For most businesses, completing the same work in half the time is an obvious advantage.
For a profession that has traditionally sold time, the calculation is less straightforward.
Consider three law firms using the same AI tools. Each can review documents faster, test legal propositions sooner and manage more information with fewer manual steps.
The first charges by the hour. The second works on contingency. The third receives part of its ordinary fees and places the balance at risk against a successful outcome.
The technology is the same. The productivity gain is the same. The economics are not.
The tension is already visible. Thomson Reuters reported that lawyers expected AI to release roughly 190 working hours a year. In the United States, guidance from the American Bar Association also makes the basic hourly-billing position clear: where AI reduces the time actually spent, a lawyer cannot bill for time that was not worked. The detail will differ by jurisdiction, but the question travels easily: when legal work takes less time, who keeps the gain?
The hourly firm may finish sooner and send a smaller bill. It can use the released capacity to take on more matters or move its lawyers towards the parts of the mandate where judgment matters most. That works if the additional demand exists and if clients continue to distinguish between the value of the work and the time required to produce it.
The contingency firm experiences the same efficiency differently. Its return does not fall automatically because the case takes fewer hours. If it rejects weak matters earlier and runs viable ones at lower cost, it is initially better placed to retain the benefit.
The hybrid firm sits between them. Current fees keep the legal team functioning, while a contingent component connects part of its remuneration to the result.
For litigation funders and legal-risk insurers, those differences affect more than the legal budget. They affect how the underlying risk should be priced and shared.
None of these models is new. Between full hourly billing and full contingency sit reduced rates, deferred fees, fixed fees, success uplifts and arrangements in which disbursements are funded while part of the legal team’s remuneration remains at risk.
AI has not created this spectrum. It is making the differences along it harder to ignore.
Litigation funding brings them into sharper focus because a funder approaches a case as both a legal matter and an investment. It is not enough to ask whether the claim can succeed. The economics must survive delay, an appeal, reduced damages, an enforcement problem or a complete loss.
A funder may therefore prefer the lawyers to have some connection to the outcome, much as an investor often prefers management to share in the performance of a business. The analogy is limited by professional duties and the need to preserve independent legal judgment, but the question of incentives remains legitimate.
The objective is not to starve the legal team of cash. A firm that cannot retain the right people, brief suitable counsel or sustain the matter becomes an execution risk of its own. No sensible funder wants the lawyers to run out of fuel.
The real question is how to keep them properly resourced while leaving enough of their economics connected to cost, duration and result.
A firm may place all its fees at risk and fund the disbursements itself. It may risk its fees while a funder covers external costs. It may receive a reduced current fee and earn an uplift if the matter succeeds. A client may instead pay everything in full because it has the capital and prefers to retain the upside.
The billable hour will not disappear. Some work cannot sensibly be priced against a recovery, and some clients prefer to carry the risk themselves. The strongest attorneys, advocates and barristers may also continue to command premium economics because clients are buying judgment, credibility and a history of performing when the stakes are high.
They are, in a sense, seeded.
The position reflects what has already been demonstrated, not a guarantee of the next result. That value may appear through an hourly rate, a fixed fee or a premium for strategic responsibility. AI may increase the value attributed to scarce judgment without preserving every existing method of charging for it.
The more difficult question concerns the broad middle of the market.
As technology makes legal work faster and easier to compare, firms without a specialist advantage or established record may find it harder to rely on conventional hourly pricing alone. Some will adopt fixed fees, capped budgets or technology-enabled volume work. Others will accept contingent components.
Different areas of law will evolve differently. But claimant litigation presents a clear question: if the outcome is financial and other participants are carrying capital or loss risk, how much of the legal team’s remuneration should remain disconnected from it?
For some firms, sharing risk will be an opportunity rather than a concession. A firm that can select strong matters, control cost and manage a portfolio may conclude that the hourly model limits its economics. It may prefer to participate in the value created rather than charge only for the time required to create it.
That firm is not accepting contingency because it lacks bargaining power. It is doing so because it believes its judgment is worth more than its hourly rate.
But contingency is not simply another way of issuing an invoice. It changes the nature of the business.
Regular payment supports stability and the ability to retain strong people. Contingency requires patience and a willingness to work without knowing when, or whether, the reward will arrive. It can sharpen selection, but also make it harder to abandon a matter once time, reputation and capital have been committed.
The firms most likely to adapt may not be those assuming the greatest risk, but those best able to price it and change course when the evidence requires it.
A firm placing fees at risk must decide which cases deserve its time, how much exposure it can carry, how long it can wait for revenue and how many unsuccessful matters its winners must support.
It begins to underwrite.
AI may improve that underwriting. It may also weaken it.
A firm can screen more claims, review more documents and commence more matters without a proportional increase in staff. Courts do not necessarily move faster. Appeals do not disappear. Defendants do not settle merely because the claimant’s lawyers have become more efficient.
Technology can make it easier to begin more litigation without making it easier to turn that litigation into cash.
For a disciplined contingency firm, AI may sharpen selection and reduce avoidable cost. For an undisciplined one, it may build a larger portfolio of badly priced risk.
Litigation funders face the same distinction between speed and judgment.
A funder providing genuinely non-recourse capital may lose the entire investment if the case fails. Yet when the case succeeds, its return is often judged after the uncertainty has disappeared. The original decision can then look obvious and the reward excessive.
It was not obvious when the capital was committed.
The matter could still fail, last longer than expected, require more capital or produce a judgment that proved difficult to enforce. Winning investments must also contribute towards losses and delayed recoveries elsewhere.
That does not justify unlimited returns, control over legal strategy or a structure that leaves the claimant with too little. Funders can misprice duration or protect their downside too aggressively. Caps, tiers and blended structures try to keep returns proportionate to the risk carried: set too high, they may distort the claimant’s recovery; set too low, they may make the capital unavailable.
Insurers of legal risk confront a related problem. They price adverse outcomes before anyone knows whether those outcomes will occur. Hindsight can make the premium look unnecessary, just as it can make funding look expensive after a successful result.
The claimant, lawyers, funder and insurer contribute different things: the legal right, judgment and execution, non-recourse capital, and defined adverse-risk protection. They need not carry identical risk.
Economic exposure can support alignment, but it does not create it on its own. A contingent interest may encourage cost control while also creating pressure to settle early. A funder may take a different view on timing. Governance, professional duties and control over key decisions remain essential.
A sustainable structure keeps each participant economically engaged and able to perform. The claimant must retain a recovery worth pursuing, the legal team enough cash flow to conduct the case properly, and the funder and insurer a credible return proportionate to risk.
When that balance is right, the parties are willing to do business together again. When it is not, the transaction may still produce a winner, but rarely a durable relationship.
AI enters this environment as an accelerant, although not only in one direction.
It may narrow some gaps by giving smaller firms access to research and production capabilities that once required larger teams. But access to the same tool does not create equal judgment. Better operators may use AI to test assumptions and reject weaker cases; others may use it to process weak matters faster or confirm conclusions they already prefer. AI can assist discipline. It cannot impose it.
That distinction matters most where time or capital is at risk. A firm or funder must live with its earlier decision for as long as the matter remains unresolved. Its ability to recognise a weakening case, revise expectations and stop committing good resources after bad ones may become as important as its ability to identify a strong case at the outset.
The legal market is often described through the idea that a rising tide lifts all boats. AI may not behave like that kind of tide. Its capabilities will become widely available, but the benefits will not be evenly distributed. Better decisions can attract stronger matters, people and capital. Weak selection and poorly aligned economics can compound just as quickly in the opposite direction.
AI is unlikely to kill the billable hour. It may increase the value of the strongest practitioners, although that value will not always be charged by the hour. It may also persuade the strongest risk-sharing firms that selling time understates the value of their judgment.
Between them will be much of the profession deciding whether it is best equipped to sell time, assume risk or combine the two.
AI will make the work faster.
Its more important effect may be to reveal, much sooner, who can turn better tools into better judgment, and who cannot.
At Wild Dog, we work at the intersection of litigation funding, ATE insurance and structured capital, helping attorneys and their clients assess, structure and finance legal claims with a clear path to recovery.
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