From implementation to accountability

Moving from AI adoption to AI accountability

Only a few years ago, AI in the legal department meant experimentation — a few pilots, some hype, some intriguing possibilities, and a healthy amount of skepticism married with lawyers’ general slowness to adopt any new technology. That phase of the AI revolution is over. AI is here to stay. It is embedded in legal department workflows and baked into enterprise software. Most importantly, company leadership expects the legal department to use it.

In-house counsel has responded. Many legal departments are already using multiple tools — some free, some paid, and some adopted as part of broader company-wide enterprise tools. That change is both progress and a problem.

The progress bit is obvious. In-house lawyers have embraced AI like no other technology before it. General counsel has seen that the right use of AI will dramatically improve efficiency, reduce costs, and allow legal teams to focus on higher-value work. Those are goals all legal departments share. The problem, however, is more subtle; while senior management expects its lawyers to use AI, most legal departments cannot clearly demonstrate whether their AI tools are delivering any benefits. In a world of KPIs, dashboards, consultants, and tight budgets, this is not good.

This means that the next phase of the AI journey for in-house counsel is moving from implementation of AI to accountability around the benefits it provides to the business — what is our return on investment for all this technology? Previous discussions have focused on making the business case for legal technology and how to select and implement the right tools. This white paper assumes you have already taken those steps, or are well along the way to doing so. Instead, we will focus on the next critical steps. Are you getting what you paid for, and how do you prove it?

The core problem: Speed of adoption vs. clarity of value

AI has been adopted faster than any prior legal technology. That rapid pace has created a disconnect for legal teams.

On one side:

• The C-suite expects AI to drive efficiency gains, cost reductions, and better data.
• Business teams expect AI to result in faster turnarounds and more self-service.
• Vendors promise AI will deliver “transformational” outcomes.

On the other side:

• Legal teams often struggle to find baseline data.
• AI usage is inconsistent across the department.
• Results are often anecdotal rather than measurable.

This disconnect is problematic for in-house counsel. Legal departments are already under pressure to do more with less, balancing increasing workloads and expectations with constrained — or reduced — budgets. AI is supposed to relieve that pressure. But without reliable measurement, AI technology becomes just another expense to justify to the bean counters — or worse, another expensive tool that slowly dies on the vine from lack of use.

The reality, therefore, is stark; if you cannot measure the value of AI, you cannot manage it and you cannot defend it.

Time for a reality check — not all AI tools are created equal

Before diving into how to measure the value of AI use, it is worth addressing an uncomfortable truth. Some AI tools are simply not worth measuring. In-house legal departments are uniquely exposed to this issue because they often:

• Experiment with free, general-purpose tools
• Inherit, or are forced to use, company enterprise solutions not designed for legal use
• Pile up multiple tools on top of one another without proper integration

This creates three big problems for in-house lawyers:

• Unreliable outputs. Public AI tools lack a grounding in legal data and their outputs may not reflect current law or jurisdictional nuance.
• Disparate workflows. Disconnected tools make consistent usage difficult when solutions don’t fit together easily.
• Inadequate security. Sensitive company and legal data may be exposed by individual tools or the connections between tools.

However, Fiduciary-Grade AI™ legal solutions , are markedly different. They are built on several critical foundational considerations:

• Workflows grounded in trusted, maintained legal content
• Designed, tested, and proven by legal experts
• Outputs designed to be defensible and verifiable
• Enterprise-grade security and compliance
• Integrated with existing legal and business solutions

If your AI tool cannot meet those standards, measurement is beside the point. You are not measuring value; you are measuring risk.

Defining value: What should you actually measure?

One of the most common mistakes legal departments make is trying to reduce “AI value” to a single number. That approach does not work. AI delivers value across a variety of uses and dimensions. A proper measurement framework must reflect this. At a minimum, legal departments should focus on three categories:

• Cost savings
• Time savings
• Strategic impact

These three categories allow you to measure the tangible and intangible benefits of AI use, the latter folding nicely into the concept that “value” is both quantitative and qualitative. Together, these three categories allow you to tell the full story about AI. Below, we discuss each one.

Cost savings: The easiest metric to understand, but the hardest to get right

As one would expect, cost savings are the most visible and most scrutinized measure of AI value. They are also the easiest to misunderstand. For most legal departments, cost savings fall into three buckets:

1. Reduced outside counsel spend

• Bringing work in-house that was previously outsourced to law firms
• Better triage of matters; what goes out, what stays in, and how the work is prioritized
• More efficient management of outside counsel

Legal technology has long been associated with reducing reliance on external counsel by enabling in-house teams to handle more work directly.

2. Efficiency-driven savings

• Faster contract review and negotiation
• Reduced research time
• Automation of repetitive tasks, allowing more time to do high-value work

The right use of technology can take work off in-house attorneys' plates and give them more time to spend on more complex and higher-value projects.

3. Risk avoidance

• Fewer compliance failures through automated regulatory guidance
• Reduced litigation exposure through early detection of disputes
• Improved contract quality through consistent contract processes

AI can help a department be more consistent in all three areas, providing consistency and rigor in oversight and allowing the legal department to intervene early if necessary.

When it comes to measuring value in cost savings, start with simple, defensible metrics:

• Outside counsel spend before versus after AI adoption
• Cost per matter
• Value of work handled internally; number of matters and percentage of matters
• Estimated cost of avoided errors or delays

One critical tip. Resist overstating the numbers. While you may feel confident that the higher numbers are justified, conservative estimates build credibility and make it easier to demonstrate success over time. In other words, it keeps the finance team happy and provides wiggle room for you later down the road.

Time savings: The fastest way to demonstrate value

While cost savings are the most visible metric, time savings are the most immediate. This is because AI excels at reducing time spent on routine, repeatable tasks, the work that often consumes a disproportionate amount of legal department bandwidth. This time savings is typically found in:

• Responding to internal business queries
• Document review and summarization
• Legal research
• Contract drafting
• Litigation analysis

Each of these aligns with the most common use cases for AI in legal practice, especially around proven time savers like document review, research, and drafting. Many in-house lawyers report saving multiple hours per week through AI-driven automation. Even if just a few hours a week for each member of the team, this time savings compounds quickly and, over the course of a year, turns into hundreds of hours of valuable time flowing back to the department.

When it comes to tracking time savings, start with:

• Time per task before versus after AI
• Turnaround times for a handful of key workflows
• Volume of tasks completed

Then convert that time savings into something meaningful to the business:

• Cost equivalents, based on internal billing rates or salary assumptions
• Increased capacity; more work handled without adding headcount
• Faster business outcomes, such as quicker contract execution resulting in more money in the door sooner

Legal department time savings are only valuable to the business if you can show what you did with that time. For most legal teams, it will not take much to show the value of time saved.

Strategic impact: Where AI becomes a competitive advantage

If you stop at cost and time savings, you are leaving value on the table — never a wise move. The most sophisticated legal departments, large and small, also measure the strategic impact of AI, the ways it changes how the department operates and contributes value to the business. There are several key areas of strategic value to consider making part of your value equation:

• Better decision-making. AI enables faster access to relevant information, improving the quality of legal advice.
• Improved accuracy and consistency. Automation reduces variability and human error.
• Stronger alignment with the business. Legal can respond more quickly and proactively to business needs.
• Enhanced reporting and visibility. AI-driven insights improve transparency for leadership.
• Talent retention and engagement. Reducing low-value work improves job satisfaction and helps retain top talent.
• Brainstorming. One of the most interesting uses of AI tools is as a brainstorming partner; ask it to analyze facts or situations and give you strategic insights and ideas to build on.

These legal operations benefits are often harder to quantify, but they are no less real. For the most part, they distinguish a high-performing legal department from an average one, though you may not be able to turn all of them into numbers for a report to your CEO.

Building out a practical measurement framework

All of the above is fine, but if you do not have a usable framework for measurement, then it is all for naught. Fortunately, measurement does not need to be complicated. But it does need to be intentional, and that takes some forethought to get right. A practical framework can be broken into four steps:

Step 1: Establish your baseline

Before you can measure improvement, you need to know where you started. This means you must document:

• Current costs. Outside counsel spend and cost per matter
• Current turnaround times. Including scenarios such as using company templates versus using customer paper
• Current error rates or compliance incidents. Uncommon but valuable; include contracts missing key clauses, redrafting requests, use of outdated templates, incomplete and faulty guidance

Without a baseline, improvement is simply guesswork.

Step 2: Define your key performance indicators (KPIs)

Focus on creating a manageable set of KPIs across the three value categories:

Step 3: Track continuously

Measurement is not a one-time exercise. It must be an integral part of ongoing legal operations. Tracking key metrics after rollout is essential to understanding ROI and impact. Regular tracking allows you to:

• Identify issues early
• Adjust workflows
• Reinforce successful use cases

Step 4: Compare results to expectations

Finally, use all available data and information to evaluate whether your AI tools are:

• Delivering the expected benefits
• Being used as intended
• Supporting the right workflows

If not, adjust what you are doing. Measurement without action is just reporting. Moreover, KPIs are not static. Over time, refine the ones you have, remove those that are not helpful, and create new ones as circumstances dictate.

Reporting results: Telling the story

Measurement is only useful if it is communicated effectively to those who matter. Different stakeholders care about different things, and your reporting should reflect that. Consider the following:

• When reporting to the legal team, focus on:
  • Demonstrating that the change was worth the time and effort
  • Highlighting time savings and ease of use
  • Sharing practical examples of success, especially time savings

The goal is adoption. Lawyers and other members of the legal department need to see that the AI tools adopted by the department help them do their jobs better.

• When reporting to the C-suite, know that executives care about:
  • Strategic implications
  • Cost savings
  • Business impact
  • Risk reduction

Frame your results accordingly:

“We reduced outside counsel spend by X%.”

“We shortened contract turnaround time by Y days.”

“We improved compliance reporting across Z jurisdictions.”

More specifically, tie AI performance directly to business outcomes. Executives don’t want to hear the legal analysis; they want to know how whatever you did helped generate value for the business or prevented and limited value destruction. No matter what you do, how and when you present the results matter:

• Keep it simple and focused
• Use dashboards where possible
• Combine data with real examples tied to the company
• Report regularly; quarterly is a good starting point

Ensuring alignment within the department: Are your AI tools doing what you expect?

Measurement is not solely about proving value; it is also about ensuring alignment between expectation and reality — especially within the department. Ask the following questions regularly and track the results via KPIs:

• Are lawyers and staff using the tools consistently?
• Are outputs accurate and reliable?
• Are workflows improving?
• Do users trust the results from AI tools?

If the answer to any of these is “no,” you have work to do. Adoption is the single biggest limiting factor to success when it comes to technology. Legal tech succeeds or fails based on whether people actually use it and not on how many features it has.

Common pitfalls to avoid
Even the biggest and most well-intentioned legal departments fall into predictable traps when measuring AI value. Regardless of size (or intentions), these are the most important pitfalls to avoid:

• Focusing only on cost savings. This misses the broader strategic impact of AI
• Failing to establish a baseline. Without a starting point, improvement cannot be demonstrated
• Allowing inconsistent usage in the department. Fragmented adoption leads to unreliable data
• Relying on the wrong tools. General-purpose AI tools will not likely provide reliable or defensible outputs
• Misalignment with business goals. Metrics must reflect what matters to the business and not just legal

Get these five right, and your department is well on its way to meaningful AI usage.

The importance of leadership

AI measurement and optimization require active leadership of the department. A clear AI strategy and engaged leaders will almost always lead to meaningful ROI and competitive advantage. For department leaders, this means:

• Using the tools and not just talking about them
• Setting clear expectations
• Defining success metrics
• Driving adoption across the team
• Communicating results to stakeholders

AI is not a “set it and forget it” investment. It requires ongoing attention to get it right and keep it moving in the right direction. If you are going to invest time and money in AI tools, know that leadership must invest time and political capital as well.

Next steps for your department

AI is no longer an “experiment” for corporate legal departments. It is now a core part of how legal work gets done. The departments that succeed will not be the ones that simply adopt AI. They will be the ones who measure its impact, manage its performance, and communicate its value. By focusing on cost savings, time savings, and strategic impact, and by building a structured approach to measurement and reporting, legal leaders can move from uncertainty to confidence that:

• They are using the right AI tools, including agentic AI
• They are getting real value
• They can demonstrate that value to the business

Ultimately, confidence that the legal department is not just keeping up with AI — it is leading with it. That fact has become table stakes at most companies.

If your legal department is ready to move beyond adoption and begin measuring and demonstrating real value from AI, the next step is ensuring you are using tools designed specifically for in-house legal work. One option is Thomson Reuters CoCounsel Legal:

• Fiduciary-Grade AI built on trusted legal content
• Integrated workflows across core legal use cases
• Enterprise-grade security and compliance
• Tools designed to deliver measurable ROI

If you feel as if your legal department is lagging when it comes to AI adoption or reporting, the solutions you need are just a click away.

STERLING MILLER, COO, GENERAL COUNSEL AND SENIOR COUNSEL, HILGERS PLLC

Sterling Miller is a four-time General Counsel who spent almost 25 years in-house. He has published seven books, including The Productive In-House Lawyer: Tips, Hacks, and the Art of Getting Things Done and Showing the Value of the Legal Department: More Than Just a Cost Center. He writes the award-winning legal blog, Ten Things You Need to Know as In-House Counsel. Miller is a frequent contributor to Thomson Reuters and a sought-after speaker. He regularly consults with legal departments and coaches in-house lawyers. Miller received his J.D. from Washington University in St. Louis and an undergraduate degree from Nebraska Wesleyan University.