In Alfred Hitchcock’s 1935 classic movie “The 39 Steps,” Richard Hannay, an unwary Canadian living in London, is caught up in the mayhem following pistol shots fired in a theater. In the ensuing panic, Hannay finds himself holding a seemingly frightened woman who persuades him to take her back to his flat. She tells him her name is Annabella Smith, she is a spy and she fired the shots to create a diversion so she could elude assassins. During their conversation, Ms. Smith insists she would rather be called an “agent” than a “spy.” The bonds tying spying and agents together have been strengthened by subsequent popular spy movies, like James Bond films. This historical association between spying and agents makes many people uncomfortable when they hear the term artificial intelligence (AI) agent. Admittedly, there is a dark side to AI agents (aka bots). Tech writer Micheal Chukwube reports, “Bot attacks constitute a major danger to businesses and individuals. For five consecutive years, the percentage of global web traffic connected to bad bots has increased, reaching 32% in 2023, a 1.8% increase from 30.2% in 2022. … These nefarious bots are designed to breach a system, access confidential files illegally, and disrupt normal operations, which leads to severe financial and reputational consequences.”[1] There is, however, an upside to agents that can be extremely beneficial to businesses and, in the future, they may be indispensable.

What is an AI Agent?

Technology journalist Melissa Heikkilä writes, “When ChatGPT was first released, everyone in AI was talking about the new generation of AI assistants. But over the past year, that excitement has turned to a new target: AI agents. … And it’s not just hype, although there is definitely some of that too. Tech companies are plowing vast sums into creating AI agents, and their research efforts could usher in the kind of useful AI we have been dreaming about for decades. Many experts, including Sam Altman, say they are the next big thing.”[2] So, what are AI agents? It turns out there is no universally accepted definition of an agent. Here are few different definitions:

• Xi Kang, an Assistant Professor in the Owen Graduate School of Management at Vanderbilt University, defines an AI agent as “any algorithm or model powered by AI or related technology that can help people make predictions about the future or make decisions, if it is approachable enough for laymen to interact with it, to get some insights from it.”[3]

• The staff at Amazon Web Services (AWS) explains, “An artificial intelligence agent is a software program that can interact with its environment, collect data, and use the data to perform self-determined tasks to meet predetermined goals. Humans set goals, but an AI agent independently chooses the best actions it needs to perform to achieve those goals.”[4]

• Journalist Ellen Glover writes, “AI agents are artificial intelligence systems that can perform a wide range of tasks and autonomously respond to changing circumstances. After receiving an initial prompt, they work on their own so that human users don’t have to walk them through the process step-by-step or constantly send new instructions.”[5]

The AWS staff identifies six different types of AI agents. They are: 1) Simple reflex agents: “A simple reflex agent operates strictly based on predefined rules and its immediate data. It will not respond to situations beyond a given event condition action rule. Hence, these agents are suitable for simple tasks that don’t require extensive training.” 2) Model-based reflex agents: “A model-based agent is similar to simple reflex agents, except the former has a more advanced decision-making mechanism. Rather than merely following a specific rule, a model-based agent evaluates probable outcomes and consequences before deciding. Using supporting data, it builds an internal model of the world it perceives and uses that to support its decisions.” 3) Goal-based agents: “Goal-based agents, or rule-based agents, are AI agents with more robust reasoning capabilities. Besides evaluating the environment data, the agent compares different approaches to help it achieve the desired outcome. Goal-based agents always choose the most efficient path. They are suitable for performing complex tasks, such as natural language processing (NLP) and robotics applications.” 4) Utility-based agents: “A utility-based agent uses a complex reasoning algorithm to help users maximize the outcome they desire. The agent compares different scenarios and their respective utility values or benefits. Then, it chooses one that provides users with the most rewards.” 5) Learning agents: “A learning agent continuously learns from previous experiences to improve its results. Using sensory input and feedback mechanisms, the agent adapts its learning element over time to meet specific standards. On top of that, it uses a problem generator to design new tasks to train itself from collected data and past results.” 6) Hierarchical agents: “Hierarchical agents are an organized group of intelligent agents arranged in tiers. The higher-level agents deconstruct complex tasks into smaller ones and assign them to lower-level agents. Each agent runs independently and submits a progress report to its supervising agent. The higher-level agent collects the results and coordinates subordinate agents to ensure they collectively achieve goals.”

The Future of AI Agents

Because different kinds of agents can be used for different tasks, most experts believe they represent the future of AI. Futurist Lital Marom writes, “In the ever-evolving world of technology, one phenomenon is rapidly reshaping the way we interact with artificial intelligence — the rise of AI agents. These autonomous systems, once confined to the realms of science fiction, have now become an industry-wide reality, proliferating across nearly every sector and vertical.”[6] She adds, “AI agents are poised to revolutionize the way we interact with technology, ushering in an era where we delegate entire tasks rather than prompting systems step-by-step. This shift represents a seismic change in how we approach problem-solving, enabling us to harness the full potential of AI in ways that were once unimaginable.” Although that sounds hyperbolic, Marom is far from alone in her assessment of the impact that AI agents will have on businesses and individual lives.

Glover reports, “AI agents can be deployed across a wide range of industries and workspaces.” She goes on to provide a few examples of how AI agents are being used. They include:

• Customer Service. “One of the most common applications of AI agents is in customer service, where they are used to interact with customers. They can autonomously access internal databases, provide relevant answers to questions and even take actions like scheduling appointments or placing orders.”

• Administrative Support. “AI agents can be used as a sort of personalized executive assistant. They can draft and triage emails, schedule meetings, transcribe calls and much more — all with little or no prompting from a human user.”

• Software Engineering. “Artificial intelligence has long been a fixture in software engineering, aiding in tasks like code generation, code translation and error correction. AI agents can take things a step further by independently building and deploying entire web applications — using the same tools, tricks and steps a human software engineer would without actually having to be asked to do so by a human.”

• Recruiting. “AI agents can streamline the hiring process by sifting through applications automatically, using machine learning to compare the data from job descriptions to the information shared on candidates’ resumes and profiles. When they identify people they like, the agents can schedule interviews and follow-up with them as needed.”

• Autonomous Vehicles. “Autonomous cars and trucks equipped with AI agents can navigate and avoid obstacles in real-time, ideally getting from point A to B without any human intervention at all. ”

Concluding Thoughts

Marom insists, “It is crucial for leaders to understand the profound implications of AI agents and how they will redefine the business landscape. Embracing this paradigm shift is no longer a choice but a necessity for those who wish to remain competitive and future-proof their organizations.” Glover notes the many benefits of AI agents including improved productivity, reduced costs, and efficient decision-making. Perhaps the most exciting thing to know about AI agents is that we are still in the early days of developing them. Heikkilä explains, “Amid all the hype and excitement, it’s worth bearing in mind that research into AI agents is still in its very early stages, and it will likely take years until we can experience their full potential.” It’s little wonder that Marom insists that embracing AI agents in no longer a choice but a necessity.

Footnotes
[1] Micheal Chukwube, “3 Types of Bot Attacks to Guard Against,” Tripwire, 5 August 2024.
[2] Melissa Heikkilä, “What are AI agents?” MIT Technology Review, 5 July 2024.
[3] Kate Whiting, “What is an AI agent and what will they do? Experts explain,” World Economic Forum, 24 July 2024.
[4] Staff, “What are AI Agents?” Amazon Web Services.
[5] Ellen Glover, “What are AI Agents?” Built In, 15 July 2024.
[6] Lital Marom, “The Unstoppable Rise Of AI Agents: Redefining The Landscape,” Forbes, 26 June 2024.