Summary

At a recent Elite Global 100 CFO Exchange, finance leaders from the world’s top law firms shared how the integration of artificial intelligence is reshaping profitability, pricing, and client relationships. CFOs discussed the difficulty of quantifying efficiency gains, the evolving pressure to adopt fixed-fee pricing, the new client demand for AI transparency, and the growing need to fund rising technology costs.

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Law firm CFOs have entered a defining stage in the modernization of legal operations. The October 2025 Elite Global 100 CFO Exchange addressed AI’s value, cost, and impact on client expectations.

Executives agreed that AI is no longer experimental. It is a core part of how finance teams analyze data, accelerate billing cycles, and respond to client pressure for efficiency. Yet the group also acknowledged a shared challenge: the promise of AI is clear, but proving its financial impact remains complex. The discussion revealed five clear themes shaping law-firm economics in the year ahead.

Measuring AI Efficiency and Real-World Impact

CFOs are united in their desire to move beyond anecdotal evidence of AI’s benefits. They recognize that tools can dramatically reduce time spent on previously manual tasks—but quantifying those savings remains difficult. 

Executives described scenarios in which processes that once took ten hours now take three and a half. Translating that gain into measurable efficiency, however, requires a detailed comparison between old and new workflows. Few firms have built systems to track both sides of that equation.

Another layer of complexity lies in the embedded nature of AI. Many of today’s tools already include machine-learning components, meaning that efficiency occurs inside existing software rather than in standalone applications. As a result, tracking usage is complicated, and true time savings are often hidden.

Several CFOs noted that staff experimentation can also distort results. Junior professionals frequently test prompts or explore AI features out of curiosity, creating early “noise” in efficiency data. Others pointed out that incidental uses—drafting emails, summarizing notes, or producing quick research—add small but meaningful value that is hard to quantify.

For most firms, the next step is building measurement discipline: process mapping, before-and-after timing, and consistent reporting that can translate AI use into financial outcomes. Until then, AI’s efficiency story will remain largely qualitative. 

The Evolution of Pricing Models

As automation shortens work cycles, firms are confronting the implications for the billable hour. CFOs acknowledged that AI is accelerating long-standing conversations about value-based pricing. 

Several participants explained the economic tension. If a matter that once required $100 of labor now costs $60 because of AI, clients expect part of that savings. Fixed-fee models could provide balance, allowing firms to charge, for instance, $80—passing value to the client while preserving margin. 

But timing matters. Executives stressed that the shift to fixed fees must occur before efficiencies are fully realized. Once clients perceive that AI is embedded, they will inevitably expect lower rates. Others cautioned that data readiness is a barrier: firms often lack the “budgeted hours” baseline needed to calculate value-based pricing accurately.

Some CFOs noted that existing fixed-fee and retainer arrangements are already creating new pressure. Clients assume that efficiency gains are immediate and reduce fees annually, requiring firms to maintain productivity improvements simply to hold revenue steady.

Despite recurring predictions of the billable hour’s demise, most finance leaders expect a gradual evolution rather than a sharp break. Still, AI is forcing firms to align internal cost savings with external pricing logic—a financial challenge that will only intensify.

Rising Client Expectations and AI Transparency

Another major theme was the rapid shift in client attitudes. What began as strict prohibitions on AI has become a demand for disclosure. Many outside-counsel guidelines that once forbade AI use now require firms to explain exactly how AI supports their work and to demonstrate the resulting savings.

CFOs attributed this change to a broader corporate trend: companies everywhere are adopting AI to drive efficiency, and legal departments are following suit. Legal spend is increasingly viewed as a cost center subject to measurable improvement.

Participants described receiving new RFPs that explicitly request details about AI utilization, expected efficiency gains, and how those gains are built into next-year rate structures. Some firms have hired AI experts to focus on practice-level metrics—documenting average time savings across similar matters rather than tracking each case individually.

However, the group agreed that connecting AI usage directly to client matters remains a critical gap. Few firms can yet answer client questions with data-driven evidence. Establishing standardized measurement and disclosure processes will be essential to meet this new expectation of transparency.

Strategic Internal Application of AI

While external reporting dominates headlines, CFOs also highlighted how AI is transforming internal operations. Firms are deploying AI across finance, HR, and project-management functions to improve speed, accuracy, and decision-making.

Examples included using customized large-language models to perform deep research, automate data entry, and generate multi-step reports. One firm described using AI to compare job descriptions and resumes to suggest interview questions, streamlining hiring. Another used AI to analyze a year’s worth of project data to identify risk factors and improve planning.

These operational improvements may appear small individually, but collectively they free staff from repetitive work and create measurable cultural change. By showcasing successful internal use cases, CFOs said, firms can encourage broader adoption and help employees view AI as a productivity tool rather than a threat to traditional roles.

Managing the Rising Cost of Technology

Even as firms celebrate early wins, CFOs are preparing for a new cost reality. The first wave of enterprise AI agreements was relatively inexpensive, but most expect substantial price increases during renewal cycles. Vendors, fueled by large investment rounds, will likely raise fees for access, compute power, and usage volume.

For finance leaders, this means confronting an emerging paradox: AI creates efficiency, but it also introduces recurring expense. Some CFOs framed this as a “cost of doing business” that must be managed strategically.

Potential solutions were debated. One option is to introduce a modest technology fee—typically three to five percent—on client invoices, mirroring practices common in accounting and consulting. Others argued for embedding technology costs into value-based pricing structures to avoid client pushback over line-item surcharges.

A cautionary example came from outside the legal sector: an accounting firm that held its base rate steady but added a seven-percent technology fee, effectively increasing total cost. CFOs acknowledged that similar strategies may eventually surface in law but agreed that transparent communication will be critical.

Ultimately, AI is reshaping both sides of the balance sheet—lowering operational costs while increasing infrastructure investment. The firms that thrive will be those that manage this dual dynamic effectively.  

Conclusion

The October 2025 Elite Global 100 CFO Exchange revealed a financial profession in transition. CFOs are now at the center of law-firm innovation, tasked with proving AI’s efficiency, rethinking pricing, and sustaining profitability under new economic pressures.

The conversation underscored that AI’s value is not self-evident—it must be measured, modeled, and communicated. Finance leaders are building the frameworks to capture that data and convert it into actionable insight. 

In the coming year, success will depend on three imperatives: measure what AI changes, align pricing with delivered value, and plan proactively for escalating technology costs. The firms that master these disciplines will define the financial model of modern legal practice.  

FAQs

Q: Why is measuring AI efficiency so challenging for law firms?

A: AI is often embedded in existing tools, making its impact hard to isolate. Firms must compare historical and current workflows to calculate real savings.

Q: How is AI influencing law-firm pricing models?

A: As automation shortens work cycles, CFOs are exploring fixed-fee and value-based structures that reflect efficiency gains while preserving margins.

Q: What do clients expect regarding AI transparency?

A: Many now require firms to disclose how AI is used and to demonstrate measurable efficiencies in rate structures and RFP responses.

Q: How are firms using AI internally?

A: Common applications include financial reporting, HR automation, research, and project-risk analysis—all aimed at improving speed and consistency.

Q: How are rising AI costs being managed?

A: CFOs are weighing technology fees, vendor-negotiation strategies, and integrated pricing models to offset the increasing cost of enterprise AI tools.

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