What Legal AI ROI Looks Like for In-House Teams

In-house legal teams are under growing pressure to support faster, more complex day-to-day legal work without proportional increases in headcount or budget for outside spending. Legal AI has emerged as a powerful lever, but its value isn’t measured by time savings alone.

For these teams, real ROI shows up when AI helps them scale capacity, move faster across core work, and keep costs under control. That means absorbing more work internally, reducing routine reliance on law firms, and giving lawyers the space to focus on higher-judgment, strategic work.

To help legal leaders evaluate and quantify that impact, we created The Legal AI ROI Guide for In-House Legal Teams. The guide outlines how in-house teams are defining ROI today, which levers matter most to the business, and how to turn AI adoption into measurable efficiency across headcount, spend, and velocity.

Below, we introduce the core ideas behind that framework and what ROI looks like in practice for modern in-house legal teams.

Turning Time Saved Into Measurable ROI

Across in-house teams using Harvey, lawyers routinely save 15–25 hours per month, with power users saving 30–50+ hours. These time savings matter, but on their own, they don’t justify investment. ROI becomes real when reclaimed time turns into measurable business outcomes. In-house teams see that value across three core areas:

1. Velocity

In internal testing and customer surveys, many legal tasks are completed 60–90% faster with Harvey. Faster workflows shorten contract cycles, reduce friction in procurement and approvals, and help legal keep pace with revenue-driving teams without expanding headcount.

2. Talent

By reducing time spent on repetitive work, legal AI creates space for judgment, strategy, and stakeholder partnership. Teams report more engaging work, faster ramp-up for new lawyers, and better retention — quietly reducing the hidden costs of burnout, turnover, and backfill.

3. Cost

When routine legal work (like drafting, review, research, and comparison) moves in-house with AI support, teams reduce reliance on outside counsel. Firms stay focused on high-value matters, while routine day-to-day work is handled internally.

ROI compounds when all three levers move together, enabling in-house legal teams to deliver more value without increasing cost.

ROI Requires Change Management

Legal AI doesn’t create ROI on its own. Value depends on how it’s introduced, adopted, and embedded into day-to-day legal work.

In-house teams that see meaningful returns start with clear goals tied to business outcomes, such as increasing internal capacity or improving speed across high-volume work. They focus pilots on specific use cases, define success metrics upfront, and involve lawyers across roles and seniority early.

ROI also depends on sustained adoption. Training, workflow integration, and ongoing enablement help ensure AI becomes part of how legal work is done, rather than a standalone tool. As usage scales, teams are able to standardize quality, capture time and cost savings consistently, and support the business more effectively.

In practice, effective change management tends to focus on three areas:

• A focused pilot: Start with a high-impact use case tied to clear business metrics — such as hours saved or faster turnaround — to generate early proof and executive alignment.
• Structured enablement: Support adoption with role-based training, workflow-specific playbooks, and ongoing visibility into usage, ensuring AI becomes embedded in day-to-day legal work.
• Platform integration and shared workspaces: Connect AI to existing systems and collaboration tools so teams can work in context, standardize workflows, and collaborate securely with business partners and outside counsel.

Together, these elements move AI from experimentation to operational infrastructure, which is where sustained ROI is realized.

Real-World Example: How Carvana Scaled Legal Without Scaling Spend

Carvana offers a clear example of what legal AI ROI looks like in practice for an in-house team.

As the company scaled its platform, legal demand increased across contracts, financing, litigation, compliance, and product development. The challenge wasn’t simply volume; it was supporting a fast-moving business without continually adding headcount or increasing spend.

Carvana began with a targeted Harvey pilot, then expanded usage across more than 70 professionals spanning Legal, Government Affairs, Real Estate, Financial Reporting, and Investor Relations. The goal was to build an AI-powered legal operating model that could scale with the business.

The impact was measurable. With AI embedded into drafting, review, research, and quality control workflows, Carvana estimates that each lawyer now reclaims 7–10 hours per week. Routine work that previously flowed to outside counsel is handled internally, while firms remain focused on high-value, specialized matters. Drafting and review cycles that once took hours or days now take minutes, helping legal keep pace with the business without expanding the team.

Just as importantly, that reclaimed capacity is reinvested in higher-judgment work: advising stakeholders, accelerating transactions, and supporting leadership with greater speed and consistency.

Carvana’s experience highlights a key point: When legal AI is deployed with clear goals and supported by adoption and workflow change, it enables in-house teams to scale impact, control spend, and operate at the speed the business requires.

Thinking about how legal AI could support your team’s priorities? The Legal AI ROI Guide for In-House Legal Teams walks through how in-house teams are quantifying ROI, identifying high-impact use cases, and turning AI adoption into measurable efficiency across headcount, spend, and speed.