The legal industry has debated alternatives to hourly billing for decades, but greater transparency into how legal work is performed is accelerating the need for change.
Artificial intelligence has compressed the time it takes to produce legal work. Clients can now see the gap between effort and invoice, not merely suspect it. When a client knows a first draft took twelve minutes, an invoice reflecting six hours of work stops being a math question. It becomes a trust problem. The firms still pricing strictly by the hour are the ones most exposed to that scrutiny, whether they realize it yet or not.
Two legal industry leaders who view this shift from different sides of the table, Gwen Griggs of ADVOS and Nancy Jeng of Billables AI, were recently asked the same question during a live conversation hosted on Law.com. Firms know they need to change how they price their work. So, why do so few do it?
Their answers point to the same root cause, approached from two different directions.
Griggs has spent years helping firm owners move away from the billable hour. She says many firms treat the shift like a leap instead of an experiment. A firm sets a fixed fee. The matter grows beyond its original scope. The lawyer absorbs the difference. The firm concludes the entire model does not work and never returns to the idea.
Jeng works with firms on the operational side of pricing reform. She sees a different point of breakdown: firms try to offer alternative fee arrangements before they have the cost data to support them. Their billing systems were designed to record hours, not reveal true cost. Without that visibility, firms cannot confidently price work outside the hour because they do not know what it costs to deliver. Write-offs accumulate quietly. Attorneys under-record time on difficult matters and over-record on easier ones, and the resulting data distorts every pricing decision built on top of it. Firms end up pricing on instinct rather than insight.
Firms that examine their own numbers have proven to successfully move past the traditional billable hour structure. Firms that reverse it, changing the pricing model before confirming what the underlying data shows, tend to repeat the same pattern Griggs describes.
That gap shows up in two places consistently: in how firms understand their own data, and in how they attempt to change pricing. What follows are the two exercises Griggs and Jeng each recommend as the place to start. The first looks backward at data the firm has. The second looks forward at a single, contained way to test something new. Neither requires a firmwide overhaul, new software, or a committee.
Start With Data You Already Have
Before a firm changes how it prices anything, Jeng recommends starting somewhere most firms overlook: the data already sitting in their billing system.
Most firms review billing performance by attorney. It is the default report, and it answers a fair question: who is busy and who is not. But it does not answer the question that determines whether a new pricing model will work, which is whether specific types of work are profitable once every cost of delivering it is accounted for. Attorney-level reporting rewards speed and volume. Matter-level reporting reveals where profitability actually exists, and where it quietly does not.
Pull the last 90 days of billing data and rebuild the view by matter type instead of by attorney. Three things are worth examining specifically once that view exists.
- Realization rate by matter type. Some categories of work consistently bill closer to full value than others. That difference matters because it shows where a fixed fee or AFA would be safe to offer, and where it would not.
- Write-off patterns. Write-offs rarely happen at random. They concentrate around specific matter types, specific stages of a matter, or specific client relationships. Once the pattern becomes visible, it becomes addressable instead of accepted as the cost of doing business.
- Matter profitability on paper vs. reality. A matter can appear successful by every visible measure while the attorney working on it absorbs hours that were never recorded. The number that looks healthiest may be the one hiding the most risk.
This exercise has become more important as AI changes how legal work gets produced. AI-assisted work generates a level of effort data firms have never had access to before. Firms with clean, structured billing data are positioned to use that information with confidence as that shift accelerates. Firms without it will be pricing in the dark, regardless of how advanced their AI tools become.
If a firm cannot pull this information in a few minutes, that absence is itself the answer.
Nancy Jeng, Billables AI
EXERCISE 1 — HERE IS WHERE TO START
Pull your last 90 days of billing data. Sort it by matter type, not by attorney. Identify the two or three matter types with the lowest realization rate. That list is where your next pricing conversation should start.
Test Pricing Without Risking the Firm
For many firms the obstacle was never analysis in the first place. Griggs sees this constantly. Firm owners understand the case for alternative pricing intellectually, then stall because the only version of the idea they can picture is an all-or-nothing rollout across the entire practice, or they tried an experiment based on limited data, it didn’t go well, so they resist trying again.
Her advice runs in the opposite direction. Treat the shift as a contained experiment with one client, not a transformation of the whole firm.
Name one client. The relationship should be strong, the work should be repeatable, and the engagement should already be profitable under the current model. That client becomes the test case, not a referendum on the entire practice.
Narrowly define the experiment. One matter type. One fee structure. One quarter. Decide in advance what success will look like, so the firm is not left interpreting the result after the fact when the temptation to call any outcome a failure is strongest.
The firms that succeed at this transition are not the ones with the most complete plan. They are the ones willing to be a little wrong on price for a single quarter in exchange for learning. Griggs has watched firms abandon alternative pricing entirely after one imperfect attempt, treating a single data point as a verdict on the whole idea. She has also watched firms run the same experiment, adjust, and run it again, each time with a clearer picture of what their work is worth and how to price it with confidence the next time.
No new pricing model survives first contact with a client. That is not a flaw. It is the only way the model improves.
Gwen Griggs, ADVOS
EXERCISE 2 — HERE IS WHERE TO START
Name one client and one matter type where you would be willing to test a fixed fee or alternative arrangement for one quarter. Write down, in one sentence, what result would tell you it worked. Bring that to your next partner or practice group conversation. The goal is not to get it right. The goal is to learn something you can price better next time.
Gwen Griggs is the co-founder of ADVOS, where she helps law firm owners move from hourly billing to value-based pricing models. Nancy Jeng is the co-founder of Billables AI, where she helps firms capture accurate effort data at scale.
