Bill(AI)ble Hour

At ILTACON 2025, the perennial billable hour debate got a new spark: generative AI. Several sessions brought together divergent perspectives on whether alternative fee arrangements (AFAs), combined with AI-enabled efficiency, could finally shift the legal industry away from time-based billing, or whether the billable hour will remain the resilient backbone of law firm economics.

The Enduring Billable Hour

Despite decades of debate, the billable hour remains the dominant pricing model. Its persistence reflects how deeply it is woven into law firm economics, talent recruitment, and compensation structures. Even when firms experiment with AFAs, the underlying calculations often trace back to hours, making the billable hour a resilient benchmark.

Supporters of time-based billing point to its simplicity and predictability from the firm’s perspective. They also highlight the challenges inherent in AFAs: the significant overhead of scoping work, the inevitable inaccuracies in forecasting, and the client friction caused by scope changes.

Shifting the Value Equation

Yet AFAs may gain traction as clients look for predictability, shared risk, and outcomes-driven engagements. Fans of AFAs highlighted: clients don’t hire lawyers for the time something takes—they hire results. Rather than measuring value in hours worked, some firms are beginning to scope matters around business impact, desired results, and the technology that will help achieve them. Fee holdbacks, milestone bonuses, and phased reviews are being used to align law firm incentives with client priorities.

This shift places technology, particularly AI, at the center of the conversation. Efficiency gains, better matter management, and the ability to redeploy talent toward higher-value work are becoming part of the value proposition. For many firms, marketing innovation and efficiency are becoming as crucial as marketing expertise.

AI as a Catalyst — and a Test

Generative AI is accelerating the pressure to rethink pricing. Clients increasingly expect firms to adopt technology that improves outcomes and reduces costs. For some, this means AI is a cost-cutting tool; for others, it’s a capability builder that allows for more complex, higher-quality work at competitive prices.

The emerging trend is a hybrid expectation: clients want exceptional results, delivered efficiently, with transparency around whether technology has reduced the cost of delivery. This opens the door for AFAs that reflect both quality and efficiency, but it also challenges firms to articulate and quantify the value AI adds.

Talent and Training Implications

How work is priced has a direct impact on how junior lawyers are trained. Under billable-hour models, clients effectively fund on-the-job learning. Under AFAs, the incentive shifts toward assigning work to the most efficient resource, which can limit training opportunities unless firms deliberately design around it.

AI adds another layer: automating some of the work traditionally handled by junior lawyers, but also creating opportunities for them to develop skills in technology-enabled practice. Firms that integrate training into tech-driven workflows may be better positioned to create future-ready talent.

Revenue Models and Innovation

Underlying these debates is the question of whether current law firm revenue structures enable or inhibit innovation. Some see traditional compensation systems as a barrier, prioritizing hours and utilization over transformation. Others believe the competition for clients incentivizes innovation, as firms must demonstrate value to retain and grow relationships.

What’s clear is that AI is joining pricing as a strategic lever in client conversations. Whether the result is incremental change or a complete rethinking of business models will depend on how quickly firms adapt culturally, operationally, and economically.

The Road Ahead

The intersection of AFAs, the billable hour, and AI isn’t a binary choice; it’s a spectrum. In the near term, expect to see more hybrid approaches where time-based billing incorporates outcome-based elements, and where AI-driven efficiency becomes part of competitive positioning.

Long term, the firms that thrive will be those that align pricing models, technology strategy, and talent development around a clear definition of client value.