Can AI-Powered LegalTech Challenge the Traditional Law Firm Model?

For decades, access to legal services has largely followed the same model: a client identifies a problem, approaches a law firm, and pays for a lawyer’s time to research, review documents, provide advice or manage a dispute. But as artificial intelligence becomes capable of performing increasingly sophisticated legal tasks, that model is beginning to face a fundamental question: how much of a lawyer’s work actually needs to be done by a lawyer?

For Dmitry Grinik, Founder and CEO of Legaline Platform, the answer lies in understanding where technology performs well — and, perhaps more importantly, where it does not.

“Startups win where the work repeats and the result can be checked,” Grinik says. That includes process automation, sorting and routing tasks, document analysis and many of the smaller functions that occupy a significant portion of a lawyer’s working day. The traditional model, however, remains essential where professional judgement, licensing and accountability are required, particularly in representation, disputes and situations where someone must interpret what the documents do not say.

That distinction is already visible in the performance of legal AI systems. Grinik points to a February 2025 comparison by Vals AI, in which legal AI systems reportedly outperformed lawyers when answering questions about documents, achieving an accuracy rate of 94.8% compared with 70.1%. But when the task shifted to contract redlining, lawyers performed better, at 79.7% versus 65% for AI.

His conclusion is straightforward: “AI wins the answer but loses the result.”

That gap between information and judgement is likely to define the next phase of LegalTech.

For small and medium-sized businesses in particular, the opportunity could be significant. Legal support has historically been difficult for smaller companies to navigate, not simply because of price but because of uncertainty. Businesses may not know what a legal service will ultimately cost, which additional fees are mandatory or whether their problem requires a lawyer at all.

Research cited by Grinik from the Legal Services Board in England and Wales found that 90% of small businesses surveyed considered legal services too expensive. Among businesses that had encountered a legal problem, only a quarter sought professional help, while 44% handled the issue themselves.

For Grinik, that is evidence that demand for legal support is not disappearing. Instead, it is frequently bypassing traditional providers.

The opportunity for LegalTech platforms, therefore, is not simply to make lawyers cheaper. It is to help users understand what level of support they actually need.

A platform may determine that an official government service and a checklist are sufficient for one problem, while another requires a licensed advocate. The challenge is building a system willing to make that distinction even when directing a customer towards self-service means sacrificing revenue.

AI could also begin to change the economics behind legal work itself.

Grinik estimates that automation could reduce the time spent on individual legal operations by roughly 30% of a lawyer’s working hours. But whether clients benefit from those savings depends on the business model surrounding the technology.

If lawyers continue to charge by the hour, greater efficiency can create an uncomfortable contradiction: completing work faster can mean billing less. Fixed pricing for a defined scope, by contrast, allows efficiency gains to translate more directly into lower costs for the client.

That may eventually push the legal industry towards a broader rethink of how professional services are priced.

Yet efficiency alone cannot be the objective. Accuracy, accountability and the limitations of AI remain critical concerns.

Grinik points to the Vals Legal Research Bench from September 2026, where the best-performing model reportedly achieved around 90% under partial-credit scoring but only 55% under strict grading.

For legal work, that distinction matters considerably.

A response that is mostly correct but omits one required element can be more dangerous than an obviously incorrect answer because the user may have no reason to question it. A polished AI response can appear authoritative even when something material is missing.

“The assistant has to show its limits, not just its confidence,” Grinik says.

That is why he argues licensed professionals must continue to own the final result. AI may build the first position, identify relevant documents or surface possible arguments, but testing those conclusions against counterarguments, missing information and professional judgement remains part of the service.

The usefulness of that model becomes particularly clear during periods of economic or geopolitical uncertainty.

When supply chains are disrupted, a shipment fails or a commercial relationship breaks down, businesses often need to understand their legal exposure quickly. Which contracts are affected? What do the notice provisions require? Has a deadline already started running? What dispute-resolution mechanism applies?

The information may be buried inside an agreement signed several years earlier under entirely different circumstances.

AI can dramatically shorten the time required to build that initial picture. It can review contracts alongside correspondence, identify notice requirements, extract deadlines and highlight dispute-resolution provisions before a specialist begins working on the strategic response.

Grinik compares the process to producing an AI-generated article: the foundation may be created quickly, but human expertise is what turns it into something that actually holds up.

The same tension exists in the wider push to democratize legal knowledge.

Generative AI has made legal information easier than ever to access, but access to information is not the same as legal literacy. Grinik defines legal literacy as understanding what to do next, what a system requires, how much different options cost and when a situation has moved beyond self-help.

The risks become particularly visible among users who do not have access to professional support.

Legal researcher Damien Charlotin has documented more than 2,000 court filings containing fabricated AI citations, according to Grinik. Many reportedly came from individuals representing themselves. The users had access to information, but lacked a reliable way to distinguish correct information from invented material.

Performance can also vary significantly by area of law. On the Vals Legal Research Bench cited by Grinik, strict pass rates stood at 13.6% in family law and 23.5% in immigration, compared with 44.5% in health-related legal research.

That leads Grinik to a different vision of AI’s role. Instead of positioning the technology as an oracle that provides definitive answers, LegalTech could use AI as a “sparring partner” — challenging users’ assumptions, presenting the opposing perspective and identifying the facts or documentation that may be missing.

The objective is not for someone to leave a platform believing an AI told them they were right. It is for them to leave with a clearer understanding of their situation and available options.

Traditional law firms are unlikely to disappear from that future. But simply adding AI tools to existing workflows may not be enough to protect the existing business model.

Grinik cites Thomson Reuters’ 2026 research showing a significant difference between firms approaching AI strategically and those adopting it without a broader plan. According to the survey, AI met expectations at 66% of firms with a strategy, compared with 22% of firms without one.

The pressure may increasingly come from clients themselves. In the same research, Grinik says 78% of corporate clients viewed AI-driven improvements as mandatory, yet only 6% believed their providers were currently delivering them. Around a third were reconsidering their law firm relationships.

That could ultimately make pricing one of the most disruptive consequences of AI.

If technology reduces the amount of time required to complete legal work, a system built primarily around hourly billing may become increasingly difficult to justify. Grinik expects greater movement towards outcome-based structures, including fixed fees for clearly defined work and, where regulation allows, success-linked pricing.

For LegalTech entrepreneurs, however, building these platforms is not simply a software challenge.

Regulation comes first.

Legaline Platform, for example, is licensed in the UAE as a portal and AI research consultancy rather than a legal consultancy. Grinik says the platform itself does not provide legal advice. Situations involving a client’s specific legal circumstances must be passed to a licensed advocate who assumes responsibility under their own professional licence.

“Keeping that boundary intact on every screen turned out to be harder than training the model,” he says.

Trust is the second challenge: users need clarity around who is responsible for the service, how their data is protected, which professional holds the relevant licence and what happens if something goes wrong.

The third challenge is technical. Performance differs between AI models and practice areas, meaning there is unlikely to be one model that performs best across every legal task. The competitive advantage may instead lie in how platforms orchestrate different technologies and verify the outputs they produce.

For entrepreneurs in the Middle East, Grinik believes this creates a particularly significant opportunity.

The region combines rapidly growing business activity with a LegalTech ecosystem that remains comparatively underdeveloped. Grinik estimates that while regional directories may list more than a thousand businesses under the LegalTech category across the GCC, many are conventional law firms, translation providers or corporate-service businesses with a digital presence rather than technology-led legal platforms.

Companies demonstrating more advanced uses of AI or building products specifically around local legal systems remain relatively limited.

The difference in investment is equally stark. Grinik puts disclosed venture funding for the regional segment at approximately US$6 million, compared with US$4.6 billion reportedly raised globally by legal technology companies in 2025.

Meanwhile, the potential addressable market is substantial. The UAE alone has more than 1.4 million companies, while mainland Dubai had 3,433 registered legal consultants as of March 2026, according to figures cited by Grinik.

He sees two major gaps still waiting to be addressed.

The first is creating a connected journey that allows a user to understand a rule, identify mandatory costs, complete the relevant procedure and reach a verified legal professional when necessary.

The second is localization. Many platforms remain limited to individual jurisdictions, lack comprehensive Arabic capabilities or struggle when legal questions require information to be reconciled across different legal systems.

For entrepreneurs who can solve those problems, LegalTech could become less about replacing lawyers and more about redesigning how people reach them.

AI may automate a growing share of the work that happens before a lawyer becomes involved. It may make legal information easier to navigate, lower the cost of routine tasks and force firms to reconsider how their services are priced. But when judgement, accountability and professional responsibility matter, the human role is unlikely to disappear.

The real disruption, then, may not be AI replacing the lawyer.

It may be technology changing when a lawyer is needed, what they spend their time doing and what clients are ultimately willing to pay for.