ILTACon Day Three: Agents, AI, and Ari..!

Orchestrating Intelligence: AI Agents in the Legal Space – Session Summary

Speakers: Lisa Erickson (Aderant), Matt Zerweck (Harvey), Adam Ryan (Litera), Joel Hron (Thomson Reuters) AI agents are sophisticated, goal-oriented systems designed to understand context, plan actions, and execute tasks autonomously. Unlike traditional AI, which often performs single, discrete functions, AI agents operate more like a capable "co-worker." They can grasp the objectives of a task, identify and utilize available tools, strategize the execution of steps, and even seek guidance when necessary. The key distinction is that users define the desired outcome, rather than dictating each specific action.

Why They Matter

AI agents hold significant strategic importance by amplifying human capabilities, allowing professionals to achieve more with higher quality. They enhance the most human and often the most challenging aspects of a job. As agents become more autonomous, human oversight and verification are paramount. Future software will likely focus on optimizing the speed of verification, emphasizing the need for transparent citation and robust source tracking.

Current Use Cases & Results

• Email Processing: Agents can proactively understand email context and perform actions such as responding to inquiries or drafting pitch materials.
• Document Drafting: Embedding firm and client preferences into AI agents reportedly leads to 50-70% time savings in reaching initial drafts, while improving consistency.
• Legal Research: AI agents excel in "deep research," demonstrating over 60% time savings and uncovering novel arguments, particularly in cross-jurisdictional litigation.
• Contract Analysis: Agents can identify standard terms, flag non-standard provisions, and proactively identify risks across large portfolios of contracts.

Training Agents: Three-Pillar Approach

• Planning & Reasoning Capability: This encompasses the core logical processes that enable agents to strategize and problem-solve.
• Purpose-Built Tools: The development of APIs specifically designed for agent utilization is crucial for their functionality.
• Context Provisioning: Providing agents with access to relevant data, whether proprietary or third-party, is essential for their performance.

Future Outlook (1-10 Years)

The future will likely see the development of "ecosystems of agents" that can effectively communicate and collaborate with each other. Experts envision agents that proactively reach out with suggestions based on incoming information. Firms that succeed will possess well-structured data sets of their own experience, a critical requirement for AI agent implementation.

Implementation Considerations

• Provide comprehensive information: The more context agents have, the better they perform.
• Start with simpler tasks: Begin with straightforward, clearly defined tasks before attempting complex workflows.
• Always check their work: Human review remains essential for validating agent outputs.
• Control access properly: Ensure agents only access data they are authorized to see.
• Results vary by task: Some tasks may require minimal AI assistance, while others necessitate frequent human guidance.

Key Takeaway

The consensus is that the impact of AI agents, while technically feasible today, will be significantly larger than currently anticipated in the next five years. Strategic transformation will occur gradually as firms build robust data foundations and refine verification processes.

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Frequently Asked Questions (FAQ)

What are AI Agents in the legal context?

AI agents are goal-oriented systems that understand context, plan actions, and execute tasks autonomously, acting as intelligent assistants to legal professionals.

How do AI agents differ from traditional AI?

Unlike traditional AI that performs discrete functions, AI agents work collaboratively, understanding tasks, available tools, and planning execution with a degree of autonomy, similar to a human colleague.

What are the main benefits of using AI agents in the legal space?

AI agents can significantly boost productivity, improve the quality of work through consistency and discovery of new arguments, and amplify the most human aspects of legal practice.

What are some current use cases for AI agents in law firms?

Current applications include email processing, document drafting, legal research, and contract analysis, all of which have shown substantial time savings and improved outcomes.

What is the key to successfully training AI agents?

A three-pillar approach is essential: robust planning and reasoning capabilities, purpose-built tools (APIs), and comprehensive context provisioning (access to relevant data).

What is the future outlook for AI agents in the legal industry?

The future anticipates ecosystems of collaborating agents and proactive AI that suggests actions. Firms with well-structured data sets will be best positioned for success.

What are the crucial considerations for implementing AI agents in a law firm?

Key considerations include providing sufficient data context, starting with simpler tasks, ensuring human oversight and verification, proper access control, and understanding that results depend on the specific task.

What is the long-term impact of AI agents on the legal profession?

Experts predict a significant, potentially exponential, growth in the impact of AI agents, necessitating gradual strategic transformation and adaptation.

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Crypto Market AI's Take

The evolution of AI agents, particularly in specialized fields like law, mirrors the transformative potential we see within the financial markets. Just as AI agents are learning to navigate complex legal documents and research, our platform leverages similar AI-driven capabilities to analyze cryptocurrency markets. We understand that strategic implementation and a strong data foundation are critical for success, whether in legal practice or in optimizing trading strategies. Our AI tools are designed to provide actionable insights and automated execution, aiming to amplify human potential in the fast-paced world of crypto. We believe that by integrating advanced AI, professionals can achieve higher quality outcomes and unlock new efficiencies, a principle that applies across both the legal and financial sectors. For those looking to understand how AI can be applied in finance, our insights into AI agents in finance and our approach to AI-powered trading offer a glimpse into this evolving landscape.

More to Read:

• Actionable AI Strategy & Policy – Session Summary
• AI Agents in the Legal Space: Understanding the Nuances
• The Future of Trading: How AI is Revolutionizing the Crypto Market

Originally published at Artificial Lawyer on 14 August 2025.