It’s early 2027. Most law firms and in-house legal departments are rapidly moving to OpenAI Legal which launched in the third quarter of 2026. Most of them cite cost since OpenAI Legal is still just $20 per month. They are also confident that OpenAI has addressed privacy and confidentiality concerns, and that its new automatic cite-checking ability can accurately verify all outputs. What’s remarkable about the shift is not so much that it happened but the speed at which the transition was made.
This Is Commoditization
The above hypothetical is what happens when a product becomes commoditized, which happens often. A commoditized product is one that has become so commonplace and interchangeable that it loses its uniqueness.
And when that happens, it also loses its pricing power.
Why? Once commoditization occurs, users see little meaningful difference between the various vendor options other than price. So, sellers can’t charge a premium for what they provide, particularly when the lower cost option provides roughly the same features, quality, and performance.
Some examples include things like economy seats on airlines: most customers shop based on price and the difference in service is relatively small. Another example is cloud storage which is now an expected feature — providers are interchangeable, and the market is price-driven.
Commoditization shows up in legal tech if tools that once felt novel become expected infrastructure. At that point, lawyers stop asking “what does this do?” and start asking “why does this cost more than the other one?” If it happens to GenAI, it will have direct impact on legal tech vendors whose products are based on GenAI. And their customers.
Indeed, a pretty big tech player may be betting that this may soon happen with GenAI. As Chance Miller noted in a recent episode of the daily 9to5 Daily, citing a report in The Information by Aaron Tilley, the potential for commoditization may be why Apple is proceeding cautiously with developing its own GenAI tools and it could foreshadow what may happen in legal. Tilley says (emphasis added):
Apple still has a team working on its own internal models that it could take advantage of in the future. But some Apple leaders hold the view that large language models will become commodities in the years to come and that spending a fortune now on its own models doesn’t make sense.
Here’s what Miller concludes: “If Apple leadership truly does believe LLMs will become commodities, then the company’s AI success will depend less on bespoke new models, and more on its ability to control the hardware, software, and services that AI runs on.”
Commoditization of Legal GenAI
Thus far, legal GenAI vendors have faced little competition from outside the legal community. But what would happen if, say, OpenAI decided to target the legal market and release general tools offering the strong privacy protections, enhanced accuracy, and stronger security lawyers and legal professionals crave?
If this were to occur, other players like Google, Anthropic, and Perplexity might follow. The greater market power of these companies could shift the legal GenAI market towards commoditization, where price becomes the primarily criterion.
It was just this kind of thing I mentioned in my post about a Business Insider interview of the founders of Harvey, Winston Weinberg and Gabe Pereyra, back in October.
At that point I noted their statements to the effect that they were less concerned about legal tech vendors and more about competition from OpenAI itself. Somewhat candidly, they admit that OpenAI could enter the legal tech space directly and cut out the middleman legal tech vendors.
These statements prompted me to observe: “[Weinberg and Pereyra] admit that OpenAI could enter the legal tech space directly and cut out the middleman legal tech vendors. Moreover, even if OpenAI never targets the legal field directly, it very well could release general tools offering the strong privacy protections, enhanced accuracy, and stronger security lawyers and legal professionals crave. In fact, OpenAI recently mentioned a contract review tool it developed and is using internally.”
Today’s Legal AI Marketplace
Today, there is a plethora of vendors offering all sorts of GenAI tools at a fairly high price. Their argument is that legal is a specialized market due to a) the ethical and privacy concerns and b) the need for accuracy. They go on to say that only they can offer the protections the specialized market requires and that open or public systems like ChatGPT, Gemini, Perplexity, or Claude simply can’t meet legal demands. Some even go so far as to say it’s malpractice to use the open systems.
And when it comes to legal research, vendors explain that only they have the data to make the systems work accurately and that this moat protects them. But the moat is not foolproof. The vendor argument ignores that the moat-protected legal research is only part of overall legal needs. Moreover, much of the data also exists within client databases that are not protected. More importantly, big players like Google and OpenAI or any of the other large players could simply license or acquire the data themselves, spreading those costs across far more customers while still undercutting specialized vendors on price.
Also, ignoring for the moment that their GenAI tools are also capable of making mistakes and making stuff up, a characteristic of LLMs that is intractable, legal tech vendors assume that just because the open systems haven’t made the case that their products can meet legal’s requirements, they won’t. Indeed, many of the vendor products depend in part on those open systems’ platforms to make their products function. And OpenAI at least is an investor in legal vendors like Harvey.
And as far as the hallucination and inaccuracy problem goes, we are already seeing vendors like Clearbrief offering solutions to the hallucination problem with tools that automatically verify LLM outputs primarily with non-GenAI tools. That potentially solves the cost of verification problem. What if OpenAI decided to do the same?
A Reality for Legal
Could GenAI legal tools become commoditized? The short answer is yes. The open GenAI providers have vast resources and capabilities. There is little to stop them from offering the privacy and confidentiality protections that lawyers demand. There is little to prevent them from offering tools like that being offered by Clearbrief. And if they put their minds to it, they could provide many of the same tools the legal tech vendors who trumpet their uniqueness do now.
And if that happens, the legal GenAI vendors could lose their uniqueness and pricing power. The big GenAI players would be forced to compete primarily on price. Legal tech vendors may not be able to legitimately compete on that basis: they have neither the financial staying power nor resources. The bigger players can spread costs across many more customers, legal and non-legal, can bundle features into larger platforms, and absorb margin pressure longer than the smaller legal vendors.
And let’s not forget many lawyers already used the open tools to do all sorts of things, so transitioning to relying on them for everything would be neither difficult nor time-consuming.
Thus far, the open GenAI providers have been content, like Microsoft, to merely offer their tools to the legal tech vendors as wrappers. But that doesn’t mean the open systems won’t decide to compete directly.
So, What’s Legal to Do?
It would be easy for law firms to just throw up their hands and just ignore the commoditization potential. But that’s not necessarily correct. In fact, law firms and in-house departments can do some things to better prepare for what may be the inevitable commoditization of GenAI tools.
But law firms typically ignore what’s developing in the tech market until it already happens. By doing so, they risk waking up one morning locked into a bunch of overpriced technology when there are just as good and cheaper products suddenly available.
Firms can avoid this by paying attention to what is going on in the marketplace and what vendors are doing. Indeed, the best strategy right now may be to keep their powder dry. To pay attention to the marketplace. To regularly review and monitor their tech stack and tech contractual commitments. To avoid long-term contractual commitments that lock them in. To look hard at things like termination rights and obligations. And to make sure they have an exit strategy should things quickly change.
Stephen Embry is a lawyer, speaker, blogger, and writer. He publishes TechLaw Crossroads, a blog devoted to the examination of the tension between technology, the law, and the practice of law.
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