Law schools face mounting pressure to prepare students for an AI-transformed legal profession, yet most institutional responses have centered on individual faculty course policies which leads to a fragmented approach, creating inconsistency and imposing significant burdens on professors who have not yet developed consensus on AI’s pedagogical implications. Other law schools have adopted schoolwide bans for AI usage. While this approach strives for consistency, it doesn’t address the need to prepare law students for a world in which they will need to utilize AI in a professional capacity. This essay proposes a complementary, institution-first strategy where artificial intelligence tools are employed at the administrative level to introduce students to AI-assisted professional practice before the classroom debate is resolved. Specifically, the essay examines how law school administrators (and student service offices) can model effective AI use by integrating these tools into routine professional communications such as emails, cover letters, curriculum vitae, internal responses at the school or University level and mandatory bar admission disclosures. In doing so, students acquire fluency with AI assistance in a low-stakes, professionally authentic context, one that will be referred to as the “administrative space.” There are four essential components of the administrative AI framework: (1) modeling the development of an authentic professional voice; (2) leveraging a variety of AI tools rather than relying on a single platform; (3) modeling ethical AI practices, including the protection of confidential information; and (4) cultivating rigorous proofreading and editing habits. Administrative AI integration offers a durable, ethically grounded bridge between the profession’s AI reality and the law school’s evolving curricular response.
I. Introduction
The arrival of capable generative artificial intelligence tools has upended longstanding assumptions about legal practice. Law schools have scrambled to respond, but most institutional reactions have been reactive (such as school-wide bans) or fragmented. Faculty members, individually and in small committees, have adopted divergent classroom AI policies, ranging from categorical prohibition to open encouragement. The result is an inconsistent patchwork that students find confusing and that fails to convey any coherent professional norm.
This essay does not propose to resolve the curricular debate. Reasonable legal educators disagree about whether AI assistance in student work product constitutes an academically honest deployment of professional tools or an improper circumvention of the learning process. Those are genuine questions that deserve sustained scholarly and institutional attention. What this essay does propose is a strategy that does not require that debate to conclude before meaningful AI education begins. Rather, generative AI instruction may be integrated into the law school’s administrative operations by training students to use AI in producing the routine professional documents that every law student must generate regardless of what happens in any classroom.
The law school’s administrative functions provide an ideal pedagogical space because communications, disclosures, applications, and similar documents are regularly utilized by law students through their engagement with the law school. These tasks are professionally authentic, universally required, and sufficiently low stakes (compared to classroom assignments) such that errors can be corrected without academic consequence. By modeling and guiding AI-assisted professional writing in this context, law school administrators can accomplish several things at once. First, we can equip students with practical competency in AI tools by giving them repeated attempts to refine their use of the tools in a setting that has educational oversight. Second, we can communicate institutional norms about responsible AI use by extending the current normative practices and rules which already govern these communications. Finally, we can provide the faculty time and space to deliberate about the harder curricular questions without leaving students entirely unequipped for the world they are about to enter.
II. The Gap Between AI Reality and Legal Education
A. The Profession Has Already Moved
By any objective measure, generative AI tools are now embedded in legal practice. Large law firms have deployed AI platforms for document review, contract drafting, legal research, and due diligence at scale.1 Mid-sized firms have adopted publicly accessible AI tools with particular enthusiasm, drawn by their low cost and immediate practical utility.2 Small and solo practitioners have been slower to adopt AI, but there is more movement in this direction.3
Courts have been addressing misuse of AI in matters before them and have repeatedly issued orders sanctioning attorneys.4 Bar associations and state supreme courts have begun issuing ethics guidance addressing AI use, implicitly acknowledging that AI-assisted practice is already widespread enough to require ethical guardrails rather than categorical prohibition.5
B. The Law School’s Response Has Lagged
Despite the profession’s rapid adaptation, law school curricular responses have been inconsistent.6 This is not surprising. Curricular change in legal education has historically been deliberate, even glacial, because it implicates faculty governance structures, accreditation standards, and deeply held views about the purpose of legal education and its role in shaping the legal profession.7
The AI question is additionally complicated because it sits at the intersection of education, academic integrity, and professional identity formation in ways that resist easy curriculum modification. Faculty members who believe that learning to write well requires struggling through the drafting process without AI assistance are not simply being “resistant to change,” they hold a coherent pedagogical view and one that is consistent with some identifiable dangers associated with early use of AI.8 Similarly, those who believe that learning to use AI well is itself a core professional skill are grounding these beliefs in solid pedagogy, that supervised practice is necessary for effective development of a skill.9 The disagreement is genuine, and institutional bans on AI are not likely to generate a long-term solution that balances these competing views. Faculty struggle and debate with these topics is essential to providing salient changes that are not simply reactionary.
While continued faculty debate on the proper way to introduce AI training into the law school curriculum is warranted, law schools will need to provide law students with opportunities to develop their proficiency with generative AI. Rule 1.1 of the Model Rules of Professional Conduct mandate that lawyers have competency with technological tools.10 This is expanded in Comment 8, which states “a lawyer should keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology.”11
C. The “Administrative Space” as a Solution
What has been underappreciated is that the law school’s administrative function operates within the larger scope of “legal education,” but is largely outside the current curricular debate. When a student emails a professor, completes a university form, applies for a position with the public defender’s office, submits a supplemental bar application disclosure, or writes a cover letter for a judicial clerkship, these activities are professional rather than purely academic in character. They are the student’s work product in a professional capacity, but they do not involve an academic submission being evaluated for grade.
This distinction creates an important opportunity to explore AI training in a confined context. Law school administrators (e.g., the Associate Dean for Academic Affairs, Dean of Students, career services offices, student affairs offices, registrars, librarians, University bursar, etc.) routinely assist students with precisely these tasks. They review cover letters, explain bar disclosure requirements, coach email communication, and guide students through professional document preparation. Introducing AI tools into this existing administrative/educational structure does not require overcoming faculty governance hurdles (so long as any AI ban does not extend beyond the classroom). Moreover, it does not (as easily) implicate academic integrity policies, nor require resolving any disagreement about classroom AI use. It simply asks administrators to model and teach AI-assisted professional writing as part of the mentorship they already provide.
III. Identifying the Right Administrative Contexts
A. Professional Communications: Email and Correspondence
Email remains a primary professional communication medium of the legal profession. Yet supervising attorneys routinely identify inadequate professional written communication as among the most common deficiencies of new lawyers.12 Similar criticisms are also expressed by law professors and administrators when they receive student communications.13 But law students’ email communications with faculty, administrators, university personnel/offices and employers often suffer from problems that AI tools are genuinely well-suited to address. For example, AI can offer opportunities to refine the formal components of a professional email, clarity of expression, inappropriate informality of tone, poor organizational structure, and failure to anticipate the reader’s informational needs.14
Career Services and Student Affairs Offices are already positioned to provide this coaching since they typically provide guidance about appropriate communications with employers, alumni and legal professionals. Adding AI as an explicit tool in this coaching by showing students how to use AI to review a draft email for tone and grammar, how to prompt AI to reorganize a communication for greater clarity, and how to critically evaluate AI suggestions rather than accepting them uncritically, can provide a natural extension of existing services. Similarly, the Deans’ Offices (Associate Dean for Academic Affairs or Dean of Students) are likely already engaging with students regarding submissions of required University forms to their office or through monitoring student requests or complaints. Providing training in how to use AI tools while educating students about law school procedures is also a natural extension of training. For example, the Dean of Students (or other administrator responsible for working with law student organizations) should train student leader on how to effectively use an AI prompt when drafting an email to a law school administrator requesting something on behalf of their group. Similarly, the Associate Dean for Academic Affairs may work with a struggling student on how to use AI to edit an email to a professor for tone and clarity. Training on appropriate emails to law school faculty and staff can be included in basic law school orientation programming when exposing students to expectations of professional students.
B. Supplemental Law School Admission and Bar Admission Disclosures
Every law student who seeks admission to a state bar must complete extensive background disclosure forms. These forms require applicants to describe prior conduct including criminal history, academic discipline, financial difficulties, mental health treatment, and similar matters with precision, accuracy, and appropriate context. An incomplete or inaccurate disclosure can result in denial of admission even where the underlying conduct would not independently have disqualified the applicant.15 Additionally, all law students must correct incomplete law school admissions disclosures and provide supplemental disclosures on matters that arise while they are a student.16 As a result, most law schools provide some training to students about these submissions.
These disclosures are an excellent context for guided AI assistance for two reasons. First, they are professional documents, not academic submissions. While there are consequences to submitting a false or misleading submission to the bar, the concerns present in academic submissions improperly relying on AI are not present. Professors who resist the use of AI for class assignments are often concerned that AI will short-change the educational process or create cognitive offloading that is detrimental to the development of writing skills.17 They espouse the value in having students independently struggle through a concept or in how to synthesize the written word for the legal document (be it a brief, motion, or exam answer). These educational goals are not integral to the drafting of a bar disclosure. Second, bar admission disclosures present exactly the kind of organizational, grammatical, and tonal challenges that AI tools address well.18 Students must present potentially sensitive information in a factual, professional, and non-defensive manner that demonstrates candor and growth. AI can help students achieve the appropriate professional tone and ensure their disclosure is organized clearly. The student, however, must supply the factual content and make all substantive judgments about what to disclose. Unlike on an academic assignment, the factual summary is unique to the student’s own situation. Because the student should have intimate knowledge of the facts (unlike a fact pattern they are presented in a course), they will be better positioned to evaluate the AI generated material for accuracy and engage in the higher-level evaluation/critique of AI that we they will apply to future legal issues. Additionally, there is an opportunity to have a conversation about the consequences of candor and the dangers of AI. Because the facts at issue are real rather than professor-created hypotheticals, and because students face tangible consequences for submitting inaccurate or untruthful accounts, this exercise creates an authentic learning environment in which students are more likely to recognize and understand the dangers of AI hallucinations.
C. Cover Letters and Curriculum Vitae
The professional document preparation services that Career Services Offices provide, such as reviewing cover letters and CV drafts, are another natural fit for AI integration. AI tools excel at identifying grammatical errors, suggesting stronger verbs, flagging inconsistencies in formatting, and helping writers achieve a professional tone.19 Again, the pedagogical value extends beyond the immediate document. By working through the AI-assisted drafting process with a career counselor’s guidance, students learn how an AI tool can be leveraged to improve the clarity of their writing while the substantive content is uniquely their own. This setting is especially valuable because it allows the student to see how their experiences are highlighted by the AI. They can then, with the guidance of the career services professional, evaluate whether they need to retool their documents to ensure that the document is framed in the best manner to connect with a particular employer. Schools or law firms could even develop specific AI tools to tailor CV and cover letters for particular employers.
IV. Four Critical Components
An administrative AI integration program that merely encourages students to “use AI” without considering the larger educational goals, misses the mark. It is not just that law students need to know how to use AI, but to learn professional decision-making and how to exercise that skill while engaging with AI. This Part identifies four critical components for any administrative AI integration program.
A. Developing an Authentic Professional Voice
A significant risk of AI-assisted writing is the loss of an authentic individual voice. AI-generated text tends toward a particular aesthetic which is slightly formal, generic, and occasionally given to hollow constructions.20 For example, a student writing a document in the context of career services might get an AI suggested response such as, “I am excited to leverage my skills in a dynamic environment.” Lawyers and employers recognize this tone immediately, and it is not a professional asset. This challenge, however, is not unique to AI. Most student services offices provide forms or examples to students.21 A student simply replicating the exemplar is not going to have the impact on the employer that they intend. The Career Services Office is still being tasked with teaching law students how to “personalize” and modify examples. Now, the example is simply being generated with the assistance of AI.
Students must learn that AI is a collaborator in drafting, not a ghostwriter. They should be trained to provide AI with substantive content and then critically evaluate the AI’s suggestions against the question, “Does this sound like me, at my professional best?” This process is integral to the development of professional identity.22 As students think holistically about what it means to be a lawyer and their own professional goals, they should be encouraged to consider that their professional “voice” should remain the same no matter the context. While “tone” may shift based on the context and the audience, the authentic identity of the writer should always remain. AI’s ability to suggest tonal revisions provides a meaningful opportunity to teach students that while tone may be adjusted for audience or purpose, authentic professional voice must remain their own.
Law students often struggle to find an authentic professional voice.23 Some err toward excessive formality, straining to sound like what they imagine a lawyer “should” sound like. This risks burying their own identity under generic legalese. Others err toward excessive informality, risking a tone that reads as unpolished or underdeveloped. AI is a great tool to help with this. A student should be asked to speak aloud what they would like to communicate. Oral statements tend to be more authentic and can made into impactful AI prompts; they are more impactful than a generic AI prompt such as “draft an email requesting an opportunity to interview with the law firm.”
The career services professional can create a learning module to assist students in generating these types of prompts and can encourage them to also use generic prompts. As part of the module, students should be encouraged to compare and critique the AI output with a rubric. Ultimately, the exercises used to train students should encourage them to revise AI output in their own voice rather than accepting it wholesale. And they should understand that a cover letter or professional email that reads as AI-generated is not a polished professional document and will not have the intended impact.
The final step is for administrators to explicitly model the revision process. Students should see administrators use AI-generated suggestions as a starting point and then deliberately revise those suggestions to align with their own authentic professional voice. By making the editing process visible, administrators reinforce that effective AI use requires judgment, critical evaluation, and personal ownership of the final product. The goal is not for AI to replace the student’s voice, but to help students communicate as the strongest, most professional version of themselves.
B. Using Multiple Tools
No single AI platform is optimal for all tasks, and professional competency requires familiarity with the strengths and limitations of multiple tools.24 Students who develop exclusive familiarity with a single AI product are not well-prepared for practice where the available tools will continue to evolve and where different tasks will call for different approaches. An administrative AI program should deliberately expose students to multiple platforms. For grammar and tone refinement, products like Grammarly or Microsoft Editor offer targeted, low-risk assistance.25 For more substantive drafting tasks, larger language models, such as ChatGPT or Claude offer different capabilities and require different critical engagement.26 Students should learn to choose the appropriate tool for the task and to triangulate across tools when the stakes are higher, for example, checking a bar disclosure narrative against multiple AI platforms before finalizing it.
This multi-tool approach also has the benefit of reducing students’ dependence on any platform whose availability or pricing might change,27 and it builds the kind of technology-agnostic competency that will serve them throughout a career that will encompass AI tools that do not yet exist. Additionally, law schools can begin to expose students to AI tools that are uniquely created for legal professionals, such as Harvey AI.
C. Promoting Ethical Use of AI and Protecting Confidential Information
It is imperative that law students are exposed to ethical concerns while using AI.28 One specific topic that AI raises is the use of confidential information.29 Some publicly accessible AI platforms retain user inputs for training purposes, or at minimum for operational logging, unless users have taken specific steps to opt out or have subscribed to enterprise-tier privacy protections.30 Inputting client information, case facts, or other confidential professional information into a standard consumer AI product is potentially a serious confidentiality breach.31
In the administrative context specifically, students should be trained not to input confidential information into AI platforms when preparing bar disclosures, employment applications, or other professional documents. Training can occur at orientation and then be developed in a series of workshops throughout the academic year. Practically, students should be encouraged describe their situations in general terms for AI drafting assistance and then replace the AI’s generic placeholder language with their own specific factual content in the final document rather than feeding the AI all specific facts at the outset. For example, in describing prior work experience, they should be reminded not to include information about specific cases they might have worked on. This habit, once established in the low-stakes administrative context, will serve students well throughout their careers.
D. Rigorous Proofreading and Editing
AI tools make confident errors.32 They hallucinate facts, misstate names, generate plausible-sounding but incorrect citations, and occasionally produce grammatical errors of their own while correcting others.33 Students must understand that AI output requires rigorous human review.34 A lawyer who submits AI-generated work product to a court or client without independent review and verification is failing her competence obligation, as several highly publicized judicial sanctions have made clear.35 The bar for AI review in law is not “does this look right?” but rather “have I independently verified every factual claim and legal citation in this document?”
Administrative AI programs should build proofreading and editing into the workflow explicitly rather than treating it as an afterthought. When a career counselor helps a student use AI to draft a cover letter, the session should include dedicated time for the student to read the AI output carefully, identify anything that does not sound right or does not accurately represent their experience, and make corrections. The same can be done in the context of supplemental admissions disclosures, disclosures made to the school following matriculation and in bar disclosures (to the extent the bar services professional or others assist the students with these). This develops the habit of critical engagement with AI output that students will need in practice.
V. Implementation Considerations
A. Coordination and Faculty Relations
An administrative AI integration program does not require faculty approval (unless the school has adopted a blanket ban of AI in all settings), but it benefits from faculty awareness and ideally from faculty support. Faculty engagement helps ensure that students receive consistent messaging about the appropriate role of AI within the law school. Even if the faculty ultimately prohibits AI use in their courses, they can help students understand that the objectives of administrative communications differ from those of academic assignments. Faculty can reinforce that the appropriate use of AI depends on context rather than reflecting a universal endorsement or prohibition. Equipping students with this more nuanced understanding of AI is an important educational objective, preparing them to exercise sound professional judgment about when technology should, and should not, be used.
Administrators should communicate clearly that the program addresses professional and administrative documents rather than academic submissions, so that faculty members do not perceive the program as an end-run around classroom AI policies. Transparency will prevent misunderstanding and may actually generate faculty goodwill, since a coherent administrative AI framework may reduce the pressure on individual faculty members to address every aspect of AI use in their courses.
B. Resource Requirements
The marginal resource cost of AI integration into existing administrative services is modest. Career Services Offices, Student Affairs Offices, and similar units already provide document review and professional mentorship as core functions.36 Adding AI tools to these workflows requires training administrators on the tools and on the pedagogical goals described here, but does not require creating new staff positions or significant new infrastructure. Many AI tools are available at low or no cost for basic use.37 Even costs associated with tools that permit more sophisticated operations, such as the ability for the user to upload and analyze documents, are a worthwhile investment. The primary investment for the law school is not the technology itself, but the time and effort devoted to training administrators and developing effective workshop curricula.
C. Assessment and Iteration
Like any educational initiative, an administrative AI program should be assessed and refined. Administrators should collect data on whether the program is building the competencies it targets, such as assessments built into any training module and expanding surveys already given to employers and others receiving student work product. Using this information, they should update their tool recommendations and pedagogical approach as the AI landscape continues to evolve. The program’s goal is not to endorse any particular tool but to build transferable AI literacy, and the curriculum should be constructed so that specific tool recommendations can be updated without restructuring the entire program.
VI. Conclusion
Law schools face an institutional dilemma. The profession has already moved to AI-assisted practice, but many schools have not yet resolved the harder pedagogical questions about AI in academic work.38 The administrative AI integration framework proposed in this essay offers a principled path through this dilemma.
This is not a substitute for curricular conversations. Faculty should continue to deliberate about AI in the classroom, because those questions matter enormously for what law students learn and for what kinds of lawyers they become. While those deliberations proceed, however, law school administrations need not leave students without institutional guidance on a technology that will shape their professional lives.
The window for acting first through administration, rather than defaulting to a classroom-by-classroom patchwork, remains open. Law schools that act thoughtfully will be better positioned to shape a professional culture around AI that is competent, ethical (and authentically human) rather than simply reactive.
* Professor of Law and Associate Dean for Academic Affairs, Simmons Law School, Southern Illinois University. Email: aupchurch@siu.edu. Comments welcome. OpenAI, ChatGPT-5.5 and Anthropic, Claude Opus 4 were used to edit text for clarity of expression. All analysis, argument, verification of supportive citation, and revisions are my own.
1. Evan Ocshner, Law Firms Adopt AI Tools at Unheard-Of Pace as Enthusiasm Grows, Bloomberg L. (June 22, 2026 at 04:00 CT), https://news.bloomberglaw.com/legal-ops-and-tech/law-firms-adopt-ai-tools-at-unheard-of-pace-as-enthusiasm-grows [https://perma.cc/9BWA-3UZU].
2. Tami Lyn Munsch, Technology Strategies for Law Firm Success, L. Prac. Mag., May 1, 2025, at 17, 20; Clio, AI Adoption Trends by Law Firm Size: Solo, Small, and Mid-Sized, L. Prac. Mag., June 26, 2025, at 129, 130.
3. Clio, AI Adoption Trends by Law Firm Size: Solo, Small, and Mid-Sized, L. Prac. Mag., June 26, 2025, at 129, 130.
4. Emily R. Desbien, Comment, With Great Power Comes Great Responsibility: Court Sanctions for Misuse of GenAI, 38 J. Am. Acad. Matrim. Laws. 211, 212 (2025); Jessica R. Gunder, Rule 11 Is No Match for Generative AI, 27 Stan. Tech. L. Rev. 308, 317 (2024); John G. Browning, Robot Lawyers Don’t Have Disciplinary Hearings—Real Lawyers Do: The Ethical Risks and Responses in Using Generative Artificial Intelligence, 40 Ga. St. U. L. Rev. 917, 920 (2024).
5. The State Bar of California Standing Committee on Professional Responsibility & Conduct, Practical Guidance for the Use of Generative Artificial Intelligence in the Practice of Law,State Bar of Cal., https://www.calbar.ca.gov/sites/default/files/portals/0/documents/ethics/Generative-AI-Practical-Guidance.pdf [https://perma.cc/5MD2-XN4G] (last visited Aug. 18, 2026); A.B.A. Comm. on Ethics & Pro. Resp., Formal Op. 512 (2024); see AI and Attorney Ethics Rules: 50-State Survey, Justia (Apr. 2025), https://www.justia.com/trials-litigation/ai-and-attorney-ethics-rules-50-state-survey/ [https://perma.cc/7994-SXCW].
6. AI & Legal Educ. Working Grp., ABA Task Force on L. and A.I. AI and Legal Education Survey Results 2024 6 (2024), , https://www.americanbar.org/content/dam/aba/administrative/office_president/task-force-on-law-and-artificial-intelligence/2024-ai-legal-ed-survey.pdf [https://perma.cc/9J2G-R55Z]; Kathryn Palmer, To AI-Proof Lawyers, Some Law Schools Restrict Technology, Inside Higher Ed. (July 14, 2026), https://www.insidehighered.com/news/tech-innovation/artificial-intelligence/2026/07/14/ai-proof-lawyers-some-law-schools-restrict [https://perma.cc/EVM8-7DKG]
7 See John C. Weistart, The Law School Curriculum: The Process of Reform, 1987 Duke L.J. 317, 320 (1987).
8. See George Sandeman, Are These AI Prompts Damaging Your Thinking Skills?, BBC (Dec. 20, 2025), https://www.bbc.com/news/articles/cd6xz12j6pzo [https://perma.cc/J6ME-ZJGK]; Nataliya Kosmyna et al., Your Brain on ChatGPT: Accumulation of Cognitive Debt When Using an AI Assistant for Essay Writing Task, Arxiv (Dec. 31, 2025), https://arxiv.org/abs/2506.08872 [https://perma.cc/7Y7U-C89L].
9 See Jeremy Blum, Shirley Clark & Nashwa Elaraby, Reskilling and Professional Development in the Age of AI, Penn. St. World Campus (Mar. 23, 2026), https://www.worldcampus.psu.edu/about-us/news-and-features/reskilling-and-professional-development-in-the-age-of-ai [https://perma.cc/TX38-QF8A].
10 Model Rules of Pro. Conduct r. 1.1 (A.B.A. 2026).
11. Model Rules of Pro. Conduct r. 1.1 cmt. (A.B.A. 2026).
12. Deborah Jones Merritt & Logan Cornett, Building a Better Bar: The 12 Building Blocks of Minimum Competence 88 (2020), https://iaals.du.edu/sites/default/files/documents/publications/building_a_better_bar_pre_print.pdf [https://perma.cc/H4CY-4RDH].
13 Ann Nowak, The Struggle with Basic Writing Skills, 25 Legal Writing 117, 117 (2021).
14 Jenny Donovan, From Concept to Clarity: Why Communication Skills Are an AI Superpower, Soc. for Hum. Res. Mgmt.: Bus. (Oct. 1, 2024), https://www.shrm.org/enterprise-solutions/insights/from-concept-to-clarity–why-communication-skills-are-an-ai-supe [https://perma.cc/6YGL-S6C9].
15 James E. Spence, Jr., From My Perspective: Advising Applicants on the Character and Fitness Process, Bar Exam’r, Spring 2022, at 54, 56.
16 Id. at 58.
17. See Sandeman, supra note 8; Kosmyna et al.,supra note 8.
18 See Spence Jr., supra note 15, at 58.
19 See Donovan, supra note 14.
20 Bradley Emi, Comprehensive Guide to Spotting AI Writing Patterns, Pangram (Apr. 2, 2025), https://www.pangram.com/blog/comprehensive-guide-to-spotting-ai-writing-patterns [https://perma.cc/XM6D-ZCEM].
21 See Employment Forms and Letter Templates, Iowa Univ. Hum. Ress., https://hr.uiowa.edu/compensation-classification/employment-forms-and-letter-templates [https://perma.cc/M53D-ULKP] (last visited Aug. 18, 2026).
22 Sumati Ahuja, Frida Pemer & Emmanuel Mastio, AI and Identity Work: A Case of AI Implementation and the Fragmentation of Professional Identity, 36 Info. & Org. 1, 10 (2026).
23 See Nowak, supra note 13, at 117.
24 See AI Tools, Harv. Univ.: Info. Tech., https://www.huit.harvard.edu/ai/tools [https://perma.cc/R6VV-9XQT] (last visited Aug. 18, 2026).
25 See Kiera Abbamonte, The 6 Best Grammar Checkers, Zapier (June 3, 2025), https://zapier.com/blog/best-ai-grammar-checker-rewording-tool/ [https://perma.cc/9C65-SSNL].
26 See AI Tools, supra note 24.
27 Basil C. Puglisi, Getting Better Answers: A Practical Guide to Using Multiple AI Platforms, Medium (Nov. 14, 2025), https://medium.com/@basilpuglisi/getting-better-answers-a-practical-guide-to-using-multiple-ai-platforms-774b65bb3987 [https://perma.cc/ZUF2-AD2F].
28 See Highlight of the Issues, Am. Bar Ass’n, https://www.americanbar.org/groups/centers_commissions/center-for-innovation/artificial-intelligence/issues/ [https://perma.cc/NJ4M-3KBE].
29 Id.
30 Security Tip: AI & Data Privacy Best Practices, Trinity Coll., https://www.trincoll.edu/lits/technology/security/best-practices/security-tips/ai-data-privacy/ [https://perma.cc/5BN2-LMKR] (last visited Aug. 18, 2026).
31. See Model Rules of Pro. Conduct r. 1.6 (A.B.A. 2026) ); A.B.A. Comm. on Ethics & Pro. Resp., Formal Op. 512 (2024).
32 Megan Morrone, AI Is Still Getting Things Wrong, More Confidently Than Ever, Axios (May 30, 2026), https://www.axios.com/2026/05/30/ai-accuracy-chatbots-hallucinations [https://perma.cc/HWE3-9FC9].
33 Chrystal R. China, What Are AI Hallucinations?, IBM (July 31, 2026), https://www.ibm.com/think/topics/ai-hallucinations [https://perma.cc/TLE2-CHXF].
34. See The State Bar of California, supra note 5; Mata v. Avianca, Inc., 678 F. Supp. 3d 443, 466 (S.D.N.Y. 2023) (sanctioning attorneys who submitted AI-generated brief containing fabricated case citations without verification).
35. Lifetime Well LLC v. IBSpot.com Inc., 819 F. Supp. 3d 373, 378 (E.D. Pa. 2026); Benjamin v. Costco Wholesale Corp., 766 F. Supp. 3d 419, 422 (E.D.N.Y. 2025); ByoPlanet Int’l, LLC v. Johansson, 792 F. Supp. 3d 1341, 1346 (S.D. Fla. 2025); Mattox v. Prod. Innovations Rsch., LLC, 807 F. Supp. 3d 1341, 1348 (E.D. Okla. 2025); Mata v. Avianca, Inc., 678 F. Supp. 3d 443, 448 (S.D.N.Y. 2023).
36 Nat’l Ass’n for L. Placement, Going Back to Law School: Moving from Practice to Law School Career Advising 1 (2024), https://www.nalp.org/uploads/GoingBacktoLawSchoolMovingfromPracticetoLawSchoolCareerAdvising.pdf [https://perma.cc/MR6W-8ALN].
37 AI Tools, supra note 24.
38 See Christopher S. Engle-Newman, Assessing Law Student Learning in the Age of AI, 87 U. Pitt. L. Rev. 451, 454 (2026).
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