The AI Dilemma: 3 Ways In-House Counsel Should Be Using AI Today
Photo by Igor Omilaev on Unsplash
Author: Ty Leitow
Last Update: June 10, 2026
As in-house legal professionals, our mandate is clear: protect the business, manage risk, and facilitate growth, all while keeping an eye on the bottom line. It’s a delicate balancing act that requires both sharp legal acumen and a solid grasp of business strategy.
Since ChatGPT was first released back in 2022, there has been a relentless drumbeat in the corporate world about artificial intelligence (AI). From the boardroom to the breakroom, everyone is talking about how generative AI is impacting the way we work. That revolution is already underway in the tech sector, sending ripple effects across the economy. The law, on the other hand, is rarely on the cutting edge of anything. Instead, the law is often reactionary, applying old models and ideas to the ever-changing world. It seems that only when forced do lawyers adapt and change to meet the world where it is. It seems that AI is an unstoppable force that every profession must adapt to.
Most corporate legal departments are interested in but reluctant to embrace the capabilities (and hallucinations) AI has to offer. Legal is an operating expense, and often is under-funded. The proper deployment of AI can be a productivity multiplier, benefitting most in-house legal teams, and especially those small departments with only a few lawyers.
According to a joint 2024 survey report published by the Association of Corporate Counsel (ACC) and Everlaw, less than half (42%) of in-house lawyers feel prepared for the impact of Generative AI on their careers. There is a palpable hesitation. We worry about data security, confidentiality, attorney-client privilege, hallucinations, and the simple fact that our entire profession is based on being right, and being able to argue, if not prove, we’re right. At the surface level, it seems quite ridiculous to ever put ourselves in a position where we are defending bad legal guidance to executives or the board by saying “I got it from AI.”
However, as progress marches forward, burying our heads in the sand is not an option. The 2025 Thomson Reuters Generative AI in Professional Services Report noted that in-house counsel AI usage nearly doubled in just one year. AI is not coming to take your job (yet), but a lawyer leveraging AI efficiently just might.
The goal is not to adopt technology for technology's sake. The goal is practical application. How can we use these tools right now to provide faster, better guidance to our executive teams? How can we streamline standard workflows? Can our legal teams be smaller and more capable at the same time?
Here are three concrete ways in-house lawyers should be utilizing AI today.
1. Accelerating Routine Contracting and Lifecycle Management
The reality of in-house practice is that high-volume, lower-complexity agreements often consume a disproportionate amount of our time. Think about standard vendor agreements, routine service contracts, and Non-Disclosure Agreements (NDAs). I’ve written before about how critical NDAs are for protecting trade secrets and proprietary information, provided they are drafted narrowly and precisely. But reviewing them manually, day in and day out, creates a bottleneck that slows down the speed of business.
This is where AI excels. Today’s legal AI tools utilize Natural Language Processing (NLP) to read, interpret, and summarize contracts in seconds. Rather than reading a 20-page vendor agreement line-by-line just to find the indemnification and limitation of liability clauses, AI can instantly extract those provisions and compare them against your company’s standard playbook.
Bloomberg Law notes that modern tools can quickly identify how contract language deviates from market standards, allowing attorneys to determine faster what counterparties typically agree to. Generative AI can also assist in the initial drafting phase—creating a solid first-pass template that a lawyer then refines.
The key takeaway here is "first-pass." AI does not exercise legal judgment, and it certainly does not replace attorney oversight. But by delegating the initial extraction and comparison work to an AI system, you reclaim hours of your day. Delegating this “first-pass” work to AI allows lawyers to engage in strategic thinking, creativity, building, and negotiation, which is where your real value shines through. It also increases efficiency and reduces errors, driving revenue and cost-savings.
With that said, I personally do not fully trust today’s AI tools. Even the paid, enterprise-level, industry-specific, AI models occasionally produce errors and provide questionable judgment, often of the type that a junior lawyer may miss. And like with the growth and development of a junior lawyer into a senior lawyer, you need to take time to review what your AI can do.
2. Supercharging Legal Research and Due Diligence
Whether you are preparing for a major corporate transaction, handling internal compliance audits, or managing early-stage litigation discovery, the sheer volume of data, documents, records, and legal work involved can be staggering. Every legal matter takes time, and this is especially true for novel legal matters. Balancing productivity on major or special projects with day-to-day workflows can be difficult for small in-house legal departments. A majority of in-house legal departments have fewer than 5 lawyers, and it’s these smaller legal teams that can benefit the most from properly deploying AI tools.
When used properly, AI fundamentally changes the math, allowing small legal teams to shorten work cycles and produce more deliverables faster and with fewer errors. According to the 2025 Thomson Reuters report, AI-driven document review and analysis is currently the most-used capability among legal professionals, completing tasks in seconds that traditionally take hours.
In the realm of legal research, AI tools designed specifically for the legal sector (often referred to as agentic AI or professional-grade AI, trained on closed legal databases rather than the open web) are drastically reducing research time. Instead of running complex Boolean searches and sifting through dozens of irrelevant case opinions, you can ask a legal AI tool to summarize the current standard for a specific employment law issue in a given jurisdiction.
The business value of this is immense. By bringing more of this high-volume review and research in-house via AI, you can significantly reduce outside counsel spend. You also get answers to your executive team faster, allowing the business to move with greater agility.
3. Leading Enterprise AI Governance (Moving from "No" to "How")
The third way in-house counsel should be using AI is somewhat paradoxical: Legal teams must embrace AI so they can govern how the rest of the business uses it.
Your marketing team wants to use generative AI to write copy. Your HR department is looking at AI to screen resumes. Your software developers are using AI copilots to write code. While this drives operational efficiency, it introduces massive enterprise risk. If employees are feeding proprietary company data into open-source, mass-market AI models, they might inadvertently be waiving trade secret protections, breaching confidentiality agreements, or running afoul of data privacy laws. As a practical note, many companies have updated their standard B2B NDAs to expressly prohibit sharing any confidential information with any AI, categorizing AI as an unauthorized “third party”.
The best in-house lawyers understand the legal department cannot simply be the "Department of No." Being competitive in the business world means using new tools to drive efficiency and productivity while also maintaining risk management and compliance. Telling employees they cannot use AI will only result in shadow use, where employees use it secretly. Instead, legal must be the "Department of How."
As outlined in Bloomberg Law’s 2026 AI Governance Framework, in-house legal teams should take the lead in drafting and enforcing clear AI usage policies. This involves several critical steps:
Defining Acceptable Use: Clearly outline what types of AI tools are permitted and which are prohibited. Differentiate between public AI (where inputs are used to train the model) and enterprise-grade AI (where your data remains secure and walled off). Work closely with your IT and Data Security colleagues as well as upper management to adopt the right tools with the right guardrails for your specific industry and business.
Updating Existing Policies: Ensure your employee code of conduct, device management policies, acceptable use policies, and anti-discrimination guidelines explicitly address AI usage. Relatedly, legal teams should work with the IT team and AI vendors to ensure proper configuration of the AI tool. In many cases, completely new guidelines on AI use will need to be published that clearly provide employees guidance on how, for what, where, and who may use AI.
Vendor Due Diligence: Every new software vendor your company works with is likely integrating AI. Legal must thoroughly review these vendor contracts. You need to know exactly how a vendor’s AI tool uses your company’s data, who owns the output, and who’s liable if the AI hallucinates or infringes on third party intellectual property. Your secure sandbox should have strong, defined walls to ensure proprietary and confidential information is not used for training or otherwise shared with any third parties.
By becoming a company leader on AI, the legal department transforms from a perceived bottleneck into a strategic business partner that enables safe, compliant adoption of AI. AI should be used with caution, and it must be used to stay current with the latest technological tools. Today’s AI can do some incredible things, but it also can make significant mistakes. Lawyers and non-lawyers alike should apply a ‘trust, but verify’ rule. If you have access to one of Big Tech’s enterprise AI suites, maybe you can treat AI like a new associate. For any other version of AI, assume it’s an intern.
I recently had an AI tell me two sections in a contract were completely incompatible. I’ve been doing contracts nearly my whole legal career, and I read the two clauses at least 5 times. I could not see the contradiction. It was relatively plain language, and it was not some obscure subject matter. I spent 20 minutes talking through the clauses with an AI, until I directly told it that it was wrong. The AI, in a lengthy diatribe, acknowledged the mistake, and said it did not read the two clauses carefully, and missed three key words. The explanation was human, in that it made a mistake, and said it simply did not read the clauses carefully. I was dumbstruck at the simplicity of the mistake, and the incredible low level of skill or knowledge it required to get it right. Trust, but verify.
An AI tool can summarize a 50-page agreement in three seconds, but it may not know your executive team’s risk tolerance, or the particular nuances of your company that makes certain clauses important. It can extract an indemnification clause, but it may not know your company has a long, established history with the other party. It can draft a policy, but it cannot cultivate the cross-departmental relationships necessary to ensure that policy is actually followed by the workforce.
The in-house lawyers who will thrive in this new era of AI are not those who resist technology, nor are those who blindly trust it. The most successful lawyers will be those who use AI to handle the mechanical, data-heavy tasks, freeing up their mental bandwidth to focus on the human elements of legal practice: judgment, strategy, empathy, and leadership.
References
1. Association of Corporate Counsel (ACC), The AI Playbook: Putting AI to Work for In-House Legal Teams (April 2026). Details how legal departments use AI for contract lifecycle management and establishing legal data readiness.
2. Thomson Reuters Institute, Artificial Intelligence and Law: Guide for Legal Professionals (August 2025). Tracks the rapid adoption of GenAI in professional services and highlights its core use cases in document review and research.
3. Bloomberg Law, AI Tools for Lawyers: A Practical Guide (2026). Provides a breakdown of how attorneys use agentic AI for drafting, clause comparison, and the ethical considerations involved.
4. Association of Corporate Counsel (ACC) & Everlaw, GenAI and Future Corporate Legal Work: How Ready Are In-house Teams? (2024). Highlights the preparedness gap, noting that only 42% of in-house legal professionals felt prepared for the impact of GenAI.
5. Bloomberg Law, Building Your Company's AI Governance Framework to Reduce Risk (April 2026). A step-by-step framework for in-house teams establishing enterprise AI policies, device management rules, and vendor due diligence.