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AI in the legal profession

Everyone's Adopting AI. The Rules Are Still Catching Up.

GCs at a recent L Suite roundtable agree: legal teams are adopting AI faster than regulation can keep up. Here's what 20 legal leaders had to say.

Earlier this month, Caitlan Rocha, Ivo’s In-House Counsel, led a roundtable of general counsel at The L Suite’s 2026 Legal AI Conference. A few years ago, the conversation around AI in legal centered on one question: Will it replace lawyers? Today, that debate has largely disappeared.

Instead, legal leaders from industries like financial services, healthcare, tech, and media spent the session discussing something much more immediate: how to leverage AI to keep pace with an ever-growing volume of legal work while protecting their organizations.

The workload that won’t stop increasing

The conversation Caitlan led centered on how fast the work is piling up, and how thin legal teams are stretched trying to keep pace. Several leaders described feeling buried under the sheer volume of work. It's not hard to understand why. Like we often say at Ivo, everything starts with an agreement. You can't hire an employee, purchase software, engage a vendor, or sell a product without a contract. And as companies grow, so does the number of counterparties they manage.

Ironically, many of the technologies companies adopt to become more efficient generate even more contracts to review. Every new software category brings new vendors. Every vendor relationship comes with its own MSA, NDA, security review, data processing agreement, and procurement process. Legal teams are left trying to solve an impossible equation: workloads continue to grow while resources largely don't. At the same time, every function around them increasingly assumes AI has already solved the problem.

“Just use AI,” right?

At this point, most legal leaders have moved beyond asking whether AI can help. They know it can. Many organizations have even mandated AI adoption to improve productivity across the business. But for legal and compliance leaders, the challenge isn't whether to use AI; it's how to do so responsibly.

“A number of them told me they felt like they were building the plane while flying it,” Caitlan says. “We all follow the few relatively clear boundaries that have emerged: don't cite a case that doesn't exist, don't upload privileged documents to a public chatbot.” Beyond that, there are few established standards, and no clear timeline for when a comprehensive governance framework will emerge.

While AI regulation continues to evolve, there is still no comprehensive governance framework that answers many of the practical questions legal teams face every day, including how contract data should move through AI systems, what governance looks like in practice, or what "good" AI adoption actually looks like. For companies in regulated industries, that uncertainty shapes every evaluation. Legal teams aren't just deciding whether a tool is valuable. They're documenting why its use is appropriate, how risks are mitigated, and how those decisions can be defended as regulatory expectations continue to evolve.

Because there are so few governance frameworks in place, companies have established their own AI governance policies, but many were written out of an abundance of caution and are too rigid to reflect the actual work employees need to do—a direct clash with employer AI mandates. As a result, employees, including lawyers, are working around those policies already simply to keep up with the workloads they're expected to manage. Many companies are now rewriting their AI policies because the first draft didn’t reflect how people needed to work.

We’re all figuring it out together

If there was one reassuring takeaway from the discussion, it was that no one is navigating these challenges alone. Every company is grappling with the same AI growing pains: balancing innovation with security, and productivity with governance. Staying at the forefront of technology while trying to stay compliant and secure is incredibly difficult.

“Nobody in the room claimed to have the answer,” Caitlan says. “What they had in common was the recognition that they're adopting AI to deal with the increased workload, but they’re doing so without the familiar guardrails, decades of precedent, or fully developed governance frameworks to demonstrate they’re doing it correctly.”

That may be the biggest shift of all. The conversation is no longer about whether AI will replace lawyers. It's about how lawyers can thoughtfully adopt AI to better support their businesses while building governance that will stand the test of time.

There isn't a tidy ending yet. The technology is evolving faster than the rules, and every legal department is learning in real time. But if the roundtable made one thing clear, it's that legal leaders aren't trying to solve these questions in isolation. They're sharing experiences, comparing approaches, and learning from one another because, for now, that's how the profession moves forward.

Solving the Contract Visibility Crisis

There’s a high chance that the contracts your team signed last quarter are already invisible to your business. While they may be stored in the cloud, in a shared folder, or in a CLM, you still can’t easily extract information from them. This is because "stored" and "findable" are two different things, and “findable" and "understandable" are even further apart.

To solve this, contracting teams have invested heavily in filing, storing, and tagging systems. However, none of these so-called solutions fix the fact that it is still extremely difficult to see what the business has already agreed to; in other words, what the contracts in these expensive storage systems actually say. That lack of information extraction has real costs; companies need to know what their obligations are, and they rely on their legal and contracting teams to be able to quickly get them answers. If those teams can’t answer in a timely way, there’s the risk that the rest of the organization moves on, making decisions independently, without that precise contractual data. Decision-making without all the relevant information exposes the company to significant risk, which, of course, the legal department will be obligated to deal with later.

Why this is a strategic problem, not just an operational one

In-house legal teams are increasingly expected, and want, to be a strategically important arm of the business. They can offer informed views on crucial business matters like risk exposure, contractual leverage, and how the company's position compares to market norms. But doing so requires the ability to answer specific questions about the business's contractual positions quickly and at scale, questions such as:

• What are our standard liability positions across our customer base?
• Which contracts have change-of-control provisions that would be triggered by an acquisition?
• If a regulatory change takes effect, which agreements put us out of compliance?
• What's our total uncapped liability exposure across the vendor portfolio?

These questions come up on occasions like board meetings and M&A due diligence, where legal guidance is sorely needed. Unfortunately, when legal departments can't answer these questions quickly, the business thinks they’re being slow or commercially disconnected. However, the real issue is simply that they don’t have the right tools for the job.

"Our problem is that folks can't find their contracts. They do a search and even if they filter it down, it gives them essentially everything under the sun and they're not entirely sure what's the most up-to-date contract." - Lawyer, Fortune 500 Company

Lawyers know the time cost of answering these questions when information in contracts can’t be easily found. Ivo's recent research study revealed that 80% of legal teams spend at least an hour every week manually searching inside agreements for this type of business-critical information, and 14% spend 10 hours or more: that’s a senior lawyer's entire working day, every week, spent on information retrieval rather than analysis or judgment. Every hour spent searching for contract information is an hour of a lawyer's time not spent analyzing risk, advising on a commercial decision, or helping the business think ahead. Legal teams are kept reactive by software that should be helping them to be proactive.

Contracts are your operating system

The root of the problem is that not very many people, and certainly not many software providers, understand just how critical contracts are to a business. Every significant commercial relationship, whether it's customers, employees, suppliers, partners, or lenders, is governed by a contract. Those contracts define what a company can and can't do, what needs to be paid and when, and what happens when things go wrong. They're the operating system that your business runs on, and if your business can’t effectively read or understand that operating system, that creates a gap between what a company has committed to and its ability to surface and act on it. That’s the real risk your business faces: one we’ve identified as a contract visibility crisis.

"Probably every big company is the same. The whole contract situation is a mess. Our CLM is a mess. We're looking at a dumpster of documents, some are linked, some are not linked, some are complete, some are not complete." - Attorney, Fortune 100 Company

The industry has spent decades only treating the symptom of this crisis, with paper contracts being moved to filing cabinets, then to the cloud, and then to CLMs that added metadata and workflows. However, each generation made storage incrementally better without addressing the actual issue: nobody can read the contracts at scale, quickly, without manually extracting the information clause by clause.

Why AI has changed everything

Reading a contract the way a lawyer does (understanding concepts, following cross-references, and spotting what's unusual) used to require pure human review. However, large language models have changed that; especially since the language in contracts is precise, structured, and pattern-based, making it well-suited to be analyzed by AI.

Initially, early LLMs could produce contract-like text but couldn't reliably comprehend an existing document. The next generation of tools could answer simple questions but were prone to hallucination and lost coherence across long documents. GPT-4-class models made reviewing a single document viable, but connecting a particular clause to its implications elsewhere in the agreement still required a specific prompt telling the system where to look.

But in the last year, models have acquired the ability to conduct multi-step reasoning across long, interconnected documents. AI can now identify relationships between clauses, flag deviations from market norms without being told where to look, and treat a master agreement, its amendments, and every governed statement of work as one coherent picture. This progression turns what once was a multi-day review of a supplier's termination rights, pricing protections, and liability caps into a query answered in minutes, with citable sources included. It lets a marketing team find which customers granted them logo rights, without getting their legal or contracting teams involved until the legal judgement stage, and lets a finance team ask which agreements carry uncapped liability and receive a downloadable table, instead of having to ask legal to make a quick, educated guess.

What’s possible with contract intelligence platforms

Seeing this progression of AI in practise, Ivo Intelligence, our contract intelligence product, illustrates what a contract intelligence platform is capable of when it accesses a portfolio of agreements:

1. AI Fields pull any structured data points, like complex termination provisions, directly from a contract repository in real time. No manual tagging is required at all.
2. Natural-language queries let teams build information tables like a CFO-ready “financial dashboard” just by requesting, in plain language, the information they need.
3. Structured extraction can triage an entire portfolio of contracts against a specific standard, such as GDPR compliance, and return a sourced, step-by-step summary instead of having to undertake a manual review project.
4. Relationship mapping automatically detects how amendments, novations, and statements of work relate to a main agreement, and assembles the prevailing terms into a single, current view.
5. Dashboards surface portfolio-wide provision patterns like auto-renewal rates and liability caps, so institutional knowledge doesn't live only in one person's head.

The takeaway

Solving the contract visibility crisis requires the business to read its own operating system the moment it is needed, at scale, and without waiting on a manual review. The good news is that the intelligent functionality to do this now exists, meaning legal and contracting teams finally have the tools to match how much they're already expected to know about the business they support.

What is a Legal Engineer? Inside Law’s Newest Career Path

Most lawyers enter law school with a fairly clear picture of the career paths ahead. For most, their career path can go in one of two directions: they can either join a law firm, where they’ll grind as an Associate until they make Partner one day, or become an In-House Attorney. Both have their pluses and minuses, and are equally well-established pathways. Today, there is a third option: the role of Legal Engineer. The rise of AI-powered legal tech has brought with it a role that previously didn’t exist, and there’s a lot of discussion about what it is and what it means for the legal profession.

Alexis Nicholas, one of Ivo’s Legal Engineers and In-House Attorneys, believes she has seen the future.

“One of the best parts about Legal Engineering at an early-stage company is that it’s such a flexible and changeable role,” she says. Alexis describes her role as having four focus areas:

• Customer Legal Engineer: she builds and rolls out playbooks that encode a company's contract positions and fallbacks; works through customer issues and challenges; assists with how customers can use AI in their legal and contract workflows; and carries out training and implementation sessions.
• Sales Legal Engineer: she demonstrates how Ivo’s product solves day-to-day contracting and legal problems; hosts webinars and AI awareness sessions; and helps educate on integrating AI into legal workflows.
• Product & Engineering Collaboration: she works closely with the engineers and product teams to build our product; builds test cases for new features; gives feedback on model outputs; and directly helps shape the roadmap.
• Legal Counsel Work: she still gets to be “a lawyer” in the traditional sense; reviewing and negotiating Ivo's own SaaS agreements, DPAs, NDAs, and various contractor/vendor agreements.

“The role will, of course, be different at different organizations, and the areas of responsibility will change based on what the business needs,” Alexis notes. “That’s what makes it so interesting and varied.”

Alexis points out that with these four different focus areas, she’s still very busy, but it’s a different, more directly rewarding form of busy than she experienced in traditional legal practice. “It’s the nature of startups,” she says. “Companies at this stage have a ‘do what it takes’ energy, which gives Legal Engineers much more scope to be creative and wear a lot of hats. Of course, there’s an infinite number of things to do, with the potential to keep doing more if you want to. But it’s a choice to be here and build, and I feel the excitement of being able to still be a lawyer and use my legal skills, but in a much more creative and novel way. It’s hugely fulfilling.”

To Alexis, one of the most important aspects of being a Legal Engineer is the energetic and resourceful culture at a startup and the immediate results she can deliver within it. “At a firm, being busy usually meant deep, narrow focus: all your hours spent becoming an expert within one practice area. But at Ivo, being busy means switching between different types of work in the same day: negotiating a contract, working on a product pitch, testing a new feature, joining a customer call, running a demo, prepping a webinar, initiating a new internal workflow; and that variety changes how the hours feel. It's less like grinding through billable hours on similar tasks, and more like constantly learning and being introduced to new directions. It’s more energizing because I can see the direct impact of what I'm doing, rather than working on a specific, siloed matter that your team has been helicoptered-in for.”

Legal Engineering is emblematic of a shift that’s happening in the legal profession: a slow but undeniable change in how the value of a lawyer’s work gets defined. Before AI, and in many legal roles, lawyers are, as Alexis puts it, “just a lawyer,” e.g., working on specific matters that lead to an outcome, whether that’s closing a deal, signing a transaction, or winning a case. The work lawyers do to achieve these outcomes is, albeit hugely important, a small part of a larger whole, generally in one area of specialization, and their relationship to the result for their client is remote at best. In-house attorneys get closer to that outcome, sitting inside the business and seeing decisions play out for their company in real time. But the work itself is still bound by traditional law: contracts, risk, compliance.

But as a Legal Engineer, Alexis gets that same privity to the business, but with a much wider remit, having exposure to types of work she wouldn’t typically get in a traditional legal role — public speaking, sales calls, demos, recruiting, marketing campaigns, product development meetings, and working with software engineers—and certainly not this early into a new position. The value Alexis brings is her judgment and legal knowledge, put to work across product, sales, and customer relationships, not just contracts. “It's a huge amount of learning, responsibility, and work that I'd never get to do as just a traditional lawyer,” Alexis notes. “I don’t see it as leaving the law at all, as not only do I still do legal work, but I’m also still embedded within the practice of law, just in a different way.”

All in all, a Legal Engineer’s role is a combination of legal and technical expertise, with a healthy dash of startup dynamism. And it isn’t going away. “We’re at a very interesting time in the world with AI,” Alexis says. “It feels like this century’s dot-com boom, and being a Legal Engineer is a huge opportunity to be at the heart of it. Legal AI is one of the fastest-growing corners of legal tech, so this hybrid legal-plus-product-plus-technical skill set will continue to be in demand.