Legal departments are increasingly grappling with the emergence of agentic artificial intelligence (AI), a technology that marks a significant evolution from the more commonly known generative AI. While generative AI is predominantly utilized through chat interfaces, agentic AI can autonomously develop plans, retrieve data, and execute tasks across integrated applications. This new capability poses both opportunities and challenges for in-house attorneys as they navigate its implications for legal operations.
The terminology surrounding agentic AI often stirs unease, conjuring images of dystopian scenarios frequently explored in science fiction. Such perceptions can complicate discussions around the technology, especially as marketing materials frequently misuse the term, conflating it with advanced automation systems that do not possess true autonomy. This misrepresentation can hinder legal teams’ efforts to conduct accurate risk assessments and may impede the adoption of these innovative tools.
In early 2023, the legal sector expressed skepticism towards generative AI, reflecting broader concerns regarding its implications. Though around 30% of U.S. legal professionals have begun to use generative AI, reports indicate that nearly 80% of companies believe their investment in this technology has yet to produce a meaningful impact on their financial performance. In contrast, agentic AI holds the promise of delivering substantive returns on investment by enabling the execution of complex workflows, such as contract reviews and compliance checks, beyond the capabilities of generative AI.
To harness the potential of agentic AI effectively, legal departments must consider whether to build, buy, or partner with these systems. Unlike generative AI, agentic AI engages in autonomous actions, introducing unique legal risks that require careful scrutiny. Issues of liability, contract formation, and regulatory compliance become more pronounced as these systems operate with a degree of independence. This raises novel concerns about data security vulnerabilities and the potential for unintended actions that could lead to legal repercussions.
The paradox facing legal teams lies in the fact that the constraints of limited budgets and personnel, which make agentic AI valuable, also limit their ability to comprehend and navigate the technology effectively. To address this challenge, legal departments must focus on understanding the autonomy spectrum of AI systems, thereby allowing for informed risk assessments grounded in the actual capabilities of the tools rather than marketing labels.
Central to assessing the risks associated with agentic AI are two pivotal questions: How much autonomy does the agent possess, and how much control does the human user retain? Legal teams need to determine if the system merely suggests actions or can autonomously execute multistep workflows without human approval. Additionally, understanding the safeguards in place—such as guardrails, override mechanisms, and audit trails—can clarify the level of human control over the system’s actions.
This framework allows legal professionals to map a system’s position on the autonomy spectrum, which ranges from assistive AI with low autonomy and high human control to fully agentic AI characterized by high autonomy and minimal oversight. As the degree of autonomy increases, so does the potential for significant adverse outcomes. For instance, a system that recommends contract terms poses minimal risk, while one that autonomously executes binding agreements carries substantial liability.
By determining where a tool lies on this spectrum, legal teams can calibrate risk management strategies, allocate resources effectively, and avoid both overregulating low-risk tools and underestimating high-risk ones. Such assessments are essential components of responsible AI governance and are increasingly mandated by emerging data privacy and AI-specific regulations.
Ultimately, the future of legal operations is not about shunning technologies, but rather about integrating them thoughtfully to maximize their potential benefits. By anchoring evaluations in the autonomy spectrum and addressing key questions regarding agent autonomy and human oversight, legal departments can navigate the complexities of agentic AI, balancing innovation with the imperative of risk management.
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