7 ASIAN LEGAL BUSINESS – INDIA E-MAGAZINE WWW.LEGALBUSINESSONLINE.COM However, barring some industry leaders, LLM adoption in the Indian legal market has been slow despite its tangible, well-documented benefits. “The Indian legal-tech market is still fragmented - making it difficult for law firms to find solutions that specifically meet their needs. This coupled with traditional lawyer mindset and regulatory uncertainty, leads to a lot of evolution of the space to happen for the industry to fully utilise the potential,” Shah explains. Having said that, Shah has noticed an increased collaboration between law firms and legal-tech startups to create custom AI solutions for specific use-case and needs. There is also the growth of specialised AI solutions for specific practice areas like corporate law, intellectual property and disputes in the market, Shah adds. Notably, legal-tech tools are focusing on improving their user experience. “A lot of legal techs are coming up with not only user-friendly websites but also mobile apps, to make it easier for lawyers to input data on the go,” Shah explains. LET’S GET ETHICAL Early users of this nascent technology note that the adoption of Gen AI in the legal industry faces three stiff regulatory and ethical challenges: maintaining client confidentiality, compliance with data privacy laws and bias perpetuation. “All documents received and shared with a client are subject to confidentiality restrictions. This is particularly of concern since law firms are required to maintain (on a case-to-case basis) Chinese walls within the firm for certain client products/documents, which would need to be factored in while leveraging firm-wide data,” Narendran explains. Compliance with the recently enacted Digital Personal Data Protection Act, 2023 (DPDP) and the EU’s General Data Protection Regulation also involves building significant data-related infrastructure, manpower and workflow by a law firm using Gen AI. “The DPDP governs the collection, storage, and processing of personal data deployed in training AI models and generation of personalised inputs,” Narendran says. Additionally, firms ought to also conduct thorough due diligence on AI vendors and their data practices before engagement, Shah adds. This includes asking as many questions as possible about data transparency and assessing if the legal tech company has a black box algorithm (socalled because the user cannot see the inner workings of the algorithm), she explains. Lastly, law firms also have to customise and train their AI in a manner to prevent it from perpetuating biases. “One major challenge is the lack of accountability and accuracy in certain AIpowered processes, such as the instances of ‘hallucinations’ where fictional sources or citations are provided in the generated content,” Narendran says. “To mitigate this risk, law firms must ensure that their AI systems are trained on diverse, representative datasets and implement detection and mitigation mechanisms for bias in AI-generated outputs,” he explains. Narendran also cautions that currently, generative AI models may also face issues in accurately interpreting and contextualising legal data in highly specialised areas of law. To fix this, Shah points out that integrating AI with human expertise is crucial. Human-in-the-loop or HITL systems, where humans and machines work together collaboratively to achieve a desired outcome, are the need of the hour, particularly in the use of GenAI in legal practice, “where human input is crucial to guide and refine the development and operation of AI models,” Shah explains. LOOKING INTO THE FUTURE The legal-tech industry is likely to continue growing despite present ethical and regulatory challenges. “While the initial investment of time and efforts in customising AI tools will be significant, ultimately, the long-term benefits are likely to outweigh such initial considerations,” Narendran says. “We foresee increased adoption of generative AI technology across four broad areas – document review, contract analysis, document management, legal and market research report, and outcome determination in legal and regulatory proceedings. Use-cases in these categories also extend to generation of legal analytics dashboards, and entirely automated due diligence processes,” he adds. Shah also says that GenAI can enable innovative pricing models based on value delivered, making legal services more accessible to a wider audience. “AI algorithms can predict litigation outcomes and durations, which might help the firms to offer fixed fees with confidence, reducing financial risks for both client and firm,” Shah says. Both Narendran and Shah believe that GenAI is going to positively disrupt law firm functions, client relationships, research and document review in a big way going forward. “While the use-cases at present are largely in an augmentative capacity to assist lawyers in offering legal advice, the near future is likely to entail a foundational shift in the manner in which law firms are structured, with artificial intelligence forming the very core of the law practice,” Narendran says. “We foresee increased adoption of generative AI technology across four broad areas – document review, contract analysis, document management, legal and market research report, and outcome determination in legal and regulatory proceedings. Use-cases in these categories also extend to generation of legal analytics dashboards, and entirely automated due diligence processes.” Nikhil Narendran, Trilegal
RkJQdWJsaXNoZXIy MjA0NzE4Mw==