TL;DR:
- Generative AI powered by OpenAI’s GPT-4 has the potential to revolutionize the legal industry.
- It can automate time-consuming tasks such as drafting clauses, inserting previous clauses, and summarizing contract language.
- Legal professionals should prioritize data security, consider intellectual property issues, temper expectations, and invest in robust systems.
- Leading software vendors are addressing security concerns and providing personalized outputs.
- Generative AI cannot replace human judgment but can enhance efficiency and free up legal teams for higher-level guidance and support.
Main AI News:
The advent of OpenAI’s GPT-4, a groundbreaking multimodal large language model (LLM), has brought generative AI to the forefront of technological innovation. This remarkable technology has already demonstrated its transformative potential in various fields, from producing captivating visuals to generating intricate code segments. But what impact will it have on legal teams? Let’s explore.
Attorneys are well acquainted with the arduous tasks of writing, reviewing, editing, and negotiating contractual clauses. Often, they find themselves entangled in the same clauses repeatedly. For instance, while vetting a vendor, questions arise: Are the payment terms reasonable? How much limitation of liability can be negotiated? Was a non-solicitation clause slipped in unnoticed?
This is merely the tip of the iceberg. Generative AI has the power to revolutionize the legal industry, not just by saving time in such contexts but by transforming the way legal professionals work. Real-world applications of generative AI are already emerging across various legal domains.
One notable application involves training models on existing contracts and legal playbooks to generate draft clause language, incorporate clauses from previous contracts, provide suggested revisions during negotiations, and summarize contractual terms. At Lexion, we have introduced our AI Contract Assist tool, which greatly streamlines these tasks.
Moreover, these models can serve as a natural language interface to vast corpuses of legal texts. Imagine simply asking your Contract Lifecycle Management (CLM) system, “Which contracts require written consent for the assignment?” and receiving a comprehensive report in return. Such AI-driven applications dramatically expedite tasks that previously took weeks to complete, empowering legal teams to offer higher-level guidance and support to businesses.
As with any new technology, generative AI does come with limitations and security concerns that legal professionals should carefully consider. Before implementing generative AI, it is essential to familiarize oneself with the technology and evaluate its potential meaningful implementation within the company.
Here are some key considerations to bear in mind:
1. Prioritize data security: As is customary, ensure that vendors adhere to robust data security measures. Specifically, confirm that vendors do not intermingle sensitive information in training models, as this could lead to data breaches. (Recall the Samsung and ChaptGPT incident.)
2. Consider intellectual property (IP) issues: While contract clauses typically do not pose copyright challenges, generative AI models may produce verbatim text based on copyrighted material, potentially infringing on IP rights. Many software companies are hesitant to allow their engineers to use certain generative AI tools due to these concerns, despite their productivity benefits.
3. Set realistic expectations: It is crucial to recognize that generative AI is not infallible. Similar to Tesla’s autonomous driving, legal professionals remain responsible for the final output, whether it’s a contract or a summarized explanation.
4. Invest in robust systems: To maximize the potential of generative AI, it is advisable to invest in a contract lifecycle management (CLM) or similar system that centralizes and streamlines the contracting process. Generative AI, when integrated with such systems, can provide contextual insights and significantly enhance efficiency.
Leading software vendors have already taken steps to address these issues and prioritize data security. For instance, at Lexion, we have implemented stringent controls to safeguard customer data and prevent its commingling with public datasets used for model training. Furthermore, we offer personalized outputs tailored to each customer’s specific information, including their unique contract clauses and legal terms, according to their preferences and comfort level. In the future, we may even support individual attorneys’ drafting preferences.
While generative AI is poised to revolutionize the legal profession, it cannot, at least for now, replace the human aspects of legal roles, such as exercising judgment. However, the technology will undoubtedly continue to improve, and legal professionals should embrace it as a valuable tool. By allowing AI to handle the time-consuming aspects of their work, legal professionals can focus on what truly drives them—solving problems and formulating effective strategies.
Conclusion:
The emergence of generative AI, particularly OpenAI’s GPT-4, has significant implications for the legal market. By leveraging this technology, legal professionals can streamline their workflows, saving valuable time and resources. However, it is crucial to approach generative AI implementation thoughtfully, prioritizing data security and considering potential intellectual property concerns. With the right systems and controls in place, generative AI can unlock efficiency, enabling legal teams to focus on strategic problem-solving and add greater value to their organizations. As technology continues to evolve, the legal market should embrace generative AI as a powerful tool for driving innovation and productivity.
