Not Ready for Prime Time: The Current State of Legal Ethics and AI

Not Ready For Prime Time: The Current State Of Legal Ethics And AI | Techdirt Not Ready For Prime Time: The Current State Of Legal Ethics And AI (Mis)Uses of Technology from the there-be-dragons dept Wed, Aug 12th 2026 03:11pm - Cathy Gellis I’ve been presenting at UC Law San Francisco Lexlab Law and AI certificate program its past several sessions, as well as some law school classes, on whether lawyers’ use of AI complies with the rules of professional conduct governing how lawyers must comport themselves or risk losing their licenses. The legal industry is keen to reap many of the benefits AI promises, such as streamlining some of the more arduous parts of the job and potentially making legal representation more affordable and/or profitable. And tech vendors are keen to profit from selling their AI systems to this market. But neither constituency can benefit unless the way AI is used is consistent with those ethical rules. They exist for a reason—to make sure clients’ interests are prioritized and protected—and nothing about AI obviates their need or applicability. As lawyers start to roll these tools into their practice they need to make sure it’s not in a way that violates those rules, and for those vendors eager to sell their tools to the legal profession, they are going to need to make sure they are designed in a way where their use does not. And we are not yet at a place where compliance can be presumed when AI tools are used. AI use by lawyers remains highly problematic for at least two big reasons: the current unreliability of AI outputs, and the tendency for AI to consume, store, and reuse data it is exposed to, even if that data needs to remain private. With regard to the former issue, the reliability concerns go beyond just the problem of hallucinated citations appearing in legal briefs; it is still the case that clients hire lawyers for their judgment, which so far AI still cannot replace. Maybe someday if AI has developed into something truly autonomous we could simply demand that it take the bar and be accountable to clients like human lawyers currently are, but since that day is not yet here it is critically important that lawyers not abdicate their own judgment in favor of whatever an AI tool might produce. Clients are depending on them, their lawyers, and they remain fully accountable to serve them as the profession requires. And with regard to the data protection issue, it remains true for any tool lawyers use, AI-based or not: lawyers need to make sure that the tool use does not compromise client information, which they have a duty to protect because really bad things can happen to the client when privacy is not preserved. But AI tools in particular are notoriously greedy about collecting, retaining, and reusing whatever information they can access, unless they are specifically designed not to do so. It is thus critically important for lawyers to make sure that whatever tool they use—including and especially an AI tool—does not have the ability to mishandle or misappropriate client data to which it is exposed. Each of these major issues then reverberates in a number of the specific ethical rules governing lawyers that they need to abide by. What follows is a closer examination of some of the ways they do. There are a few things to note at the outset. First, there are more rules governing lawyers than what have been included in the analysis here, such as those relating to the duty to uphold the reputation of the profession, or those relating to advertising, which AI can also implicate. But the ones included are some of the major ones and examples of how AI use can rule afoul of them. It’s also important to note that the rules can work together, and sometimes are in tension. The duty of zealous advocacy, for instance, can sometimes be at odds with the duty of candor. But AI does not itself resolve those ethical questions. Instead what is important to realize is that an AI use might implicate more than one rule. As for the rules themselves, although they are rooted in some longstanding principles, what governs lawyers today are a set of model rules the American Bar Association promulgated in 1983 and pretty much every state has since adopted in some form. Because they can vary somewhat in how they were adopted by each state, lawyers need to consult the specific language their state has used to know how the rules apply to them, along with any other guidance and commentary their state’s lawyer regulators have produced. In fact, many states are also busy updating this guidance in order to specifically apply it to lawyer AI use (as is the ABA). But the basic gist of each rule is largely the same for all lawyers and based on the model language articulated by the ABA originally. These rules also apply to all lawyers and not just litigators. Even transactional, or deal-making, lawyers need to follow them, and so do in-house counsel, who still have clients they owe duties towards, even if it is just one client. So when they declare, on behalf of their client—as, alarmingly, many have—that they will only hire law firms that use AI it is fair to question whether such a priority is indeed consistent with their ethical duties. Perhaps in individual circumstances such an AI-using firm might be preferable, but it won’t be universal; it will depends on the task the lawyers are being engaged to help with and what specific tools they are using. It would after all be contrary to the client’s interests to engage a firm that used an AI tool that compromised the confidentiality of the client’s sensitive information. Plus there remains the question of whether the AI tool being used is really one that can help the job get done in a way that can be trusted, let alone with the savings the client is hoping to see, given the time needed to verify its output. Rule 1.1: Competence. If you are going to be engaged as a lawyer, you must make sure you know how to do the job, however you find yourself called to do it. Traditionally the duty of competence has, for example, meant that a lawyer could not take on a matter in an unfamiliar area of law, like criminal defense when they were an estate planner (or vice versa), but the rule is not limited to just those situations. Case hallucinations strike at the heart of it, for instance. If you are advocating for a client, you need to know the law relevant to the client’s situation, and if you are submitting hallucinated cases that don’t exist, it strongly suggests that you do not, or else you would have known they were imagined. Which is one reason AI cannot suddenly expand the types of matters a lawyer can take on—it’s simply not reliable enough on its own. The lawyer will still need to know when it is giving good answers and when it is not, but if the lawyer does not already have that competence themselves, then they won’t be able to make that determination. There is also a related concept that is becoming more and more important to the legal profession: technical competence. Do you know how to effectively use the tools you are using? The answer needs to be yes, particularly to ensure that your tool use is not creating problems you were not aware of, especially with respect to protecting client data. As discussed further below, lawyers have a duty to protect client information, which means they need to know how to use their digital tools properly to ensure it remains protected. Concerns about technical competency predate AI, given the risk of potential hacker exfiltration, but they apply just as readily to an AI system exposed to client data that may then train on it. Rule 1.3: Diligence. This duty goes hand in hand with the duty of competency but requires a bit more. It’s a lawyer’s job to do the job. And the whole job, not just the bits of the job they like best. One supposed promise of AI is that it can increase the volume of matters a lawyer can take on. But can it actually? Because on each matter it will still be the lawyer’s judgment on the line. So while AI might offer some time savings on certain tasks associated with a representation, and that might seem to create capacity to take on more matters, the lawyer will still need to have the bandwidth to competently provide any representation they’ve been engaged to provide. There are physical limits to what one lawyer can do, even with the help of AI, and especially given that they still need to be able to review whatever results an AI tool might give them to help along the way and that supervisory function will also require time. This diligence rule also incorporates the general lawyer duty of zealous advocacy. Before relying too heavily on an AI tool, one needs to ask whether an AI can actually itself deliver zealous advocacy. Can it deliver all the strategic thinking needed to look out for the client and their objectives in evolving circumstances? And would whatever it recommended also comport with the rest of the ethical rules? If the AI can’t meet all those requirements—and it’s doubtful whether any truly can right now—the lawyer will still need to. There is also a new wrinkle developing with respect to this rule and case hallucinations: increasingly courts are imposing a duty on litigators to police their opponents’ briefs for false citations. If they do not, they may not be able to recover fees for litigating against the fiction once they are finally brought to the court’s attention. Diligence appears to now require that sort of review (although in some instances it is framed as part of the duty of competence). Rule 1.4: Communications. Clients are entitled to be kept apprised of how things are going with their representation and be able to contribute to it. On the one hand, if AI does create some time savings for lawyers, it may help ensure they have more time to communicate with clients. But if AI is used in a way that replaces lawyer judgment, and, worse, is applied to tasks where it performs them in a way that lacks adequate transparency, then clients won’t be given enough information such that they can assist with their own representation. The lack of transparency is especially an issue for agentic AI, where instead of manually working with an AI a step at the time the lawyer is trusting the AI to do a more complex task, because the AI may not even realize that it needs to report out what it has already done and be able to get more input before proceeding. Furthermore, applying AI to client communications themselves also raises the risk of exposing confidential client information. Such a task would inevitably require the AI to learn about the client in order to know what to tell them, but if what it learns does not stay local to the law firm then its confidentiality is no longer protected. Rule 1.5: Fees. This rule requires lawyer fees to be reasonable, which some have suggested may require using AI. The thinking is that if technology makes some lawyer tasks more efficient, it would be unreasonable to bill for the time taken to perform the tasks without the technology. And as a general proposition this view may be correct: we may, for instance, no longer consider it reasonable to bill for the time needed to research in a law library when so much information is now digitized. But it does not follow that using AI is similarly necessary to use, especially not when there are so many issues still associated with its use. Indeed, it’s even questionable whether it can provide true savings given that lawyers must still take the time to review anything resulting from an AI tool before it is relied upon. Perhaps in some in some situations there can be a savings, but, given the current state of the technology, the savings are not nearly certain enough at this point to support the inference that AI use is something that must be implicitly required. There also is a side issue of when the costs associated with AI use can be [truncated for AI cost control]