Traditional AI systems are used in the legal industry to analyze data and extract insights from documents. Generative AI tools like ChatGPT create content and clauses for legal documentation, contracts, and client onboarding workflows.
Here is the distinction and how these technologies can revolutionize work in the legal sector.
Predictive Analytics and Risk Management
Predictive analytics involves analyzing large volumes of data to identify potential risks and opportunities with legal cases and address challenges before they occur. Generative AI can find patterns and suggest possible strategies for their effective remediation. Generative AI tools can construct new scenarios or datasets, unlike traditional AI tools, thus synthesizing new content and mapping out all possible legal scenarios. It improves risk identification and management.
Generative AI has other uses cases in the legal field like legal audits, litigation support, e-discovery, dispute resolution, and contract analysis and negotiation.
Due Diligence and Mergers & Acquisitions
Due diligence is a core component of M&A transactions and helps legal professionals identify risks, liabilities, and opportunities associated with target companies and assets. Traditional AI automates repetitive tasks when it comes to administrative work and is limited to legal research and analytics.
Generative AI on the other hand helps users conduct comprehensive investigations and minimizes the likelihood of running into unforeseen legal issues post-acquisition. It analyzes contractual data and reviews regulatory and compliance history, enabling companies to adhere to applicable laws and regulations. These solutions can help stakeholders make better negotiation decisions, structure transactions, and position companies to capitalize on new investment opportunities.
Contract Analysis, Corporate Governance, and Document Drafting
Generative AI can generate new metadata for predicting outcomes for different cases. It can uncover legal non-compliance trends, summarize historical review board agendas, and make market forecasts for better legal liability management. Automating corporate governance, creating policy templates, and ensuring consistency in contract drafting styles, quality, reviews, negotiations, and their overall implementations.
Whereas AI is trained to work on limited datasets. Gen-AI reduces the volume of documents for manual reviews by eliminating human errors, and inconsistencies, and by creating higher-quality datasets.
Conclusion
There are many nuances and complex aspects of practices in the legal landscape that require human empathy, judgment, and intuition. While AI cannot replace lawyers, it can assist professionals with reducing workloads and working collaboratively. Generative AI is a natural progression in that direction and will evolve how professionals fit into their roles and boost performance.
