A Lawyer’s Primer on AI Agents
BY
PAMELA
LANGHAM, ESQ.
The most simplistic way to explain the dynamics of AI Agents is to distinguish them from the more simple form of generative artificial intelligence technology.
THE FIRST WAVE OF GENERATIVE artificial intelligence brought us large language models (LLMs) that can analyze documents and provide responses in reaction to a prompt, with speed, but not always with accuracy. We are now witnessing the emergence of a second, more sophisticated wave: Generative Artificial Intelligence Agents, simply referred to as “AI Agents.” Lawyers increasingly find themselves in uncharted territory as clients deploy AI Agents across their business operations. These autonomous systems raise complex questions that go far beyond the ethics of using LLMs or other traditional legal technology concerns. When an AI Agent independently manages a client’s supply chain, for example, attorneys must advise on issues ranging from contract formation authority to liability for AI-initiated decisions. The key challenge isn’t just understanding what these systems can do, but anticipating the cascading legal implications of their autonomous actions.
A Lawyer’s Primer on AI Agents
BY PAMELA LANGHAM, ESQ.
The most simplistic way to explain the dynamics of AI Agents is to distinguish them from the more simple form of generative artificial intelligence technology.
THE FIRST WAVE OF GENERATIVE artificial intelligence brought us large language models (LLMs) that can analyze documents and provide responses in reaction to a prompt, with speed, but not always with accuracy. We are now witnessing the emergence of a second, more sophisticated wave: Generative Artificial Intelligence Agents, simply referred to as “AI Agents.” Lawyers increasingly find themselves in uncharted territory as clients deploy AI Agents across their business operations. These autonomous systems raise complex questions that go far beyond the ethics of using LLMs or other traditional legal technology concerns. When an AI Agent independently manages a client’s supply chain, for example, attorneys must advise on issues ranging from contract formation authority to liability for AI-initiated decisions. The key challenge isn’t just understanding what these systems can do, but anticipating the cascading legal implications of their autonomous actions.
WHAT ARE AI AGENTS?
Generative Artificial Intelligence and LLMs
The most simplistic way to explain the dynamics of AI Agents is to distinguish them from the more simple form of generative artificial intelligence technology. There is no single definition of generative artificial intelligence (GAI). In Formal Opinion 512, issued by the ABA Standing Committee on Ethics and Professional Responsibility, the committee chose to define GAI as a technology “which can create various types of new content, including text, images, audio, video, and software code in response to a user’s prompts and questions.” Another widely used definition defines GAI as a “subset of AI that utilizes machine learning models to create new, original content, such as images, text, or music, based on patterns and structure learned from existing data. A prominent model type used by
AI Agents are software programs endowed with artificial intelligence capabilities, enabling them to perceive their environment, make decisions, and perform actions autonomously to achieve specific goals.
generative AI is the [LLM].” See General Artificial Intelligence, Cornell Center for Teaching Innovation, last visited February 10, 2025. Examples include OpenAI’s ChatGPT, Anthropic’s Claude, and Microsoft’s CoPilot.
AI Agents
AI Agents are “software programs endowed with artificial intelligence capabilities, enabling them to perceive their environment, make decisions, and perform actions autonomously to achieve specific goals. They mimic human cognitive functions such as learning, problem-solving, and pattern recognition. Unlike traditional software that follows predefined instructions, AI agents can adapt their behavior based on new data and experiences.” AI Agents: Transformative Use Cases for Your Company or Brand, Mori, Giancarlo, Medium, October 1, 2024. In simpler terms, AI Agents use
GAI to autonomously perform tasks or make decisions with minimal human intervention. Distinct from LLMs, AI Agents can analyze data and make decisions based on pre-defined goals or learned patterns. AI AGents also learn through their environment, sensing through various inputs like cameras and microphones. They provide recommendations and can learn from their experiences and improve over time. Examples include autonomous vehicles perceiving their surroundings using cameras and sensors, and making driving decisions. AI Agents that understand and generate human language, provide customer support, or carry on conversations with users are an additional example.
COMPANIES USING AI AGENTS
According to Mori 2024, AI AGents are essential to organizations in today’s GAI environment because:
Operational Efficiency: AI Agents automate repetitive tasks, freeing up human resources to focus on strategic initiatives.
Enhanced Decision-Making: They provide real-time insights by processing large datasets, enabling better and faster business decisions.
Personalized Customer Experience: AI Agents tailor interactions based on customer data, improving satisfaction and loyalty.
Cost Reduction: Automation leads to significant cost savings by minimizing errors and reducing manual labor.
Scalability: Businesses can scale operations quickly without a proportional increase in costs, as AI agents handle increased workloads efficiently.
Employee Productivity: AI Agents streamline workflows by handling routine tasks, allowing employees to focus on higher-value activities, boosting overall productivity and job satisfaction.
TOO GOOD TO BE TRUE?
Of course, many organizations have used automated transaction systems before the onset of AI Agents. However, those automated transaction systems are determinative, i.e., programmed with if, then rules. AI Agents are non-determinative.
AI AGENT’S IMPACT
Legal professionals need to stay informed about
the implications of AI Agents.
Lawyers
must advise their clients on the ethical, legal, and regulatory considerations associated with deploying AI Agents, ensuring compliance with relevant laws and protecting against potential liabilities.
AI Agents are changing how businesses work in many areas, including customer service, marketing, logistics, and healthcare. They are changing business, allowing people to focus on more important work. Critical areas requiring legal guidance include risk management as AI Agents become more integrated into core business functions. Lawyers will be called upon to help clients establish protocols for human oversight, create audit trails for AI-driven decisions, and establish clear boundaries for AI Agent authority. The technology is very useful, but overreliance can cause significant legal problems.
A practical example of how this new technology can be over-relied upon was a case out of Canada decided by a civil tribunal. In Moffatt v. Air Canada, 2024 BCCRT 149 (CanLII), https://canlii.ca/t/k2spq, (retrieved on February 10, 2025), a customer interacted with Air Canada’s online AI tool on their website, explaining that he needed to purchase an airline ticket because his grandmother had died and inquired about a lower fare. The AI tool responded to his inquiry by explaining that if a customer is traveling because of a family death, then the traveler is entitled to reduced airfare. Further, the AI tool advised the customer that he could submit an online form and receive a lower bereavement fare within 90 days after the ticket’s issuance. When the customer submitted his application for a partial refund after the ticket was issued and after his travel, Air Canada denied his request. Air Canada’s bereavement policy provides that refunds or lower rates
for travel triggered by family deaths will only be considered before a flight and not after the travel was completed. In other words, Air Canada’s AI tool’s independent interpretation of the bereavement policy and decision that Moffatt could apply for a refund within 90 days after travel was incorrect. Moffatt sued Air Canada. Air Canada argued that the AI tool was “a separate legal entity.” The tribunal ruled in favor of Moffatt, stating Air Canada was responsible for the AI tool’s negligent misrepresentations. Even though this case is out of Canada and decided by a civil tribunal, it illustrates the over-reliance on AI technology.
There have also been numerous reports of a Chevrolet dealership AI chatbot agreeing to sell a customer a $58,195 Chevrolet Tahoe for $1. See Chatbot Case Study: Purchasing a Chevrolet Tahoe for $1, Parsani, Cut the SAAS, June 7, 2024.
CONCLUSION
Many lawyers are grappling with their clients’ use of AI Agents as there is a rush to implement this new technology. Legal professionals need to stay informed about the implications of AI Agents. Lawyers must advise their clients on the ethical, legal, and regulatory considerations associated with deploying AI Agents, ensuring compliance with relevant laws and protecting against potential liabilities. By understanding the capabilities and limitations of AI Agents, lawyers can help their clients harness the benefits while mitigating risks.