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ContractPodAi 2025 Predictions: The Future of AI in Legal Tech is Moving from Generalist Models to Specialized Solutions

vmblog-predictions-2025 

Industry executives and experts share their predictions for 2025.  Read them in this 17th annual VMblog.com series exclusive.

By Atena Reyhani, Chief Product Officer at ContractPodAi

The legal tech sector is on the brink of a major transformation that I expect to see fully unfold throughout  2025, ultimately revolutionizing how the legal industry deploys GenAI. Up to this point, in many cases, the legal tech sphere has been using the traditional approach of layering large language models (LLMs) on top of existing systems and branding them as "AI-enabled." Going forward, however, we'll start to see more widespread use of specialized, task-oriented intelligence systems.

Why the shift is necessary

The driving force of this transformation is largely due to the legal industry's unique complexities. Generalized LLMs, while impressive in their versatility, tend to fall short when applied to intricate legal tasks. Legal work requires precision, contextual awareness and adherence to strict regulation requirements - all of which broad GenAI models tend to struggle with.

A multi-model approach is one of the essential factors to help solve this problem, similar to the practice of consulting specialized experts for certain challenges or tasks. Integrating multiple specialized LLMs, each focused on specific tasks and verticals, creates better, more tailored solutions and ensures legal professionals can rely on GenAI for relevant solutions to their specific needs.

Building the infrastructure for specialized AI

As the legal industry moves toward more specialized AI applications, it's critical for organizations to deploy a robust infrastructure that supports this transition. This involves implementing platforms designed to integrate AI solutions into various workflows while incorporating tools and guardrails to ensure reliability and compliance throughout. A well-built infrastructure ensures that AI applications are not only functional but also scalable and adaptable to the complexities of diverse legal environments.

Features such as audit trails for tracking AI-driven decisions and safeguards to protect sensitive data are essential for fostering trust and driving adoption. Additionally, tools tailored to specific legal tasks - like contract lifecycle management systems or due diligence platforms - enhance the practicality and relevance of AI in day-to-day operations. By combining compliance-focused measures with workflow-specific tools, organizations can create an environment where specialized AI applications flourish and deliver significant value to legal teams.

Redefining workflows with AI

One of the most exciting aspects of embracing vertical-specific AI is its potential to reimagine the ways lawyers do work. Legal tasks that once required significant time and human effort - like managing the contract lifecycle, conducting risk assessments, or performing detailed due diligence - are significantly streamlined with these tools. Vertical applications are designed to handle these processes with unprecedented efficiency and accuracy, freeing up legal professionals to focus on higher-value tasks.

This shift represents a move from reactive to proactive problem-solving. Instead of using AI solely to speed up repetitive tasks, legal teams can leverage these tools to gain strategic insights, anticipate risks, and make data-driven decisions.

Addressing ethical and operational challenges

The use of AI in legal tech comes with significant responsibilities. As generative AI tools become more advanced, ensuring they operate within ethical and operational boundaries is increasingly vital. Clear guardrails must be established to maintain data privacy, ensure compliance with legal and ethical standards, and provide transparency in AI-driven decisions.

Clarity and accountability are particularly vital in the legal field, where the implications of a legal professional's decisions can be far-reaching. We must be able to understand and justify the outputs of AI systems, particularly in high-stakes situations. Additionally, the continuous monitoring and refinement of AI models are necessary to address potential biases, errors, or unintended consequences, ensuring these tools remain dependable and effective over time.

Unlocking the transformative potential of AI

The future of AI in legal tech is not just about adopting new technology; it's about rethinking how legal professionals approach problem-solving and create value for their clients. These tools, tailored to the specific needs of legal professionals, promise to deliver efficiency, accuracy, and strategic advantage. As AI continues to evolve, it will empower legal teams to navigate complexities with confidence, ultimately enabling a more agile and forward-thinking legal sector.

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ABOUT THE AUTHOR

Atena Reyhani 

Atena Reyhani is Chief Product Officer at ContractPodAi. Her responsibilities include leading the product vision, product strategy, and roadmap. She leads the product team and works in close collaboration with the rest of the leadership team across the organization to formulate and execute the product vision. Prior to joining ContractPodAi, Atena led various cross-functional teams to develop products in Higher Education, Lottery & Gaming industries. Her educational background is a blend of computer science and business, and her areas of focus include brain-computer interfaces and AI-based business transformation.

Published Thursday, December 19, 2024 7:32 AM by David Marshall
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