Law Firm AI Profitability: Why Firms Struggle to Make Money From AI
Law firms are spending enormous amounts of money on artificial intelligence. They're purchasing software, hiring technical specialists, developing internal systems and investing in infrastructure that would have been difficult to imagine just a few years ago.
But there's a question that many firms are still struggling to answer: Is any of this actually making them more profitable?
An October 2026 report from The American Lawyer examined the difficulty large law firms are having translating their AI investments into consistent financial returns. Despite the efficiencies these technologies can create, the financial benefits have been harder to capture.
Law firm AI profitability is an issue that goes well beyond the cost of purchasing software.
AI is changing how quickly legal work can be completed, how firms staff matters, what clients expect and potentially how legal services are priced. For a profession that has historically relied heavily on billing for attorney time, those changes create some difficult business questions.
And as AI becomes more deeply integrated into legal practice, firms will need to start answering them.
Law Firms Are Investing Heavily in AI
The legal industry has moved well beyond experimenting with ChatGPT and other general-purpose AI tools.
Major law firms are developing their own AI strategies, entering partnerships with technology companies and incorporating AI into research, drafting, due diligence, contract review and other legal work.
Some are making particularly significant investments.
Kirkland & Ellis has discussed plans to spend approximately $500 million on AI over several years. Latham & Watkins has invested in Nvidia computing infrastructure to support its own AI development and customization efforts.
We recently examined Latham's approach in Why Law Firms Are Starting to Build Their Own AI Infrastructure.
These investments reflect how seriously large firms are taking the technology. They also introduce substantial costs that firms ultimately need to justify.
Purchasing an AI platform is relatively straightforward. Determining whether that platform is improving the firm's financial performance is considerably more complicated.
Why AI Efficiency Doesn't Automatically Mean Higher Profits
Consider a contract review assignment that would ordinarily require ten hours of attorney time.
With AI assistance, the same assignment might take six hours, including attorney review and verification.
From an operational standpoint, that's a meaningful improvement. The firm has reduced the time required to complete the work by 40 percent.
But what happens to the firm's revenue?
If the client is billed hourly, the firm may now bill six hours instead of ten. Assuming the same hourly rate, the client receives the benefit of the efficiency while the firm collects less revenue for that particular assignment.
The firm may be able to use the additional four hours for other billable work, but that depends on whether the demand exists and whether the attorneys can be redeployed productively.
If the client is paying a fixed fee, the economics look different.
The firm can potentially complete the same work with fewer resources while collecting the agreed fee, improving the margin on that matter.
Neither arrangement is inherently better in every situation. The point is that AI-driven efficiency and law firm profitability are not necessarily the same thing.
Firms need to understand how improvements in productivity affect revenue, costs, capacity and pricing.
Otherwise, they may end up completing legal work faster without realizing much of the financial benefit.
The Billable Hour Creates a Complicated Incentive
The billable hour has been a central feature of law firm economics for decades.
Attorneys record their time, clients are charged for that time, and the firm's revenue is closely connected to the number of hours billed and collected.
AI complicates that relationship.
If technology allows an attorney to complete a task in half the time, billing twice as many hours for that work is not a legitimate solution. The time recorded must reflect the work actually performed, and fees must remain reasonable under applicable professional obligations.
That leaves firms with an important business challenge: How do they benefit financially from technology that reduces the time required to perform services traditionally billed by the hour?
One possibility is increased capacity. Attorneys may be able to handle more matters, serve additional clients or devote more time to complex work that requires professional judgment.
Another possibility is changing the way certain services are priced.
Flat fees, phased fees, subscription arrangements and other alternative fee structures can allow firms and clients to share the benefits of improved efficiency.
But those models require firms to understand their costs and the value of the services they're providing.
Simply introducing AI into an existing hourly billing structure doesn't resolve those issues.
Clients Are Starting to Expect More
Law firms are also facing growing pressure from clients who understand that AI can make certain legal tasks faster and less expensive.
Thomson Reuters' 2026 Future of Professionals Legal Report found that 71 percent of surveyed in-house legal professionals expect their outside law firms to change their commercial models as AI use increases.
Only 28 percent of surveyed law firms reported making pricing changes in response to AI.
The same research found that 77 percent of clients consider AI-enabled improvements in quality very important or essential, while just 5 percent believe most or all of their outside providers are delivering those improvements.
Those numbers illustrate the gap between what clients expect and what law firms are currently providing.
Corporate legal departments are dealing with their own budget pressures. If outside counsel can complete work more efficiently, clients will naturally want to understand how those improvements affect cost, turnaround time and service quality.
That doesn't necessarily mean every client expects lower legal fees.
Some may place greater value on faster responses, more comprehensive analysis, better risk identification or improved access to legal services. But firms should expect more questions about how they're using AI and what value clients are receiving from it.
Law Firms Need to Measure AI ROI Against Actual Legal Work
One of the problems with evaluating Legal AI is that firms sometimes focus on what the technology can do rather than what it accomplishes in practice.
A demonstration showing that AI can summarize a 100-page agreement in seconds may be impressive.
But that demonstration doesn't establish whether the tool saves an attorney meaningful time once the output has been reviewed, corrected and incorporated into the actual work product.
The same issue applies to legal research, due diligence and contract drafting.
A system might generate an initial answer quickly but require substantial attorney review. It might perform well on straightforward assignments while struggling with complicated factual records or unusual legal issues.
The relevant measurement is the complete workflow.
How much time did the assignment require before AI was introduced? How much time does it require now, including review and correction? Has the quality improved? Are errors being reduced? Is the firm completing more work with the same resources?
And ultimately, is the investment improving the economics of delivering legal services?
We discussed some of these considerations in How Law Firms Should Evaluate AI Tools Before Buying Them.
As firms move from testing AI products to making larger investments, those measurements become increasingly important.
AI May Require Firms to Redesign Their Workflows
Another challenge is that many firms are introducing AI into processes that were designed around traditional staffing models.
A document comes in, a junior attorney reviews it, a senior attorney checks the analysis, revisions are made and the final work product is delivered.
AI might accelerate one or two steps without changing the rest of the process.
That can still create value, but it may leave much of the technology's potential unrealized.
A more substantial improvement could require the firm to reconsider how the entire assignment is handled.
For example, an AI-assisted due diligence process might involve organizing documents, extracting relevant provisions, identifying exceptions and preparing preliminary reports before an attorney begins substantive review.
The attorney would still be responsible for evaluating the results and exercising legal judgment, but the allocation of work could change considerably.
This is one reason agentic AI has attracted attention.
As we discussed in What Is Agentic AI? What Lawyers and Law Firms Need to Know, agentic systems can potentially connect individual tasks into broader workflows.
That creates opportunities for efficiency, but it also introduces additional requirements for supervision, permissions, escalation and accountability.
Firms cannot evaluate these systems solely by measuring how quickly the underlying model produces an answer.
They need to understand how the entire process performs.
The Cost of AI Goes Beyond Software Subscriptions
The subscription price of an AI platform is only one part of the investment.
Firms may also need to spend money on implementation, integration, employee training, data security, technical support and ongoing evaluation.
Some will hire specialists to manage AI adoption or build internal tools.
Others may need to modify document management systems, develop internal policies or establish new procedures for handling confidential information.
These expenses can be particularly difficult for smaller and midsize firms to absorb.
A large firm may have the resources to experiment with several technologies before identifying which ones deliver meaningful value.
A smaller practice may need a much clearer business case before making the same investment.
That doesn't mean smaller firms are necessarily at a disadvantage.
They may be able to adopt targeted tools more quickly, avoid expensive infrastructure projects and concentrate on specific workflows where the benefits are easier to measure.
The size of the investment matters less than whether the technology solves a real operational problem at a reasonable cost.
More AI Adoption Doesn't Necessarily Mean Better AI Governance
There is another consideration that can affect the financial value of AI: risk.
The 2026 Legal Industry Report from 8am found that 69 percent of surveyed legal professionals were using general-purpose AI tools for work-related tasks, compared with 31 percent in the prior year's report.
At the same time, the research identified significant gaps in formal training and governance.
Thomson Reuters also reported that 34 percent of surveyed law firm professionals were using AI tools their firms had not authorized.
For law firms, unauthorized AI use can create confidentiality, security and compliance concerns.
A technology that saves time but introduces additional exposure may ultimately cost more than it saves.
Firms therefore need appropriate safeguards around client information, output verification, permitted uses and attorney supervision.
Those controls should be incorporated into the workflow rather than treated as an afterthought.
The goal is to capture the benefits of AI while maintaining the professional standards clients expect.
What Does Law Firm AI Profitability Adoption Actually Look Like?
There probably won't be a single business model that works for every law firm.
A litigation practice handling complex, unpredictable matters has different economics from a firm processing large volumes of standardized commercial agreements.
Some firms may benefit most from reducing administrative work and increasing attorney capacity.
Others may find that AI makes fixed-fee services more attractive because they can estimate the cost of completing certain assignments more accurately.
Still others may use AI to improve turnaround times, expand their services or compete for work that previously would have been too expensive to perform.
The important part is connecting the technology to a specific business objective.
If a firm invests in AI to reduce the time required for contract review, it should measure whether that actually happens.
If the goal is to improve profitability, the firm should examine the effect on matter margins, utilization, write-offs, realization and operating costs.
If the goal is better client service, it should evaluate quality, responsiveness and client satisfaction.
These are familiar business considerations. AI simply makes them more important because the technology can change the relationship between the time spent performing legal work and the value delivered.
The Next Challenge for Legal AI
Law firms have spent the past several years learning what AI can do.
The next stage will require them to determine how to make it work financially.
That means moving beyond software demonstrations and adoption statistics to examine the economics of actual legal matters.
A firm can have excellent AI tools and still struggle to generate a return on its investment. It can also make relatively modest investments and achieve meaningful results by applying the technology to the right work.
The firms that succeed will need to understand both the technology and the business model supporting it.
For now, the legal industry has demonstrated that it is willing to spend money on AI.
The harder part is proving that those investments are creating lasting financial value.
Frequently Asked Questions
Why are law firms struggling to make money from AI?
AI can reduce the time required to complete legal work, but that doesn't automatically increase revenue or profitability. Firms using hourly billing may collect fewer fees for tasks completed more quickly, while also incurring software, implementation and training costs.
How can law firms measure AI return on investment?
Firms can compare the cost, time and quality of legal work before and after introducing AI. Useful measurements include attorney review time, cost per task, error rates, turnaround time, matter profitability and client satisfaction.
Will AI replace the billable hour?
AI may encourage greater use of alternative fee arrangements, but it is unlikely to eliminate hourly billing across every area of legal practice. The appropriate pricing structure depends on the type of work, its predictability and the needs of the client.
Can smaller law firms benefit financially from AI?
Yes. Smaller firms may benefit from targeted AI tools that reduce administrative work, accelerate document review or improve legal research. The financial return depends on the cost of the technology and whether it produces measurable improvements.
What are the hidden costs of Legal AI?
Costs can include employee training, implementation, integration, cybersecurity, attorney review, ongoing evaluation, data governance and technical support.
Why are clients pressuring law firms to use AI?
Clients increasingly expect technology to improve the efficiency, quality and cost of legal services. Some corporate legal departments are also reconsidering their relationships with outside firms that cannot demonstrate meaningful AI-enabled improvements.
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Further Reading
The American Lawyer — Profits From AI Remain 'Stubbornly Out of Reach' For Big Law (October 7, 2026)
Thomson Reuters Institute — Future of Professionals: 2026 Legal Report and Turning Law Firm AI Strategies Into Practice: Findings From the 2026 Stand-out Lawyers Survey
District of Columbia Bar — AI Adoption Is Outpacing How Firms Manage It (June 12, 2026)
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About the Author
Cory D. Raines ("Cory Raines") is a Legal AI Consultant and Founder of Raines Legal Group, and PROTIPPZ, where he focuses on legal strategy, emerging technology, AI workflows, and the evolving intersection of law and artificial intelligence.
Posted by Cory D. Raines
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