The Aldo Group, a leading multinational retailer specializing in shoes and accessories, has chosen Ivo to accelerate and streamline its review contract. The in-house legal team was excited to select Ivo to ensure consistency and speed across all of its contract review workflows.
Retailers deal with dozens of contracts, if not more, on a daily basis. And for a retailer that operates across multiple countries like the Aldo Group, a universal approach to documents is very important. Ivo’s implementation of custom playbooks with our customers’ own standard terms means that customers can ensure consistent application of their own positions every time. And of course, having the standard positions already implemented in Ivo means the tool can detect and flag deviations from those positions for a lawyer to review quickly and easily.
We are proud to work with The Aldo Group as they re-imagine their contract workflow for speed and consistency across their global team, said Min-Kyu Jung, the co-founder and CEO of Ivo.
Ivo’s contract review platform allows legal teams to review contracts up to 75% faster while maintaining their unique standards and positions. Ivo reads and interprets complex contracts exactly as a lawyer would, providing surgical redlines directly in legal teams’ existing workflows.
A growing number of retailers are implementing Ivo to make their contract workflows simpler and more consistent. Ivo delivers accurate, precise redlines in a fraction of the time it takes to manually review contracts, helping legal teams work smarter, not harder.
Learn more about how Ivo could help your company transform contract review here.
Backblaze, the leading open cloud storage platform, has selected Ivo to streamline its contract review workflows. The company’s in-house legal team will use Ivo to end time-consuming manual reviews and create efficiency and scale as the company continues to grow.
The legal team at Backblaze wanted to solve the often laborious contract review process. In-house legal teams are interested in simplifying repetitive processes like reviewing counterparty redlines or third-party paper. Ivo can also generate issue lists and executive memos for large deals.
Min-Kyu Jung, CEO & Co-Founder of Ivo, noted:
“We are proud to partner with Backblaze as they embrace AI to transform legal workflows. By choosing Ivo, their team is investing in efficiency, effectiveness, and the ability to focus on the highest-value outcomes.”
Ivo’s platform enables legal teams to review contracts 75% faster while maintaining their unique standards and achieving time-to-value through rapid implementation. In-house legal teams appreciate Ivo’s purpose-built AI that understands complex legal documents with lawyer-like precision. In other words, Ivo’s AI understands your contracts as a lawyer does, dramatically speeding up contract review without compromising accuracy or context.
The efficiency benefits that come from implementing a modern contract review process include building a strong foundation to scale and increase strategic impact. In addition, Ivo’s custom playbooks offer surgical redlines and rapid, consistent insights that accurately reflect your legal standards.
Learn more about how Ivo is partnering with legal teams across industries.
After an extensive evaluation process, Reddit selected Ivo for its contract review and repository capabilities. With Ivo, Reddit’s legal team will streamline its review processes, improve contract insights, and drive business impact.
Traditional contract management systems are difficult to maintain and often rely on manual tagging, which is expensive, time-consuming, and prone to error. Attempts to automate this with CLMs have largely failed, as traditional CLMs lack robust search and data retrieval capabilities.
Contract management should be efficient, insight-driven, and effortless to manage. Ivo’s purpose-built AI engine, AiRE, powers its Repository: automatically extracting, linking, and clustering contract data without the need for manual tagging, setup, or maintenance. Legal teams can instantly query their contracts for insights that inform strategy and strengthen operations.
In addition, Ivo’s native integration with Microsoft Word and other tools legal teams already use minimizes workflow disruption and delivers rapid time to value. The ability to work within familiar systems makes adopting Ivo effortless.
“Technology leaders like Reddit recognize that legal teams have a strategic impact on their business,” said Min-Kyu Jung, CEO & Co-Founder of Ivo. “Reddit’s investment in Ivo is an investment not only in speed and efficiency, but also in insights that drive powerful business outcomes.”
Companies that use Ivo see up to a 75% efficiency gain in contract review—an advantage that’s critical in industries where speed defines success.
Ivo is transforming contract review and management for companies across tech and beyond. Learn more about Ivo’s impact.
Lemonade, America’s top-rated insurance company, has joined the rapidly expanding list of companies using Ivo. Ivo’s AI-powered contract review tool will allow Lemonade to generate precise, accurate redlines while reducing the time spent manually reviewing contracts.
Like many in-house legal teams, Lemonade needed a solution to speed up its laborious, manual contract review processes. Lemonade’s in-house legal team evaluated many AI-powered solutions before choosing Ivo. Ivo’s platform received top marks for accelerating their contract review processes by 75%, while achieving fast time-to-value with implementation that takes just one to two weeks. In addition, Ivo’s custom-built playbooks offer rapid, surgical redlines and consistent insights that accurately reflect each company’s unique legal standards. Lemonade will use Ivo to, among other things, review vendor agreements, including redlines of their form agreements.
Min-Kyu Jung, CEO & Co-Founder of Ivo, noted:
“We are proud to partner with Lemonade as they embrace AI to transform their legal workflows. By choosing Ivo, their team is investing in the ability to focus on the highest-value outcomes and to achieve strategic impact.”
In-house legal teams appreciate Ivo’s purpose-built AI, which understands complex legal documents with institutional knowledge and surgical precision. In other words, Ivo understands your contracts as a lawyer does.
Legal teams—specifically those in the financial services and insurance industries—choose Ivo to enhance and standardize their agreement review workflows. Ivo’s use of bespoke playbooks promotes custom results with rapid, surgical redlines that accurately reflect an institution’s unique legal positions.
Want to learn more? See how Ivo can help you achieve similar results.
At Ivo’s inaugural customer advisory board (“Visionaries Board”) meeting, legal leaders from top companies, including Canva, Pinterest, Intel471, and others, came together to discuss the future of legal AI.
The conversation covered everything from risk management and redlining to speeding up contract review and rethinking how legal teams maximize their value.
What became clear? AI isn’t about replacing lawyers—it’s about reducing the time spent in the tedium of contract review to enable lawyers to spend more time focusing on strategic initiatives that drive business forward.
Here’s a look at the top takeaways from the Visionary Board’s first session and what it means for legal teams navigating the AI-laden path ahead.
The Visionaries Board emphasized that the goal behind implementing AI is not just efficiency, but the elimination of low-value work altogether.
One Visionary Board member specifically noted, "It’s not just about helping me do a task faster; I want to remove the task entirely."
Rather than manually reviewing every line of a contract, redlining a routine NDA, or triaging vendor forms, lawyers want AI to handle the full review and surface the provisions that pose the biggest risks or could impact strategic business outcomes. Some even imagine a future where traditional redlining fades away entirely, replaced by dynamic risk scoring that enables teams to act on priorities, not sift through edits.
A clause that scores 90% or higher on an acceptable risk framework? Route it to a junior reviewer. A liability cap significantly below the acceptable threshold? Escalate it to corporate counsel.
This shift in contract review processes could redefine how teams assess legal exposure and allocate time.
How lawyers use AI varies widely. Junior lawyers may default to over-redlining to capture every nuance or demonstrate competency, while seasoned attorneys may be more apt to accept low-risk deviations to their playbook to expedite deals.
That’s where AI can help–by providing junior lawyers with the same institutional knowledge as their experienced peers, embedded in a standardized playbook. The goal isn’t just speed, but alignment and clarity.
Context matters. Style matters. No two companies—or legal teams—approach risk the same way. That’s why customization is key.
Visionary Board members emphasized the importance of tailoring AI solutions to reflect how their organizations already operate, such as fallback clauses by product, risk profiles by team, or stylistic playbooks by user.
At its best, legal AI isn’t generic; it’s purpose-built to mirror your unique approach to contracts, risk, and business goals.
Visionary Board members also made it clear that the toughest part of legal transformation isn’t the adoption of the technology itself, but ensuring that it can co-exist with the judgment and reasoning that only legal teams and leaders can provide. Aligning stakeholders on definitions. Agreeing on risk thresholds. Positioning legal as a strategic partner, not a blocker.
AI can help support this shift by providing metrics, dashboards, and heat maps that highlight how legal contributes to efficiency, alignment, and risk mitigation—not just compliance.
But there are limits. Resoundingly, Visionary Board members agreed there are tasks AI shouldn’t do; it shouldn’t calibrate risk tolerance for business teams, navigate internal politics, or override human decisions. The role of AI is to enhance the legal team’s impact, not replace human judgment.
Whether you're exploring legal AI for the first time or scaling an existing implementation, here are five recommendations from the Visionaries Board to guide the way:
1. Start small, but smart. Focus on repetitive, low-risk tasks first, like NDAs or vendor reviews, and build trust with AI from there.
2. Codify your playbooks. The more clearly you define your preferred and fallback provisions and risk thresholds, the better AI can assist.
3. Invest in customization. Legal teams should control style, tone, and escalation logic, because risk isn’t one-size-fits-all.
4. Shift the metrics. Don’t just measure speed. Measure alignment with risk profiles, reduction in review cycles, and effectiveness.
5. Empower, don’t replace. Legal AI should enable attorneys to be more strategic, not take the human out of the loop. Think augmentation, not automation.
The Ivo Visionaries Board meeting highlighted how collaborative and forward-thinking our members are. These legal leaders aren’t just giving feedback; they’re shaping the future of legal AI. From model design to workflow integration, the Visionary Board members' insights directly influence how we build Ivo. As AI advances, expectations are shifting, too, and tools like Ivo are on track to evolve into peer-level teammates.
The consensus was clear – AI should surface what matters and never override human judgment. Legal teams want to spend their time focusing on strategic outcomes and assessing risks, not tracking changes line by line. We're grateful to our Visionaries Board for pushing us to build Ivo with clarity, context, and real-world impact in mind.
The current wave of legal technology is entering into its next phase and we’re continuing to see unprecedented speed and scale with AI leading the way. Do lawyers need to get on board with this evolution now at the risk of getting left behind? Or is there still time to wait until the dust settles?
Douglas Sayranian, General Counsel at Intel 471, gives us his perspective on this sea change moment for lawyers and how legal leaders can prepare for the inevitable shift.
When I finished my undergrad at the University of Michigan, the world was in the throes of the global financial crisis. Three years of law school gaining a valuable baseline skillset was an attractive way to make use of the time while economies recovered and job opportunities rebounded.
After finishing my J.D. at Northwestern, I immediately moved to NYC for my first associate position at Kirkland & Ellis doing corporate M&A. Over the course of the past decade I’ve also worked at Latham & Watkins, Baker Hostetler, and most recently Reed Smith all here in NYC doing private equity, public company, and cross-border M&A.
When I was approached by Intel 471 in 2022 to become general counsel, I ultimately decided to step away from private practice because of the opportunity to move from advising decision-makers to being one. I wanted to expand my knowledge and experience while working alongside Intel 471’s leadership, and deepening those relationships has been incredibly rewarding.
Intel 471 is a cyber threat intelligence company, which in many ways makes us a quasi-journalistic business while also at our core being a SaaS. As general counsel, the scope of my responsibilities is much wider than in private practice, extending far beyond legal matters to include significant involvement in compliance, business operations, sales operations, human resources, and strategy.
With the explosion of the LLM/AI industry, I’ve started taking on much more work in the thought space related to those areas. Ancillary to some of the new challenges and opportunities our business identified in those areas, I’ve had to begin diving deep to get educated on the technology and the many challenges and opportunities it raises for the law, business, existing technology and infrastructure, culture, society, and ethics.
Technology–specific computer technology related to the creation, use, and transmission of information–is an omnipresent but asymmetric force. In many ways the effects of advancements in AI technology have been diffuse and disparate. I think the most obvious example of this is in the modalities available to us–they are much more diverse, sophisticated, and intuitive (but also complex) than ever before. But at the same time, access to the underlying technology, and the sheer cost of getting started, means that the physical infrastructure is concentrated in the hands of a few companies. It’s important for my company–and any company–to be aware of the asymmetry here, since it means that really digging into the details is essential.
AI will improve both in terms of fundamental capabilities and in the identification, refinement, and adaptation of specific use cases. The first wave, that I think is already washing over us, is the use of AI to streamline or eliminate organizational or administrative processes that are inefficient or annoying for lawyers. For example, grammatical edits for consistency across a large contract, or the first “red flags at a glance” review of a markup based on a human-curated playbook. Similarly, AI can be incredibly powerful in creating efficiencies when conducting due diligence.
That said, I think it will take some time before lawyering shifts (as it inevitably will) to be dominated by judgment, expertise, and wisdom-based work. Much like how redlining software eliminated the need for lawyers to know how to blackline with a ruler and pencil, AI in the legal space will eliminate the need for certain skills. I’m wary of skill erosion in areas like drafting, where insight and creativity result in brilliance when applied to a foundation of fundamental competencies like logic and grammar. But I am excited for the prospect of being able to eventually implement conceptual changes in documents without having to input them manually. There’s a tradeoff here, since the ability to draft well from scratch provides the foundation for being able to craft meaningful instructions to an AI tool and adequately evaluate the results.
Lawyering is a person-focused profession, so what will endure is the core need for lawyers on a direct human scale to provide advice and exercise judgment on the intersection between human action and legal frameworks. However, the scale and function of legal services will both expand and contract in different areas. Matters subject to a legal touchpoint will expand as operational and monetary costs decrease, but fewer lawyers will be needed to perform a greater volume of work. As a result, I predict that lawyers in private practice and in-house will need to invest more development into skills that advance, and originate in, thoughtfulness and creativity.
A lot of law firm lawyers are “rock stars” because they bill a large number of hours, executing tasks like managing project teams, conducting research, and generating or editing work-product for deals or disputes. New expectations for efficiency will force lawyers to emphasize the value they bring to the table when it comes to emotional intelligence, communication skill and commercial judgment, such as forging consensus, aligning incentives, contextualizing decisions and information in industry-specific and company-specific knowledge, and removing unnecessary bureaucracy while focusing on improving and maintaining necessary standards and safeguards.
Less complex legal work will become truly productized with lower barriers for people who need assistance. For example, forming an entity like a corporation or LLC has become quite easy in many states simply because of the internet, and with AI a person will be able to more readily understand and complete the formation process and customize the provisions on governance.
The quality of the outcome will more consistently match what could be achieved by a human drafter.
On the other hand, more complex legal work will shift to become more common but also more bespoke–when an AI can handle some of the high-volume matters like file organization and due diligence, then there will be more resources available to dedicate to the creative aspects of counseling clients. It will also be efficient to engage in optimization efforts that might have previously presented a bad value proposition. A storied company with decades of records might reach a tipping point where using AI to digitize and organize warehouses of files is finally cost-effective, and it may also use the newly organized data to deploy contracts with its customers and suppliers that custom-fit the incentives and dynamics of the relationships to the distinct goals and risks involved.
I live in Brooklyn with my girlfriend, Tara Simoncic, and our cats. She’s a conductor and does a lot of work with orchestras and ballets around the world (including for the Joffrey Ballet’s Nutcracker in Chicago in December, which was of course excellent). She and I also do a lot of work for Cats In the City (NY). We often get calls to go help stray cats or kittens and make sure they get veterinary care before going to an adoption center or foster home. It’s a lot of work, but very rewarding.
Outside of that, I tend to read a lot about a wide variety of topics. I’m currently on an AI-focused reading list, but I’ve also picked up some books on psychology and marketing & design as well as a few high fantasy and science fiction novels.
My current recommendations for books in the AI space are The Coming Wave by Mustafa Suleyman, Nexus by Yuval Harari, and AI Ethics by Mark Coeckelbergh.
Society is currently focused mainly on AI technology, but soon quantum computing and biocomputing will join the fray and play a significant role in people’s day to day lives. I’m immensely curious about how post-quantum cryptography (PQC) and areas like omic analysis, bioinformatics, and bioengineering will unfold.
Chances are that you’ve been reading up on, actively implementing, and/or already using tools and technologies to help you and your legal team work smarter and scale. The million dollar question moving forward will be “how do we build the right legal technology stack that’s right for us?” Natalie Kim, former Head of Commercial and Privacy Legal at Intrinsic, an Alphabet company, joins us to explore this question and delve deeper into the impact of AI as the legal tech stack evolves.
I’m drawn to problem-solving using interdisciplinary perspectives, and continuous learning. Practicing as a lawyer allows me to do both. In particular, with new technology where the law hasn’t “caught up yet”, how can innovators win in the market while doing right by their stakeholders? I’ve been exploring the answer to that question my entire career, first at Bay Area law firms representing technology companies (all the way from startups in the proverbial garage to the FAANG-sized companies) and then working in-house. I’ve managed billion-dollar deal desks for large established companies, and built contracting and privacy compliance programs from scratch for earlier-stage startups. What I enjoy about the journey is that legal advice is never cookie-cutter, and it’s more about getting to know your company and together building a custom solution tailored to their risk tolerance, industry vertical and other unique parameters.
I’m also a systems thinker and a nerd about creating processes that are scalable and nimble. In my last role, I also managed the legal ops function, and there got to think in-depth about how to minimize the pain points in processes like the sales motion and privacy compliance. It’s amazing to experience this moment in legal tech where the annoyances we chalked up as part of being lawyers are finally being tackled in a serious way, and that makes me optimistic about legal tech as well as lawyering as a whole in the future.
Strength of cross-functional relationships - I really believe that lawyers are at their best when they have built trusted relationships with their clients and, when confronted with a problem, they’re thinking “let’s get legal looped in early” as opposed to trying to figure out ways to keep legal away.
Another factor is the effectiveness of your legal operations (whether you have a formal legal ops team or not, you are still doing legal ops) and how seamless your legal processes are. How efficient are they? Is your team proactively taking steps to continuously improve and gauge colleagues’ sentiment about how well they’re working? The contracting process particularly comes to mind because every company has one and it touches nearly every team. It’s integral to the customer experience and how it affects the perception of your company as a result.
When I started in my legal career, “legal tech stack” was basically just IT, and the extent of attorney involvement was mostly confined to using whatever software that was provided. The bleeding edge of digital transformation was still whether the process could be managed end-to-end using a computer as some attorneys still preferred to scan in manual markups. Every organization had its own set of tools, but I’m not sure if there was an expectation for them to play well together and lawyers had a mostly passive relationship with the tools they were being asked to use.
The current idea of a “legal tech stack” borrows from our engineering counterparts who try to build a “tech stack” that is efficient, plays well with adjacent components and is delightful to use. It comes from legal teams trying to reimagine the relationship they have with their tools as increasingly both the number and dependency on various software to execute legal tasks increase. Part of it is digitizing tasks that existed from time immemorial (like billing clients) but another part is utilizing new tasks that were previously unimaginable (like deriving real-time insights from a contract base of thousands). As the number of tasks and tools increase, it becomes much more important to make sure the tools are operating well with each other with intentional integrations that increase efficiencies as well as cost-effectiveness.
All of this takes a lot of work, doesn’t really sound like tasks lawyers traditionally do, but requires some depth of knowledge on legal work. This is where in the last decade or so, legal ops has grown out of this vacuum. We’re living through an evolution of this function from a pure legal support function to this combined chief-of-staff, COO type counterpart to the GC that handles not only an intentional development and curation of the legal tech stack, but budgeting, operational efficiencies and other special projects. I’m really excited about this development because it signifies maturation of legal teams as a department with serious focus on efficiency, enhanced client experience and cost effectiveness - all of which were traditionally gripes against the legal department. Coming back to the legal tech stack, these developments have transformed the lawyer’s relationship with the software to one that is more proactive - the best legal teams have an ongoing iterative development of the legal tech stack to accommodate changing needs within the team and asks from clients.
For any legal team, making legal tech stack decisions that are well-tailored for their specific needs should be a top-of-mind item. A commercial counsel might use the CLM every day and need it to work flawlessly with invoicing and billing tools, CRMs and e-signature integrations. A privacy counsel’s compliance dashboard might be linked to product documentation tools that product and eng teams use. These tools need to be integrated well in order to make the high-volume tasks seamless and continue executing without disruptions. A GC would want to work closely with legal ops to make sure that legal tech stack decisions are cost-optimized to defend budgets year to year. It impacts every team member and will only increase in importance as more tasks migrate online and are made possible with AI.
It’s easy to forget, since we’ve been talking about AI nonstop, that it’s still very early days with AI. I think there’s still a ton of low-hanging fruit that today is being handled with very manual, repetitive work that is contributing to attorney burnout and needless errors. We’re already seeing seismic shifts in how contracts are managed and negotiated, and within the next few years, those AI-first, early adopter legal teams will influence what will be considered best practices for legal teams as a whole. Zooming into one really specific problem as an example - today many teams still have a big word document (or worse, many fragments of word documents) as their contract playbook. Attorneys waste a lot of time trying to find it, update it and get the information they need. All that wasted time could be drastically reduced if it lived on one, evergreen platform. A good AI contracting tool can do that, while taking into account all of the forks that we care about (like custom provisions depending on geo).
Another exciting area where AI is changing the game within legal is the “legal co-pilot” - lawyers are already using free options like ChatGPT extensively to get quick questions answered and/or “first stabs” of documents started. But, generic models are limited because they aren’t trained on legal-specific information for legal-specific purposes. Providers are starting to do just that, and are offering options where you can “teach” it the information about your company that results in fast tailored output. I’ve seen people have copilots do benchmarking or research projects where large amounts of information need to be digested and classified fast - essentially, something that would have taken an attorney a week can now be done within a few hours.
Better minds than mine are pondering the answer to this question, but I’d be willing to guess AI is going to be neither all good nor all bad. In terms of “maybe bad” - as much as we gripe about it, part of legal training did come from all that monotonous, repetitive work they had us do as juniors. Reading voluminous material, summarizing said material, writing about that material. If AI is doing all of that for us, I’m not sure many up-and-coming lawyers will be incentivized to go the hard way in learning those skills. In 20 years, if an AI contracting tool had an outage, does that mean all contracting comes to a standstill because noone knows how to draft anymore? I hope not!
In terms of “maybe really good” - I think AI is an amazing teacher (when used right, for the right purposes). Today’s students can study much more efficiently (pre-2022 we had to read entire casebooks, or look up summaries online), and even practicing lawyers can ask AI all of the silly questions they’d be afraid to ask someone else. I still remember being a first-year associate wondering what an “indemnity” is - and now we can just ask ChatGPT to “explain it to me like I am a 7 year-old.”
I mentioned I can do interdisciplinary problem-solving and continuous learning as a lawyer, and the same is equally true as a parent. I have 7 and 4 year old boys and a 19-month old girl at home so there’s a lot of code-switching, trying to tailor to different interests, languages, learning styles and capabilities. It’s the same muscle lawyers use all the time. I’m also training for the Seattle Half Marathon, and also have been volunteering as a board member at Cancer Lifeline, which is a Seattle-based nonprofit dedicated to providing better support to cancer patients.
In June, I resigned from my job and started a sabbatical. My goals were to refuel my tank, reconnect with loved ones and recenter myself for my next adventure. Quitting with nothing lined up in a bad economy felt a little like jumping off a cliff, but it’s led to this incredibly serendipitous, rejuvenative period where I’ve been able to work on amazing projects (like authoring a white paper), advise innovative startups in the AI and legal tech space and most importantly, slow down and take stock of where I’ve been and where I’d like to go. I’m grateful for the many people who were willing to sit down with me and share their wisdom and career journeys, and it’s helped me change some of the less healthy habits I brought to work. If it’s a possibility financially,
I’d highly recommend mindful breaks as it helps you stay replenished and can even create new perspectives, all of which can help you in and outside work.
Check out the the latest white paper from Natalie Kim - AI Contracting Tools: A Buyer’s Guide
Large language models (LLMs) are both incredibly powerful and incredibly limited. On the other hand, Generative AI is a limited, nascent technology–the good news is that it is limited in certain predictable ways, and developing a familiarity with these limitations can help legal professionals navigate potential pitfalls when using the technology in their work.
CLM vendors dominated the event in 2023, and they did it in style. At the time, my only prior experience at a legal conference had been the Legal Innovation & Tech Fest in Sydney, and in comparison the glitzy booths sprawling across the exhibit hall of the Bellagio were a shock to my modest Kiwi sensibilities.
In 2024, CLM vendors were much more muted, eschewing elaborate sets and costumed mascots in favor of a more serious presentation style. Notably, there was an absence of the lavish parties that every CLM vendor seemed to be throwing last year.
It’s no secret that CLMs have been the primary legal tech beneficiary of VC dollars in recent years; the pullback of VC funding in CLM companies and its subsequent impact on marketing budgets were felt throughout the event. There were also indications that CLMs were losing their shine in other ways; Zach Abramowitz has previously questioned whether CLMs have reached Product Market Fit, and privately I heard similar comments both from other vendors and legal ops professionals.
These firms undoubtedly see generative AI as an opportunity to create new, more compelling experiences for users. Speaking of AI…
Detailed prompts yield better results. This is almost so obvious as to go without saying, but Generative AI is not completely magic—you do need to give clear instructions.
Including examples within prompts can significantly improve AI outputs. This technique is known as “one-shot learning” (if providing a single example) or “few-shot learning” (if providing multiple examples).
Encourage the AI to reason through its process step by step. Consider breaking down complex problems to their components parts and adding "let's think step by step" to prompts can enhance accuracy.
Framing the AI as an expert and assigning a specific role can improve the quality of outputs. For example, starting with "You are an excellent contract lawyer" can yield better results.
LLMs are prone to two categories of errors:
These commonly occur when the AI struggles with complex nested logic, such as exclusions to limitations of liability. Breaking down prompts into simpler, single-statement queries can help mitigate these issues.
These happen when the relevant part of the document isn't processed by the AI. To avoid this, users should narrow down the scope of their queries by only passing relevant passages of the agreement into the AI at a time.
We also suggest avoiding the use of LLMs for research tasks due to the risk of hallucinations and outdated information, particularly in cases where you cannot easily verify the AI’s output.
Min-Kyu highlighted three practical use cases for generative AI in contract review:
AI can check for correct clause references and consistent use of defined terms, significantly reducing tedious manual work.
Prompt: Identify and list any instances where a clause reference points to a non-existent or incorrect clause. If a reference is found to be erroneous, specify both what the incorrect reference is and, based on the context, suggest which specific clause it should actually refer to.
AI can flag terms that are generally unfavorable to the user’s position, helping to streamline the review process.
Prompt: You are acting for Party X. Review the agreement and provide a list of the top 5 provisions that are unfavorable to Party X and a brief explanation for why the provision is unfavorable to Party X. An unfavorable provision could be provisions that are particularly onerous to Party X, not market standard, and/or exposes Party X to significant legal or commercial risk.
AI can verify that agreements are consistent with predefined legal positions, providing a brief explanation for any discrepancies.
Prompt: You are acting for Party X. Review the agreement. For each of the requirements below, assess whether the agreement meets each of the requirements. Provide a brief explanation for why the agreement meets or does not meet the requirement.
1. Requirement 1
2. Requirement 2
3. Requirement 3
For more information on the above, check out our webinar replay here where we walk through these areas step by step.
We’ve seen technological advances change the way we work, and change the way we do business. What was at first a slow shift—the launch of legal research engines that allowed for easier research at your fingertips, e-signatures for easy signing of legal documents, cloud solutions for data and document management, the ability to be connected and work whenever, wherever—has now become a rapidly changing environment affecting every industry. As we adapt to these new environments, learning how to work smarter, not harder, as the saying goes, is critical to success, and one tool has been driving this change—generative AI.
Love it or hate it, AI is here to stay, and its applications are seemingly endless. AI technology has advanced to generative AI—machine learning that uses algorithms to create different types of content, including text, images, audio, and more. This shift is both exciting and a challenge for legal teams.
Using Generative AI for contract review strips away these issues. Large language models (LLM) are designed to essentially do what a human lawyer would do—but in a fraction of the time, including:
When legal professionals hand these tasks over to AI, they can concentrate on activities that are more complex, nuanced, and require human judgment.
Chances are, your legal team, like so many others, is being asked to do more with less. What’s more, the average lawyer spends upwards of 60 percent of their time drafting and reviewing contracts. Using AI for contract review is a way to free up valuable staff time.
In addition to that, using AI for contract review allows for improved risk management. Early detection is the best detection, and when legal teams can use generative AI as a second set of eyes during contract review, potential issues such as problematic terms, items, or clauses can be caught sooner rather than later, saving time and money, and also providing a streamlined process from the jump.
Like all technologies, AI can provide lawyers with significant leverage. Lawyers who are proficient with AI will discover that they can produce higher-quality work more efficiently and effectively than those who do not. Corporate legal teams in particular will find that they can accelerate critical processes across their company and position themselves as business enablers rather than blockers.
Connect with us now to learn how we can streamline your contract review process
