By: Joyce Jia

Pricing reform to replace billable hours has long been debated in the legal industry. Yet as software companies increasingly shift toward outcome-based pricing with AI agents’ assistance—charging only when measurable value is delivered—the legal profession remains anchored in time-based billing and has been slow to translate technological adoption into pricing change. The recently released Thomson Reuters Institute’s 2026 Report on the State of the US Legal Market (“2026 Legal Market Report”) revealed that average law firm spending on technology grew “an astonishing 9.7% … over the already record growth of 2024”, while “a full 90% of all legal dollars still flow through standard hourly rate arrangements,” This growing disconnect between technological investment and monetization reflects not merely a billing challenge, but a deeper crisis in how legal value is defined, allocated, and captured in the AI era. 

How Did We Get Here?

The billable hours system wasn’t always dominant. As documented by Thomson Reuters Institute’s James W. Jones, hourly billing emerged in the 20th century but remained relatively peripheral until the 1970s, when the rapid growth of corporate in-house legal departments demanded standardized fees and greater transparency from outside counsels’ previously “amorphous” billing practices. The logic was straightforward: time equaled work, work equaled measurable productivity, and productivity justified legal spending for in-house departments (and conversely, profitability for law firms).

That logic, however, is increasingly strained. As AI enables what Clio CEO Jack Newton describes as a “structural incompatibility”, the revenue model built on time becomes increasingly unjustifiable. According to Thomas Reuter’s 2025 Legal Department Operations Index, corporate legal departments face mounting pressure to “do more with less.” Nearly three-quarters of respondents plan to deploy advanced technology to automate legal tasks and reduce costs, while one-quarter are expanding their use of alternative fee arrangements (AFAs) to optimize operations and control costs. As the 2026 Legal Market Report observes, general counsels now scrutinize matter budgets line by line. Seeing their own team leverage AI to perform routine work “at a fraction of the cost,” they question why outside counsels charging premium hourly rates are not delivering comparable efficiencies. Unsurprisingly, corporate legal departments have led their outside firms in AI adoption since 2022. 

Is AI a “Margin Eroder or Growth Accelerator”?  

Research by Professor Nancy Rapoport and Legal Decoder founder Joseph Tiano frames this tension as a central paradox of AI adoption. When an attorney completes discovery review using AI in 8 hours instead of 40, firm revenue could drop by 80 percent theoretically under the hourly model even as client outcomes improve. This appears to be a productivity trap: AI-driven efficiency directly cannibalizing revenue. But this framing is overly narrow. With careful design, restructuring billing models around technology-enabled premiums need not shrink revenue; instead, it can enhance productivity while strengthening client trust through greater transparency and efficiency.  It also enables a more equitable sharing of the benefits of technological advancement and a more deliberate allocation of the risks inherent in legal matters.

Recapturing the Lost Value of Legal Inefficiencies

According to the Thomson Reuters Institute’s 2023 research on billing practices, the average law firm partner writes down over 300 hours annually, nearly $190,000 in lost potential fees. These write-offs typically involve learning curves in unfamiliar legal areas, time-intensive research, drafting various documents and meeting notes, or correcting associates’ work. Partners often decline to bill clients for such work when it exceeds anticipated time expectations, even though it remains billable in principle. This is precisely where AI excels. By reducing inefficiencies and accelerating routine tasks, AI allows firms to recapture written-off value while offering clients more predictable budgets and higher-quality outputs. 

Justifying Higher Hourly Rates Through AI-Enhanced Value

Paradoxically, AI may also support higher hourly rates for certain categories of legal work. As Rapoport and Tiano argue, AI enables lawyers to deliver “unprecedented insights” through deeper, more comprehensive, and more reliable analysis. By rapidly synthesizing historical case data, identifying patterns, and predicting outcomes, AI may elevate legal judgment in ways that time and cost constraints previously rendered impractical. In this context, premium rates can remain justifiable for complex, strategic work where human judgment and client relationship prove irreplaceable.

Extending Contingency (Outcome-Based) Fee Beyond Litigation

Beyond traditional litigation contingency fees, Rapoport and Tiano identify “disputes, enforcement actions, or complex transactions” as areas ripe for outcome-based pricing, where firms can “shoulder more risk for greater upside.” The term “disputes” may be understood broadly to encompass arbitration, debt collection, and employment-related conflicts, such as discrimination or wage claims.

An even more underexplored application lies in regulatory compliance, a domain characterized by binary and verifiable outcomes. Unlike litigation success or transactional value, compliance outcomes present even clearer metrics: such as GDPR compliance versus violation, SOX compliance versus deficiency, patent prosecution approval versus rejection. This creates opportunities for compliance-as-a-service models that charge for compliance or certification outcomes rather than hours worked. Where AI enables systematic, scalable review, risk allocation becomes explicit: the firm guarantees compliance, and the client pays a premium above hourly equivalents for that assurance.

New Revenue Streams in the AI Era

The rise of data-driven AI also creates entirely new categories of legal work. As Rapoport and Tiano identify, “AI governance policy and advisories, algorithmic bias audits, data privacy by design”, all represent emerging and durable revenue streams. Moreover, as AI regulatory frameworks continue to evolve across jurisdictions, clients will increasingly seek counsel for these specialized services, where interdisciplinary expertise at the insertion of law and technology, combined with sound professional judgment and strategic foresight, remain indispensable for navigating both compliance obligations and long-term risk. 

The Hybrid Solution: Tiered Value Frameworks

Forward-thinking firms are increasingly experimenting with hybrid AFA that blend fixed fees, subscriptions, outcome-based pricing, and legacy hourly billing into tiered value offerings. Ultimately, the legal industry’s pricing transformation is not solely about technology. It is about candidly sharing the gains created by technology and confronting how risk should be allocated when AI reshapes legal work.

As AI simultaneously frees lawyers’ time and creates new revenue opportunities, law firms face a defining challenge: articulating, quantifying, and operationalizing a value-and-risk allocation framework capable of replacing the billable hour and sustaining the economics of legal practice for the next generation.