The term "AI agent" has become increasingly prevalent in legal technology discussions, yet it can be defined in numerous ways. As highlighted in Anthropic's recent article "Building Effective Agents," there is no clear definition of AI Agents. Some define AI agents as autonomous systems that operate independently over extended periods, like customer support bots that continuously handle requests. Others use the term to describe systems that follow prescriptive, predetermined workflows with specific guardrails and human oversight.
Legal practitioners are trained to focus on precise definitions and classifications. Just as lawyers carefully analyze whether specific facts fit within legal definitions, there's a natural tendency to debate what exactly constitutes an "AI agent" or an "agentic workflow." While this attention to definitional precision is valuable, it's most useful when it serves to establish a common understanding for productive dialogue. Let's explore these concepts and how they're reshaping legal practice.
Understanding Agents and Workflows
AI agents, in their most autonomous form, are systems that can dynamically choose approaches within their programming constraints. They can operate independently, making decisions about how to accomplish complex tasks over extended periods. However, this level of autonomy, while technologically fascinating, raises important security and reliability considerations for legal applications.
Agentic workflows represent a more controlled approach. These systems combine AI capabilities with structured, predefined steps and clear parameters for operation. They maintain human oversight at critical junctures while leveraging AI to enhance efficiency and accuracy. This controlled, auditable workflow aligns particularly well with legal processes, where consistency and accountability are paramount.
The Anthropic article emphasizes this distinction, noting that effective implementation AI Agents often begins with more controlled workflows before moving toward greater autonomy. This measured approach helps organizations build powerful solutions to automate complex legal tasks while maintaining necessary safeguards.
Practical Applications in Legal Work
Legal teams are finding value in controlled agentic workflows across multiple areas. Consider contract analysis: workflows can be designed to identify key clauses, flag potential issues, and suggest edits based on predefined legal standards. The operation of the workflow can include autonomous evaluation of output and improvement through a reflection process.
Similarly, legal research workflows can systematically navigate legal databases, identifying relevant precedents and extracting insights more efficiently than traditional methods. Workflows that allow the system to evaluate the results and determine further research steps enhance the ability to provide a more thorough work product.
Security Concerns and Risk Mitigation
The implementation of AI agents raises legitimate security concerns that deserve careful consideration. Access to sensitive data and tools makes these systems potential targets for bad actors. A security breach could allow unauthorized users to manipulate agents or access confidential information, creating significant risks for law firms and their clients.
Additionally, autonomous agents without proper controls could potentially perform tasks in ways that deviate from intended purposes or professional standards. These risks underscore the importance of implementing robust security measures and maintaining human oversight.
This is where controlled agentic workflows offer a pragmatic solution. By operating within predefined parameters and maintaining clear checkpoints for human review, these workflows provide a secure framework for leveraging AI capabilities. They allow organizations to begin implementing AI-enhanced processes while mitigating many of the risks associated with fully autonomous systems.
The Path Forward
As Agentic technologies evolve, maintaining the balance between autonomous operation and human control becomes increasingly important. While future developments may expand the capabilities of autonomous agents, the current focus on controlled agentic workflows provides a practical framework for enhancing legal services while maintaining professional standards.
Success lies in understanding both the potential and limitations of AI. Rather than replacing lawyer judgment, these technologies create environments where human expertise and AI capabilities work together effectively. By maintaining this balanced approach, firms can confidently implement AI-enhanced workflows while ensuring security, compliance, and quality of service.
The legal profession's path forward isn't about rushing toward full automation (or obsessing over the fear of sci-fi scenarios) but rather about thoughtfully implementing controlled workflows that enhance capabilities while maintaining necessary oversight. Abstracting current legal workflows into agentic workflows that incorporate human supervision is the path forward for legaltech. This measured approach allows firms to build confidence, develop best practices, and ultimately deliver better results for their clients.