Incentives for Lawyers

GAICIL Insights

Pay people for hours and they will give you hours. Incentives for Lawyers, by Ann P.¹ Bartel, Brianna Cardiff-Hicks and Kathryn Shaw, documents an international law firm that discovered this the expensive way. Team leaders poured effort into billable hours and neglected the leadership activities that build the firm. The firm changed its compensation plan to reward leadership more and billable hours less.

The response was large and robust. Team leaders increased their non-billable hours and shifted billable hours to team members. The new plan combined an objective formula with subjective evaluations of leadership. The authors note this type of plan is the fastest-growing compensation system among law firms, regardless of country. Most law firms now base pay on a mix of personal performance in serving clients, generating new business and managing the firm.

The general lesson, in the conclusion's words, is that firms must solve the multitasking problem when designing compensation: if rewards for individual performance omit important contributions, employees will not allocate time to those tasks. Adjusting incentives redirected effort toward neglected but valuable work, and quickly.

Now add artificial intelligence and the billable hour becomes a trap with a timer. AI is transforming professional services, including law. Document review and research that once consumed billable hours can increasingly be done faster with AI. If pay stays tied to billable hours, professionals have weak incentives to adopt tools that cut the hours they bill, even when those tools serve clients better. The multitasking problem expands to technology adoption: a reward system that omits productivity improvement quietly discourages it. The hourly model pays a lawyer to ignore the best tool on the desk.

The firm in the study points to the escape route. Compensation that rewards contributions beyond billable hours, leadership, client development, firm-building, aligns individual incentives with the firm's long-run health. In an AI-transformed profession, firm-building could include designing new service models, training teams on AI tools and investing in knowledge systems. Plans that blend objective measures with subjective evaluations can capture such contributions, which are hard to count but valuable.

The reallocation inside teams is a preview. When leaders spent more time leading, team members took on more billable work, improving the division of labor. AI may enable further shifts as routine tasks move to machines and team members take on more complex work. Compensation design will determine whether those shifts happen smoothly or meet resistance from people whose pay depends on the old arrangement.

There is a measurement trap worth flagging. Objective formulas reward what can be counted. Subjective evaluations reward what matters but resists counting. As AI makes work easier to track, firms may be tempted to lean harder on formulas. The multitasking problem warns against it: metrics capturing only measurable output will pull effort away from mentoring, collaboration and innovation. More precise measurement can produce worse incentives if it measures the wrong things precisely.

Policy has a role. Billing rules, fee structures and performance metrics in regulated professions and public organizations shape whether professionals adopt productivity-enhancing technology. Fee arrangements rewarding outcomes or value delivered, alongside time spent, align incentives with innovation. Regulators can help by removing rules that entrench hourly billing. A legal market priced by the hour is, in effect, a market that taxes efficiency.

The broader message: organizations get what they pay for. Pay for billable hours and get billable hours. Pay for leadership and firm-building and get investment in the firm. In an era when AI is reshaping professional work, compensation that rewards the full range of valuable contributions, including adopting better tools, will help firms and clients capture the gains from innovation.

The firm studied here offers the encouraging coda. Change was feasible, and people responded fast when incentives shifted. The AI transition in the professions may hinge on the pay plan.