workflows or multistep automation.

Interest in agents was considerably broader: 47 respondents said they were actively exploring them, and another 32 were interested.

For anyone wondering whether their peers have already automated large portions of legal work, this distinction matters. In this sample, regular use for individual tasks was far more common than full workflow automation. Interest in agents was widespread, while reported implementation remained limited.

Half have a company-wide mandate. Fewer have sufficient budget.

Forty-nine respondents said their executive team or board had mandated AI adoption across the company.

Base: the 49 respondents reporting a company-wide AI mandate.

Across the full sample, only 11 respondents selected a documented strategy in active implementation. Forty-two said their strategy was in development, and another 42 reported no formal strategy. Three said it was not a priority.

These answers do not establish that departments lack controls or thoughtful practices. They do show that executive expectations, funding, and formal planning are not always moving together. A department can be using AI regularly while still deciding how to organize its next phase.

Time is the most frequently selected barrier

We asked respondents which barriers were preventing faster adoption and allowed them to select more than one.

Multiple selections were permitted, so percentages do not sum to 100%. Resources include budget, people, or infrastructure. Chart shows the five listed barrier categories; individual “Other” responses are not displayed.

The most frequently selected barriers concern the capacity to make implementation happen.

For legal ops leaders, that is a useful point to bring into planning conversations. Testing a tool, preparing information, and helping colleagues use it require time. An expansion plan needs to account for that work.

Choosing where to start is still difficult

When asked to identify their single biggest challenge in moving from exploration to implementation, the most common answer was finding the right use cases, selected by 26 respondents.

Lack of internal expertise or training followed with 19 responses. Fifteen selected integration with the existing legal technology stack, and 13 selected change management or team adoption.

The expertise question adds context: 66 respondents described their teams as having basic AI proficiency, while 18 selected limited awareness. Twelve described advanced users, and two selected leading-edge or expert capability.

That mix helps explain why a team might be using AI and still want help identifying its next investment. Familiarity with a tool does not settle which process to change, how to evaluate the result, or who will maintain it.

Your peers’ next priorities

Asked to choose their top AI priority for the next 12 months, respondents most often selected expanding adoption to new use cases, building custom or agentic solutions, and deepening integration.

Base: all 98 respondents. Each respondent selected one top priority.

Those plans span very different stages of adoption. They also sit alongside a finding worth watching: 65 respondents said their departments used multiple separate tools, while nine described multiple integrated tools.

Separate tools can serve different needs effectively. As teams expand, they will need to understand how information and responsibility move between them, and whether gains in one task improve the complete service.

What these results mean for your next team conversation

The survey offers a more useful comparison than a simple judgment about being ahead or behind. Your peers are reporting benefits while continuing to work through implementation.

Use the findings to ask where your own team needs support. If the constraint is time, identify what capacity implementation will require. If it is expertise, define the assignment someone needs help delivering. If it is use-case selection, choose a recurring task with a clear problem and a result the team can evaluate.

There is momentum in these responses. The next question is how legal departments will turn that momentum into improvements they can sustain.

Turn the next priority into a defined assignment

For teams facing similar constraints, the practical next step is to identify the work that needs an owner. That might be documenting approved knowledge, scoping a workflow, establishing a review process, or testing a use case before expanding it.

Lawtrades connects legal teams with attorneys, legal operations professionals, and legal engineers who can support those assignments. A legal operations professional can help define the process, responsibilities, and success measures. An attorney can help prepare guidance for internal approval. A legal engineer can support configuration and testing alongside your technical stakeholders. Flexible legal coverage can also free internal experts to lead implementation while ongoing work continues.

Bring Lawtrades the use case you want to advance and the expertise or capacity gap holding it back. Ask for a scoped proposal with deliverables, fees, timing, internal review responsibilities, and handoff requirements. Start with an assignment whose result your team can evaluate.

These are suggested ways to address implementation needs; the survey did not evaluate Lawtrades engagements or establish their outcomes.

For a bounded implementation plan, scope your first legal AI workflow.