Automating GDPR Compliance

Irdeto initially relied on an external tool to maintain compliance with GDPR regulations, but found that their process was creating inefficiencies and contributing to poor data quality. Over the course of nearly 9 months, the Irdeto Legal Operations team partnered with internal business units to initiate new processes and create automated workflows within existing systems. The outcome has resulted in reduced time, costs, and efforts across multiple teams, as well as allowed Irdeto to work in-house, without reliance on an external tool.

The CLOC DEIB Council is committed to achieve DEIB successes that will ensure a more inclusive and equitable legal operations community for the future. In doing so, we celebrate the leaders who have paved the way. In celebration of Black History Month, here are just a few of those leaders:

Willie Mae Mallory – Often left out of the historical narrative surrounding the Black Power Movement is Willie Mae Mallory, a member of the Harlem 9, who fought for the right to send her daughter to a desegregated school in the state of New York.

Sojourner Truth – Abolitionist and women’s rights activist Sojourner Truth is best known for her speech on racial inequalities, “Ain’t I a Woman?” delivered at the Ohio Women’s Rights Convention in 1851.

Carl Stokes – Carl Stokes became the first African American mayor of a major U.S. city when he was elected mayor of Cleveland in November 1967. He later became a news anchorman, judge, and Ambassador to the United States.

Margaret Gardner – Many people are familiar with Toni Morrison’s Pulitzer Prize-winning novel, Beloved, but there is much less recognition given to Margaret Gardner, the woman who inspired Morrison’s novel. To learn more about Margaret Gardner, check out this Northern Kentucky History hour video, where they explore the woman behind the novel.

Virgil Abloh – The first Black Artistic Director of Louis Vuitton, Virgil Abloh is known for bridging the gap between streetwear and high fashion.

Kimberly Crenshaw – Kimberlé Crenshaw is a well-known scholar whose career has spanned several decades focusing on civil rights, critical race theory, Black feminist legal theory, race, racism, and the law. In 1989, Crenshaw coined the term  “Intersectionality,” which she explains by saying, “Consider an analogy for traffic in an intersection, coming and going in all four directions. Discrimination, like traffic through an intersection, may flow in one direction, and it may flow in another. If an accident happens in an intersection, it can be caused by cars traveling from any number of directions and, sometimes, from all of them. Similarly, if a Black woman is harmed because she is in the intersection, her injury could result from sex discrimination or race discrimination.”In short, Crenshaw’s theory should challenge us to think critically about how discrimination is compounded by the layers of one’s identity.

Leymah Gbowe – 2011 Nobel Peace Laureate Leymah Gbowee is a Liberian peace activist, social worker and women’s rights advocate. She is Founder, and President of the Gbowee Peace Foundation Africa, based in Monrovia.

Bayard Rustin – Civil rights activist Bayard Rustin, subject of the 2023 biopic Rustin, planned the 1963 March on Washington and was best known for his role as an adviser to Martin Luther King Jr.

Lorraine Hansberry– Playwright and activist Lorraine Hansberry wrote ‘A Raisin in the Sun’ and was the first Black playwright and the youngest American to win a New York Critics’ Circle award.

Dr. Rebecca Lee Crumpler – Rebecca Lee Crumpler became the first Black woman in the United States to become a doctor of medicine. She was also one of the first Black authors of a medical publication; her book of medical advice for women and children released in 1883.

Grace Wisher  – Grace Wisher, a free-born Black girl from Baltimore, Maryland, helped stitch the Star-Spangled Banner during the six-year apprenticeship she began with white flag-maker Mary Pickersgill around 1810.

Sarah Boone – Biography, Inventor of the Modern-Day Ironing Board  – Sarah Boone was a 19th century African American dressmaker who was awarded a patent for her improved ironing board.

Garrett Morgan – Inventor of the Traffic Light & Gas Mask (biography.com)  – The Three-Light Traffic Signal, Invented by Garrett Morgan in 1923.

Frederick Jones – Biography, Inventor, Education & Death – Frederick Jones was an inventor best known for the development of refrigeration equipment used to transport food and blood during World War II.

James West – Inventor, Microphone & Facts (biography.com) – James West is a U.S. inventor and professor who, in 1962, developed the electret transducer technology later used in 90 percent of contemporary microphones.

Lewis Howard Latimer – Biography, Inventor, Draftsman – Lewis Howard Latimer was an inventor and draftsman best known for his contributions to the patenting of the light bulb and the telephone.

Mark Dean – Biography, Computer Scientist, Engineer – Computer scientist and engineer Mark Dean is credited with helping develop a number of landmark technologies, including the color PC monitor, the Industry Standard Architecture system bus and the first gigahertz chip.

James Van Der Zee – Photos, Quotes & Work (biography.com) – James Van Der Zee was a renowned, Harlem-based photographer known for his posed, storied pictures capturing African American citizenry and celebrity. James Van Der Zee – Photos, Quotes & Work (biography.com)

Jean-Michel Basquiat – Art, Death & Paintings (biography.com) – Jean-Michel Basquiat was a Neo-Expressionist painter in the 1980s. He is best known for his primitive style and his collaboration with pop artist Andy Warhol.

Gordon Parks – Photography, Movie & Quotes (biography.com) – Gordon Parks was a prolific, world-renowned photographer, writer, composer and filmmaker known for his work on projects like ‘Shaft’ and ‘The Learning Tree.’ Gordon Parks – Photography, Movie & Quotes

Edmonia Lewis – Sculptures, Quotes & Facts (biography.com) – The first professional African American and Native American sculptor, Edmonia Lewis earned critical praise for work that explored religious and classical themes.

Augusta Savage – Art, Harlem Renaissance & Facts (biography.com) – Sculptor Augusta Savage was one of the leading artists of the Harlem Renaissance as well as an influential activist and arts educator.

With the proliferation of AI-based tools for legal at a seemingly all-time high, a pressing concern for most legal teams is — how can I validate the effectiveness of Legal AI tools while safeguarding the confidentiality and security of my company and its data? Or, put more simply, how do I pick the right solution(s) for my team and organization?

Having worked in legal tech for 13 years, I’ve had numerous conversations with lawyers and legal operations professionals about the various challenges they hope technology can solve, many of which haven’t changed for the last 10 to 15 years (such as locating contracts). But despite its great potential, using AI-based legal solutions requires adjusting our expectations or at least better understanding new trade-offs.

At Ravel, the company I co-founded out of Stanford Law School in 2012 before joining Knowable, we always thought the best AI was AI you didn’t know was there. We set out with the goal of helping lawyers solve the kind of problems that only software, cloud computing, and, yes, AI could help solve. We always believed the attorneys didn’t need to know how the software was made, just that they could rely on it, but therein lies the crux of the issue. How can you discern which tools are right for your organization and best suited for a specific task? And how do you manage potential new risks, whether it be intellectual property, copyright, or quality?

Historically, the answer to those two questions was pretty simple. We would test the product and evaluate the result. If the answers were good enough, we’d move forward with a plan to iterate and improve over time. But that was before 2023 (well, really 2022) and the mass market advent of Large Language Models (LLMs) like GPT, Bard, and Anthropic.

Today, we must ask different questions to get to the right answer. During the inaugural Harvard Law AI Summit, a leading specialist in artificial intelligence (under the condition of anonymity as per the Summit’s rules of attendance) pointed out that while we don’t understand how LLMs work, humans have often used technology we don’t understand, such as cooking. We cooked food and made all kinds of dishes for over 10,000 years before understanding the underlying science. Trial and error were all we had. But as legal experts, is trial and error acceptable? Can we really afford that level of risk?

7 Critical Questions

In reality, we don’t have a choice. AI is not coming; it’s already here. Here are seven questions to ask your potential Legal AI provider to help you determine if a particular AI solution is suitable for your organizational needs and, more importantly, to identify which provider you are willing to entrust with a certain level of risk.

1. Is your IP protected?

This question seems fundamental, but the consequences are real. Remember the news story about Samsung engineers who fed proprietary source code into ChatGPT that OpenAI then used as training data to answer other users’ questions? Each time you ask a model to do something for you, it’s curating information and delivering an output from numerous sources. Despite having millions or trillions or more data points, open and public models are learning from every input and, in some cases, can serve up proprietary information given the right prompts.

There are ongoing debates about the legal risk associated with AI and its potential infringement, but the bottom line is your IP needs to be protected. Ask your provider if you have the right to use the AI’s output or if it belongs to someone else from whom you must seek permission. Also, ask whether the provider owns the model and has copyright in the answers. Most companies today state that you have the right to use the answers, but you should confirm before selecting a provider. Lastly, ask if you are indemnified in the event of copyright infringement. In a world of trial and error, you have a right to know.

2. What models are being used? And are they open or restricted?

This is a variation of question one, but it’s an essential component of your evaluation. The point highlights three types of LLM models that you should understand. Models like GPT are open,  public, and continuously learning from everything it ingests, updating its knowledge and making it available to anyone using the tool. Forked models are customized based on an open-source model from a fixed point in time, only answering questions based on its existing knowledge set. Proprietary models are developed from scratch in-house and not shared externally (or can be built off a forked model). This is the ultimate build vs. buy question, with the latter requiring a heavier lift to keep the training data up to date. (see  question #5)

You should also ask if the models being used are open or restricted. Often referred to as “walling,” models can be deployed via commercial agreements with AWS or MS Azure (and hence are “walled”), but they can also be deployed without commercial protections. Pending your risk tolerance, you may be more or less comfortable with a walled or open solution. 

Importantly, providers should be comfortable sharing some details about their infrastructure. While they may not reveal the specifics (as that is undoubtedly part of the company’s IP), it is not controversial to tell you if they are multi-model or single-model, nor is sharing specific names, like OpenAI, Anthropic, Bard, or BERT. Armed with this knowledge, you can engage in proper research and better understand the pros and cons of each LLM when comparing vendors and deciding whether to build one yourself.

3. What if PII is placed into the model?

What happens if you input someone’s address or upload a document that contains personally identifiable information (PII)? Revisit questions one and two, as this could create issues with GDPR or CCPA for you and the provider, increasing your company’s risk and liability. You may need to revisit or create policies and ensure enforcement, much as you do today around the use of PII.

4. How do you prevent “model drift?”

Over time, the results of AI models “drift,” which means the results or the outputs from a model or solution change in one of two ways.

• Data Drift: When the input data changes significantly, it is considered “data drift.” For example, suppose the model is trained on older contracts, and you implement a new contracting template. Consequently, the model may be unable to predict results as well on the new documents.
• Concept Drift: There is also a possibility of “concept drift.” For example, if the meaning of a term changes (like a contracting term), the dataset becomes more expansive and, thus, less effective as we use it over time.

In both cases, the model struggles to adapt to new, unexpected changes, and hence the results change. Additionally, the company you are working with may switch to an entirely different model or a different version of a model. For better or worse, the results are likely going to be different. How will you know when that happens and are the differences acceptable?

5. Do you do the training and evaluation yourself?

Especially in a world of LLMs, training is increasingly being handed over to the model creators. In these situations, the model is no longer getting better based on specific “gold standard” data but on what it has been trained on writ large. Depending on your use case, this may be sufficient, but you may want an experienced provider to train your model to increase precision and accuracy.

With training comes evaluation — a costly and challenging endeavor. It is imperative to know how models are performing if you are going to use their outputs. Ask your provider who will be responsible for the evaluation. If the answer is you, analyze the time and resources needed to put teams in place that specialize in model evaluation and ask yourself whether you are ready to assume that cost.

6. What data do you get back?

If you use a model to extract data such as redlines, drafts, or answers to contract questions, understand what the AI tool will ultimately deliver. Is it just a blurb of text or a full string and conversation? Ask your vendor to provide real-world examples of what you will receive and in what form based on your contract data set as part of your proof of value (POV).

7. Do you guarantee accuracy?

Lastly, and likely often most importantly for attorneys and their legal teams, is how trustworthy is the output? Accuracy is a critical success metric. Many companies hedge by saying, “The model learns the more you use it,” or “As you correct the output, the model gets better.” This is highly unlikely for the reasons mentioned in questions four and five since your input data will change over time, which may improve the model and sometimes confuse it. Furthermore, there are diminishing returns to training – at a certain point, the benefits become incremental and likely not noticeable. In the end, the outcomes of AI-only tools will be unpredictable, which will erode trust. This is why it is still critical to have humans-in-the-loop (HITL) to reduce risk and ensure accuracy.

What’s Next?

Amidst all this uncertainty, what can you do? The good news is traditional approaches to minimizing risk hold up.

• Step 1: Ask all the questions above. Don’t avoid them.
• Step 2: Ensure your IP is protected contractually.
• Step 3: Ask the company to be open about the models they use and their overall approach to training and evaluation.
• Step 4: Ask about accuracy and how it will be continuously monitored and validated. (Hint: HITL should be a core part of this process.)

I am quite frankly very bullish about AI for legal. Thanks to technology, I have seen attorneys accomplish previously impossible tasks and have great outcomes. I’ve also seen lots of companies overpromise and under-deliver. My former Ravel co-founder Daniel Lewis recently made the point that lawyers don’t all need to become prompt engineers to get the benefits of AI, but we do need to ask questions and be smart about who we work with.

Have questions about how Knowable thinks about ML/AI in post-signature contract management? Visit knowable.com.

By Nik Reed, SVP, Product and Research & Development, Knowable

The advantages of digitization for law firms

The benefit of digital over analog isn’t always a given. Your legal team may find they generate their best ideas working on paper — similar to how some photographers still prefer film.

Nevertheless, the overall advantages of switching to digital systems in the legal industry are significant and undeniable. They include:

• Increased productivity — By streamlining processes using digital tools, legal professionals can complete tasks more efficiently and with fewer resources. Increased efficiency allows lawyers to focus on higher-value tasks, boosting their overall productivity. Plus, the cost savings associated with reduced overhead expenses can be passed on to clients or reinvested into the firm to fuel further growth and innovation.
• Enhanced client service — Your clients are digitizing too — often faster than the average law firm — and have come to expect the cost savings and convenience technology creates. Through digitization, you can provide clients easy access to documents, case updates and billing information. And by collecting and analyzing data about your clients, you can offer customized solutions that meet their unique needs and preferences.
• Competitive advantage — Firms that harness the power of technology can offer innovative services, respond more quickly to market changes and differentiate themselves from competitors who are slow to adopt digital solutions. By staying at the forefront of legal tech, your firm will be better positioned to attract and retain clients who value speed, convenience and innovation.
• Improved work-life balance — Legal professionals can use tools like video conferencing and cloud-based document storage to stay connected with colleagues and clients while working remotely. This offers opportunities to improve work-life balance and as a result, contribute to increased job satisfaction, stress reduction and overall improved well-being for your employees.

6 tips for hiring tech-savvy legal professionals

To find talent with expertise in areas like data analytics, cybersecurity and artificial intelligence, follow these six tips:

1. Broaden your search. When hiring, expand your talent pool to include candidates with experience in technology, data science or business. These professionals can bring fresh perspectives and valuable skills to your firm.
2. Update your job descriptions. Clearly outline the technical competencies required for each role, including any software, platforms and tools that candidates should be familiar with. Emphasizing technical skills can help set realistic expectations for potential hires and encourage applicants who are passionate about integrating technology into their legal practice.
3. Offer targeted perks and benefits. To attract and retain tech-savvy talent, provide benefits that cater to their unique needs, such as flexible working arrangements, professional development opportunities and access to cutting-edge technology.
4. Invest in upskilling and training initiatives. Some of the talent you need may already be on the payroll. Encourage current staff to develop their technical skills through training programs, workshops and certifications like Certified E-Discovery Specialist (CEDS) and LTC4 Core Competency. Partner with law schools and other educational institutions to develop specialized courses and programs for your employees tailored to the evolving needs of the legal industry. This focus on upskilling not only helps your firm stay current with technological advancements but also promotes employee satisfaction and loyalty.
5. Implement reverse mentorship programs. Pair tech-savvy junior team members with experienced legal professionals who may be less familiar with digital tools and trends. This encourages knowledge exchange, fosters a collaborative environment and helps bridge the generational gap in technology adoption.
6. Partner with a staffing firm. Collaborating with a talent solutions specialist like Robert Half gives you access to a diverse pool of professionals — contract/temporary or permanent — with the necessary blend of legal and technical experience.

Bottom line: The digitization of the legal profession is a permanent shift you and your firm must embrace to stay competitive and meet the evolving needs of your clients. By recognizing the need for change and investing in technology, talent and training, you’ll be ready for long-term success in an increasingly digitized world.

This article originally appeared on Robert Half’s blog.

Jamy Sullivan is executive director of the legal practice at Robert Half, a premier provider of talent and consulting solutions for a wide range of initiatives in the legal field, including compliance, contract management, data privacy, litigation support and more. Visit RobertHalf.com.

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If you opt in, your name, title, email address, and company name will be shared with the sponsors of the event you register for, or attend. By selecting “No” you are opting out. In this case, CLOC will remove your email address from the shared attendee list. Please note that third parties will still be provided an attendance list with information generally discoverable through sources such as LinkedIn.

Modern legal entity management has finally transcended its traditional confines in the general counsel’s office, and not a moment too soon. In fact, we see this happening more frequently, with legal departments increasingly involving compliance (48%), governance (38%), finance (35%) and tax (25%) business units in entity management activities.

By no longer limiting itself to a small team of legal colleagues, the corporate record can finally be used for strategic decision-making. However, even with more business units participating in entity management, is there room to make this an even more powerful partnership? The answer lies with your colleagues in Finance & Tax.

Finance: Follow the money

Formally engaging the finance department can help more senior executives beyond the general counsel’s office understand entity management as an important business priority. Finance departments are often profit centers (as opposed to the legal department, which is often viewed as a cost center).

And for finance teams, entity data is increasingly important to their strategic planning processes. This year, the volatile markets and increased financing costs have pushed companies and funds to act more cautiously than in years past, with a higher priority on entity restructuring (and spinoffs), smaller M&A deals, and looking at past opportunities with fresh eyes. However, these short-term activities are only setting up for a bigger potential play in 2023; with high rates of undeployed capital — or dry powder — in the capital markets, 80% of Deloitte’s survey respondents believed that may be an opportunity to catch the wave and invest their cash as targets rise in value.

These opportunities, both short and long term, require a comprehensive understanding of entity data and a strong compliance track record to be competitive. Yet, 49% of companies still report using Excel to manage their entity data and a quarter reported at least one entity out of good standing in the last 24 months.

It is in the finance department’s best interest to find and invest in solutions that ensure the meticulous execution of entity management processes and empowers them to stay competitive for whatever opportunity arises.

Tax: Fighting complexity with collaboration

The Head of Tax seeks out opportunities that minimize costs and drive efficiency. Yet global complexity has hampered their agility in a trend that only seems to increase: in 2023, 45% of TMF Group’s accounting and tax experts anticipated compliance to grow over the next five years, which demonstrates the operational strain these business units are increasingly facing.

However, there’s acute awareness that with access to the right data at the right time, these heads of tax can ward off complexity. Focusing on global tax provisioning and integrating tax data company-wide are the top two priority for tax professionals in 2023, of which entity data is interlinked. By using technology to create a holistic view of the organization’s tax burden, this alignment with the legal team breeds efficiency, reduces redundancies and maximizes the potential for growth.

Entity technology: The path to partnership

In a world where collaboration reigns supreme, technology’s importance in connecting disparate business units cannot be underestimated. By creating a single source of truth for your entity data stored in a self-service database, tax, finance and legal teams can finally strategize from a collective playbook. This playbook can unlock the potential for growth, risk mitigation, and efficient decision-making. The era of entity management as a cross-functional responsibility has arrived, transforming it from an individual effort into the team sport it was always meant to be.

Diligent

Diligent Entities is the world’s leading purpose-driven entity management technology solution.  With solutions across governance, risk, compliance, audit and ESG, Diligent empowers more than 1 million users and 700,000 board members and leaders to make better decisions, faster. No matter the challenge.

Now that you know the value of partnering with tax and finance teams, take a closer look at how entity management technology can help you solidify that partnership and practice more efficient entity management.

If you ask your legal team what one of their biggest challenges is, the phrase “contract management” will undoubtedly come up. Improving the contract management process, increasing efficiency and finding the right legal tech stack is a top priority for legal operation teams year after year. Yet, many organizations still struggle with years of disorganized contracts and outdated processes. In many cases, contracts live in multiple locations and it’s anyone’s guess as to which one is the most recent version.

As a legal ops professional, “contract chaos” may not directly impact your day-to-day, but it’s a huge barrier to your legal team’s productivity. It costs the company money, whether from spending time inefficiently or paying for unnecessary outsourced legal hours. And it creates risks: the risk of no centralized visibility to contract terms and requests, the risk of missed opportunities to accelerate deals or remove unfavorable terms at renewal – just to name a few.

Even if everyone is resigned to using the current system, regardless of these costs and risks, legal operations should never be satisfied to let bad processes go unquestioned.

Generative AI can be the “assistant” your legal team needs

Another blog about generative AI? Before you tune out, we’re not here to tell you that AI is going to replace your legal team.

The truth is, generative AI has huge potential to transform the way legal teams work, but not because it’ll do real, thoughtful, legal work for them. Instead, generative AI will be the assistant your lawyers always wished they had. A tool that can effortlessly read and summarize large document sets in seconds, or instantly pinpoint parts of a contract that aren’t in line with your company’s playbook. Amplifying each legal team’s capabilities by removing admin work is where generative AI really shines.

While we can’t cover everything in one short article, we’ll touch on three of the ways incorporating generative AI into your contract management process can solve many of the traditional CLM shortfalls.

The Challenges of Traditional CLM

Even with a CLM in place, managing contracts can still be a complex and time-consuming endeavor. Traditional CLMs, even when they incorporate some degree of AI, often suffer from these common limitations:

• Without a central (and clean) repository, the system is trying to pull contract data from fragmented sources, or missing some sources entirely.
• The system isn’t able to effectively analyze contract data in real-time, as each new contract is added.
• The system’s functionality is based on rules, which even with the help of AI, fails to capture the full meaning that lives within contracts.
• Rigid templates and workflows can’t possibly work for the large variety of contracts most organizations deal with.
• The system doesn’t have the ability to understand relationships and hierarchies between different contracts within the same document family, nor does it know how to organize these document families on its own.
• The system focuses on individual documents and not the entire library of contracts or the relationship between different documents.

As you might guess, traditional CLMs with these limitations might be a step in the right direction but they’re hardly a full solution to your legal team’s needs. Moreover, any tasks performed by, or information gleaned from, this type of system still needs a thorough review by a highly trained (and highly paid) legal professional. In some cases, investing in a traditional CLM can create more work than it relieves, which doesn’t delight your legal team or anyone else around the company who feels the ripple effect of difficult contract management.

Generative AI is changing the game

Enter generative AI. And forget, for a moment, the publicly available large language models (LLMs) like Google’s Bard or Microsoft’s Bing, which are impressive but not platforms you should trust with the entirety of your company’s contract data.

Instead, we’re talking about generative AI that exists within your CLM platform and only draws from the contracts and documents you provide it. In this way, the AI lives inside a closed environment, known in technical terms as a sandbox.

How is generative AI different?   

Generative AI has the potential to provide unprecedented levels of accuracy and speed for anyone looking to unlock the data within hundreds or thousands of documents. With the right data set and prompts, generative AI can perform a wide variety of detailed contract analyzes that traditional approaches cannot.

Unlike traditional methods, generative AI takes a more flexible approach that centers around learning and simulating human-like language capabilities. This means the models don’t need strict templates and standardized workflows, but rather acquire language skills in an unstructured manner, similar to humans. This revolutionary ability allows legal teams to automate more aspects of their document review process than ever before, all without having to manually create or update templates.

Generative AI can also provide invaluable insights into the risk factors that might otherwise be hidden deep within contracts. It does this by quickly summarizing documents, identifying discrepancies, and analyzing risks from a variety of angles.

By leveraging this technology for your legal team’s needs you can reduce costs while improving accuracy and efficiency across multiple areas of your business. And here’s how!

3 ways generative AI empowers legal teams

All of this sounds great, but you want to know how generative AI will make a concrete difference in your legal team, sales team, procurement team, or others’ processes. Here are just three of the ways generative AI + CLM, when done correctly, can reduce the burden on your legal team and empower them to serve the entire business better.

1. Quickly summarize contracts 

Generative AI can be used to quickly review large numbers of documents and pull out key terms, themes, changes over time, etc. This dramatically reduces the time a highly-trained human needs to spend doing the same. With the right prompt, “Summarize the changes across the master and all amendments,” for example, and the right data set, generative AI can provide an accurate answer that would have taken a person hours of reading to obtain.

2. Instantly analyze risk 

When provided with your compliance and playbook requirements (in plain English, no less!) generative AI can identify terms and conditions in your contracts that present risk or are entirely noncompliant. Having these risks pinpointed removes the most time-consuming step and allows your legal team to address the risks in order of priority.

3. Assist in contract authoring 

Sure, there are plenty of cases when you need an attorney to draft a custom portion of a contract. But there are many more instances when standard language will do the job, as long as it’s compliant with your best practices, industry standards, and your contract playbook. Generative AI can be used to speed up contract drafting by suggesting language based on past agreements and current business objectives. It can also detect discrepancies between existing contracts and your standards, and alert attorneys of potential risks that arise based on contract language.

Limitations of generative AI for legal teams

No discussion of generative AI for legal teams would be complete without touching on the limitations of this groundbreaking technology.

While it can provide a powerful tool for quickly reviewing and summarizing documents, identifying discrepancies, and analyzing risks, it’s also subject to the same biases as humans, particularly when trained on biased or incorrect information. Additionally, generative AI can suffer from “hallucinations” where it produces seemingly factual information that simply isn’t.

Most of the major pitfalls of using generative AI in the legal context can be mitigated by high quality, clean data on the input side and skilled prompt engineering, along with an expert human’s review, on the output side.

A new world of AI-powered contract management

These three capabilities are just scratching the surface of how generative AI can aid legal teams (and, as a result, the rest of the company) work faster, smarter, safer, and for less cost. For a deeper dive into the game-changing ways AI can power a new way of managing contracts, check out The Ultimate GenAI Playbook for Contract Management by Pramata.

We’re excited to announce that CLOC (Corporate Legal Operations Consortium) is a supporting organization for the prestigious ALITA Awards 2023. Organized by the Asia Pacific Legal Innovation & Technology Association (ALITA), this year’s awards ceremony will take place live at TechLaw.Fest in Singapore on September 21-22. Our very own President, Mike Haven, will serve as a judge for the awards, solidifying CLOC’s commitment to promoting innovation in the legal space.

About the ALITA Awards

ALITA Awards have been designed to give voice and recognition to the trailblazers in the legal technology and innovation ecosystem across the Asia-Pacific region. This is the 3rd edition of ALITA’s flagship awards and promises to be an eventful ceremony, held in conjunction with TechLaw.Fest 2023 at the Suntec Singapore Convention & Exhibition Centre.

Award Categories

The ALITA Awards 2023 will recognize outstanding achievements in various facets of legal innovation with six award categories:

1. Outstanding Legal Innovator (Law Firm) Award
2. Outstanding Legal Innovator (Individual) Award
3. Outstanding Legal Innovator (In-House & Operations) Award
4. Outstanding Legal Innovator (Solution Provider) Award
5. Outstanding Legal Entrant Award
6. Outstanding Legal Innovation / Legal Tech For Good Award

Additionally, there will be a People’s Choice Award, making it a grand total of seven accolades to be won.

CLOC’s Role

CLOC, as a global community committed to transforming the business and practice of law, is proud to support the ALITA Awards. Our President, Mike Haven, brings a wealth of experience and insight as a judge for these awards.

“We are committed to fostering innovation and collaboration in legal operations across the globe. The ALITA Awards are a fantastic platform to recognize and celebrate the people and organizations that are changing the face of legal practice in the Asia-Pacific region,” says Mike Haven.

How to Participate

If you believe that you are (or know) a deserving nominee, please consider nominating yourself or share details of the ALITA Awards 2023. The deadline for nominations is September 8, 2023. Finalists and winners will be showcased at TechLaw.Fest, providing an excellent opportunity to network and learn from the best in the industry.

Final Thoughts

The ALITA Awards are more than just trophies; they are a testament to the collective efforts to innovate and improve the legal industry. As a supporting organization, we are thrilled to be a part of this journey towards a more efficient, transparent, and equitable legal system.

We encourage all our members and partners to engage with the awards, either by nominating deserving candidates or by attending the TechLaw.Fest event. Let’s celebrate the incredible work being done in legal innovation and technology.

This blog post is part of CLOC’s ongoing commitment to supporting initiatives that foster innovation and improve the financial management of legal departments worldwide.

Legal transformation is no longer a goal or a looming trend – it is a commercial imperative. Legal departments must embrace change, formulate a plan, and action it, fast, in order to control their future.

In May 2023, the global legal community gathered in Las Vegas for CLOC’s annual meeting. Unlike its physical location, CLOC is a fertile place where ideas are developed, strategies shared, and potential solutions are unpacked. Industry leaders collaborate. Curiosity is rife, plans are ignited.

But when the lights go down and we return to the office, what can be done to effect real legal transformation? Some ideas generated at CLOC have been consolidated here, along with insights and market trends. Here are four key pillars for you to embrace and help create change.

Generative AI

Generative AI (GenAI) is expected to bring real transformation to the legal industry. You must face it head on, experiment with it, use it and adapt to its current form, while at the same time preparing for the iterations and exponential improvements that will likely follow.

As most assess the impact of GenAI, there is some hesitancy in the market for buying legal technology – a ‘wait and see’ approach.  A better strategy may be to focus on fixing internal processes and getting documents and organizational knowledge in order now, enhancing current processes and know-how while GenAI continues to improve and any pitfalls are addressed. New skills are vital; prompt engineering must be mastered. For GCs, questions surrounding privacy, security, ethics, and IP concerns should be top of mind.

Techstack: The market

The market is still growing, although is bordering on being overrun with CLM solutions. Any current digital solution will need to adapt to GenAI over time to survive. Assessing legal tech has become more challenging of late, and vendors can be vague on GenAI capability for only so long.

Legal departments should focus on leveraging their existing techstacks. Through a process of strategy and road-mapping, they should determine if existing and planned legal tech will become stranded by the recent developments in GenAI.

Techstack: People and process

Legal departments need clear guidance to decide between expert systems and GenAI. Outside counsel management tools still need better data and insights on spend (an easy win), while the savings from reducing this spend can be used to fund other investments. On pricing, as outside counsel begin to use GenAI in client delivery, the billable hours will become redundant and pricing models may shift to fixed fee or effective fee arrangements. System integration and UX should be front of mind for legal departments, together with a new form of change management that reflects the seismic impacts of GenAI.

Enterprise technology

Enterprise technology is rapidly merging with legal tech, transforming the financial, security, and integration discussions within organizations.

For legal departments which are open to repurposing enterprise tech, the immediate focus is how to better utilize what you already have. Begin with a strategy and a desired end state. Consider whether you have internal development teams to assist with pilot programs. If not, find out where you can bring in outside support.  Be realistic about the pros and cons of onboarding as opposed to upfront investment in design and build.

Where to begin?

Most legal departments are in the early stages of transformation and the use of legal tech. This results in transformation immaturity and a lack of insights and data, which are crucial for optimal decision-making. There are key questions to address: where should a legal department begin on the journey? How can a legal team imagine what good looks like, and how can it get there? The immediate focus for your legal department should be in seeking to understand where you are now, to facilitate mapping for the future.

Data

Data and metrics underpin legal transformation and are some of the keys to unlocking transformation. Data allows teams to make data-driven decisions and to create maturity frameworks which help teams assess where they are on the transformation journey. Data is critical to demonstrate the value of legal, workload, spend, and ROI on initiatives, and for building the business case for investment.

However, most legal departments struggle with incomplete or unreliable data, and there is discernible hesitancy in this area with teams overburdened by overreporting obligations or the collection of data that isn’t eventually used.

Simple data strategies can be created through identifying outcomes and strategic goals, and then mapping to the data required. There are possible quick wins, through leveraging existing tools and datasets and pre-configuring new tools to help capture the data wanted. Legal departments should become focused on developing a plan to gather data now, and to consider what data and metrics to capture later.

KPMG Law can help you with your transformation. KPMG Law professionals can walk with you through the key challenges, wherever you are currently placed on the maturity pathway. There is so much more to transformation than ideas and conversations. They can help you get there, together.

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