How to unlock AI's ROI with data-driven investment cases

6 minute read  30.06.2025 Jason McQuillen, Matt Johnson

Despite recognising AI's potential, many in-house legal teams struggle to secure investment. We outline ROI with hard numbers, addressing data deficits, building data-driven business cases to transform AI investment discussions.


Key takeouts


  • In-house legal functions face a unique challenge in adopting Generative AI (GenAI) due to a lack of investment and data to demonstrate ROI, despite recognising its transformative potential.
  • General Counsels must shift from focusing on technology capabilities to presenting data-driven business cases that align with CFOs and CEOs' expectations, emphasising measurable business outcomes.
  • Our AI Advisory team outlines practical steps for General Counsels to gather baseline data, assess current resource deployment, and build compelling AI investment cases to transform in-house legal functions from cost centers to value drivers.

The strategic imperative: From cost centre to value driver

In-house legal functions face an unprecedented opportunity disguised as a familiar challenge. According to Thomson Reuters' 2025 Generative AI in Professional Services Report (TR's Report), 57% of them recognise GenAI's transformative potential but most, at best, remain stuck in perpetual pilot mode, unable to secure meaningful investment to move beyond preliminary use cases or surface level training initiatives.

For forward-thinking General Counsels, GenAI represents more than a technology decision. It's the pathway to reposition the function from a necessary cost centre to an indispensable value driver. TR's Report, however, outlines several barriers to realising AI's benefits, including capability gaps, risk aversion, and regulatory uncertainty (to name a few). One of those barriers has inhibited General Counsels time and time again - the inability to articulate ROI. To unlock investment, that must change and General Counsels need to speak the language CFOs and CEOs understand, which involves hard numbers tied to measurable business outcomes.

This article outlines the challenge of the data deficit and what budget holders want to know, before providing the practical steps General Counsels need to take to build clear, data-driven business cases to secure AI investment, ultimately creating a clear path forward to transformation.

In-house legal functions: The data deficit

TR's Report reveals a striking disconnect. Adoption of GenAI for legal has grown from 14% to 26% year-over-year, but in-house legal functions' adoption rates continue to lag. Why is that?

A fundamental reason is that, whilst law firms operate with a built-in measurement infrastructure through billable hours, making ROI calculations straightforward, in-house legal teams are different. They typically operate in a measurement vacuum, frequently lacking tangible data to articulate how their internal resources are deployed when assessing internal costs; as contrasted with often knowing their external legal spend down to the invoice line item. This creates a fundamental asymmetry, with budget holders demanding ROI justification but in-house legal functions lacking the baseline data to provide it. The result? A strategic stalemate where innovation and adoption stalls and competitive advantage erodes.

Answering the right questions: What do budget holders want to know?

Consider the typical General Counsel presentation to the executive committee requesting AI investment. It likely focuses on potential capabilities - document review automation, document summarisation, contract analysis, legal research enhancement - because that's what vendors showcase, peers discuss at conferences and what TR's Report shows as the most frequent use cases.

But budget holders are asking different questions:

  • What percentage of your team's effort is currently spent on those activities and what does that cost is?
  • Which of those activities represents the highest-cost, lowest-value work and what would we save if we approached them differently?
  • How will you measure success and demonstrate ROI post-implementation so I know we invested wisely?
  • What's the opportunity cost of not investing and why can’t you just “make do”?

Without baseline data, these questions are almost unanswerable.

Building the data foundation: A practical framework

The most successful General Counsels are flipping the traditional approach. Instead of starting with technology capabilities and working toward business justification, they're beginning with rigorous current-state analysis, gathering baseline data and working toward targeted solutions. This approach transforms the conversation in three fundamental ways:

  1. From aspiration to evidence: Rather than discussing what AI could do, General Counsels are presenting data on what AI must do to address quantifiable inefficiencies and cost concentrations.
  2. From generic to specific: Instead of implementing popular use cases, General Counsels are deploying solutions tailored to their organisation's and function's strategic priorities.
  3. From cost to investment: By establishing baseline data, General Counsels are creating the framework to demonstrate concrete ROI rather than hoping for blanket "productivity gains."

Establishing this baseline data doesn't require a law-firm style time sheet or months of analysis. It requires an honest, systematic assessment of current resource deployment on a percentage of effort basis and it can be done in four easy steps:

Step 1: Activity Mapping Navigation Show below Hide below

Survey how legal team members actually spend their time rather than where you think they do. Focus on broad categories that are likely to lead to a solution or effective use case, such as: legal advice, document review, research, administrative tasks, training, project management, people management and so on. The goal isn't precision but a reliable, proportional understanding of where time is currently spent, illuminating areas of concern and opportunity.

Step 2: Activity Assessment Navigation Show below Hide below

Review the results of the activity mapping exercise to validate if time is being spent on the right activities by the right resources. This can be done by assessing its value, complexity, risk and alignment to the role of your in-house legal function. Activities that are high value and high complexity (e.g. merger negotiations, regulatory strategy, etc.) should consume the majority of senior legal time. Activities that are lower value or more routine (e.g. document location and retrieval, repeat advice generation, policy compliance etc.) should consume less time but often do not, and so represent prime activities around which to develop potential AI use cases.

Step 3: Cost Calculation Navigation Show below Hide below

Apply fully-loaded cost data to activity categories to reveal the true economic impact of resource misallocation. This creates a compelling investment justification by tying team effort to real dollar cost.

Step 4: Opportunity Quantification Navigation Show below Hide below

Identify specific AI opportunities with measurable impact. For example, if analysis reveals that 15% of legal team effort (worth approximately $400,000 annually) is spent answering routine questions and directing people to internal policies, that becomes a concrete problem worth solving.

Making the business case: Numbers that persuade

Armed with this data, the AI investment conversation transforms dramatically. Instead of requesting budget for "productivity tools," you're proposing solutions to quantified business problems.

Consider the contrast between "We need contract analysis software to improve efficiency and reduce risk", which is a typical approach, with a more robust data driven approach of "Our analysis shows we spend $300,000 annually on routine contract review that could be automated. Implementing AI to support this workstream would allow us to redeploy this capacity toward high-value activities while reducing the contract processing time by 60%."

The latter does more than request investment; it demonstrates strategic thinking and establishes the metrics for measuring success.

The path forward: From measurement to transformation

The 95% of legal professionals who expect GenAI to become central to their workflows within five years aren't wrong about the destination but they need to lead the business to get there. The in-house legal functions that prioritise data over technology, need over want, and evidence over aspiration will arrive first and establish positions that become increasingly difficult to challenge.


For General Counsels ready to break through the AI investment deadlock, the opportunity is immediate and the approach is clear: measure first, deploy second, and watch as data transforms both budget conversations and organisational impact. The in-house legal functions that embrace this discipline won't just adopt AI, they'll master it, and in doing so, will redefine their role in driving organisational success.

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