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 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.