For technology adopters looking for the next big thing, \u201cagentic AI\u201d is the future. At least, that\u2019s what the marketing pitches and tech industry T-shirts say.<\/p>\n
What makes an artificial intelligence<\/a> product \u201cagentic\u201d depends on who\u2019s selling it. But the promise is usually that it\u2019s a step beyond today\u2019s generative AI chatbots.<\/p>\n Chatbots, however useful, are all talk and no action. They can answer questions, retrieve and summarize information, write papers and generate images, music, video and lines of code. AI agents, by contrast, are supposed to be able to take actions autonomously on a person\u2019s behalf. <\/p>\n If you\u2019re confused, you\u2019re not alone. Google searches for \u201cagentic\u201d skyrocketed from near obscurity a year ago to a peak this fall<\/a>. Merriam-Webster hasn\u2019t added it to the dictionary but lists \u201cagentic\u201d<\/a> as a slang or trending term defined as: \u201cAble to accomplish results with autonomy, used especially in reference to artificial intelligence.\u201d<\/p>\n A new report Tuesday by researchers at the Massachusetts Institute of Technology and the Boston Consulting Group, who surveyed more than 2,000 business executives around the world, describes agentic AI as a \u201cnew class of systems\u201d that \u201ccan plan, act, and learn on their own.\u201d <\/p>\n \u201cThey are not just tools to be operated or assistants waiting for instructions,\u201d says the MIT Sloan Management Review report. \u201cIncreasingly, they behave like autonomous teammates, capable of executing multistep processes and adapting as they go.\u201d<\/p>\n How to know if it\u2019s an AI agent or just a fancy chatbot<\/p>\n AI chatbots \u2014 such as the original ChatGPT that debuted three years ago this month \u2014 rely on systems called large language models that predict the next word in a sentence based on the huge trove of human writings they\u2019ve been trained on. They can sound remarkably human, especially when given a voice<\/a>, but are effectively performing a kind of word completion.<\/p>\n That\u2019s different from what AI developers \u2014 including ChatGPT\u2019s maker, OpenAI, and tech giants like Amazon, Google, IBM, Microsoft and Salesforce \u2014 have in mind for AI agents.<\/p>\n \u201cA generative AI-based chatbot will say, \u2018Here are the great ideas\u2019 \u2026 and then be done,\u201d said Swami Sivasubramanian, vice president of Agentic AI at Amazon Web Services, in an interview this week. \u201cIt\u2019s useful, but what makes things agentic is that it goes beyond what a chatbot does.\u201d<\/p>\n Sivasubramanian, a longtime Amazon employee, took on his new role helping to lead work on AI agents in Amazon\u2019s cloud computing division earlier this year. He sees great promise in AI systems that can be given a \u201chigh-level goal\u201d and can break it down into a series of steps and act upon them. \u201cI truly believe agentic AI is going to be one of the biggest transformations since the beginning of the cloud,\u201d he said.<\/p>\n At its most basic level, an AI agent works like a traditional, human-crafted computer program that executes a job, like launching an application. Combined with an AI large language model, however, it can search for knowledge that enables it to complete tasks without explicit, step-by-step instructions. That means, instead of just helping you draft the language of an email, it can theoretically handle the whole process \u2014 receiving a message from your coworker, figuring out what you might want to say, and firing off the response on its own. <\/p>\n For most consumers, the first encounters with AI agents could be in realms like online shopping. Set a budget and some preferences and AI agents can buy things<\/a> or arrange travel bookings using your credit card<\/a>. In the longer run, the hope is that they can do more complex tasks with access to your computer and a set of guidelines to follow.<\/p>\n \u201cI\u2019d love an agent that just looked at all my medical bills and explanations of benefits and figured out how to pay them,\u201d or another one that worked like a \u201cpersonal shield\u201d fighting off email spam and phishing attempts, said Thomas Dietterich, a professor emeritus at Oregon State University who has worked on developing AI assistants for decades. <\/p>\n Dietterich has some quibbles with companies using \u201cagentic\u201d to describe \u201cany action a computer might do, including just looking things up on the web,\u201d but is enthused about the possibilities of AI systems with the \u201cfreedom and responsibility\u201d to refine goals and respond to changing conditions as they work on people\u2019s behalf. They can even orchestrate a team of \u201csubagents.\u201d<\/p>\n \u201cWe can imagine a world in which there are thousands or millions of agents operating and they can form coalitions,\u201d Dietterich said. \u201cCan they form cartels? Would there be law enforcement (AI) agents?\u201d<\/p>\n \u2018Agentic\u2019 is a trendy buzzword based on an older idea<\/p>\n Milind Tambe has been researching AI agents that work together for three decades, since the first International Conference on Multi-Agent Systems gathered in San Francisco in 1995. Tambe said he\u2019s been \u201camused\u201d by the sudden popularity of \u201cagentic\u201d as an adjective. Previously, the word describing something that has agency was mostly found in other academic fields, such as psychology or chemistry. <\/p>\n But computer scientists have been debating what an agent is for as long as Tambe has been studying them.<\/p>\n In the 1990s, \u201cpeople agreed that some software appeared more like an agent, and some felt less like an agent, and there was not a perfect dividing line,\u201d said Tambe, a professor at Harvard University. \u201cNonetheless, it seemed useful to use the word \u2018agent\u2019 to describe software or robotic entities acting autonomously in an environment, sensing the environment, reacting to it, planning, thinking.\u201d<\/p>\n The prominent AI researcher Andrew Ng, co-founder of online learning company Coursera, helped advocate for popularizing the adjective \u201cagentic\u201d more than a year ago to encompass a broader spectrum of AI tasks. At the time, he also said he liked that mainly \u201ctechnical people\u201d were describing it that way. <\/p>\n \u201cWhen I see an article that talks about \u2018agentic\u2019 workflows, I\u2019m more likely to read it, since it\u2019s less likely to be marketing fluff and more likely to have been written by someone who understands the technology,\u201d Ng wrote in a June 2024 blog post.<\/p>\n Ng didn\u2019t respond to requests for comment on whether he still thinks that.<\/p>\n","protected":false},"excerpt":{"rendered":"For technology adopters looking for the next big thing, \u201cagentic AI\u201d is the future. 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