While the technology behind AI-powered chatbots quickly captured the public imagination, an even more powerful application of generative artificial intelligence has been creating a buzz among business leaders. It’s called agentic AI.

“This innovative technology is not just another industry buzzword; it’s a paradigm shift that’s poised to redefine the boundaries of AI capabilities,” tech guru Bernard Marr wrote Monday in his Intelligence Revolution newsletter.

“At its core, agentic AI refers to artificial intelligence systems that possess a degree of autonomy and can act on their own to achieve specific goals,” he noted. “Unlike traditional AI models that simply respond to prompts or execute predefined tasks, agentic AI can make decisions, plan actions, and even learn from its experiences — all in pursuit of objectives set by its human creators.”

“Agentic AI is the hottest thing going right now,” observed Jason Wong, a vice president analyst with Gartner, a research and advisory company based in Stamford, Conn.

He elaborated that the technology is not merely about understanding intent and performing basic tasks like data retrieval and generating responses but also about taking action. “It could access an API or another tool, or even create code, for example, writing Python to rectify a problem,” Wong explained to TechNewsWorld.

“This technology’s capability varies greatly, but it combines AI with specific tooling,” he added. “It formulates a plan to tackle your inquiry or issue, then utilizes tooling to resolve it effectively.”

Scott Dylan, founder of NexaTech Ventures, based in Manchester, England, explained to TechNewsWorld that agentic AI significantly advances beyond generative AI. “While generative AI is about creating content — whether it’s text, images, or code — from existing data, agentic AI involves a degree of independence,” he stated. “It has the capability to make choices, act, and adapt dynamically without continuous human oversight.”

He described it as a transition from a tool that offers suggestions to one that independently carries out tasks, learning from its operational environment.

Agentic AI marks a significant advance beyond traditional generative AI by integrating self-initiated reasoning, flexible computing power distribution, and enhanced problem-solving abilities, according to Dev Nag, CEO and founder of QueryPal, an enterprise chatbot company based in San Francisco.

“In contrast to generative AI, which relies on generating content from provided prompts, agentic AI independently adjusts its processing time for intricate problems, engages concealed thought-process spaces, and applies reinforcement learning to refine its decision-making strategies,” he explained in an interview with TechNewsWorld.

“This evolution enables agentic AI to address more complex issues and tailor its strategies according to the specific needs of the task, advancing beyond simple text outputs to more nuanced, human-like problem-solving across various areas of tokenizable data,” he continued. “It’s clear that contemporary agentic AI — like OpenAI’s o1 — not only stems from generative AI foundations but also aims to achieve broader objectives.”

The robust features of agentic AI have the potential to radically transform numerous businesses.

“Agentic AI has the potential to revolutionize entire industries by taking over not only simple, repetitive tasks but also intricate decision-making processes. For instance, in the realm of supply chain management, agentic AI can forecast and address disruptions in real time, manage routing, and control inventory autonomously,” mentioned Hodan Omaar, a senior AI policy analyst at the Center for Data Innovation, a think tank that explores the convergence of data, technology, and public policy in Washington, D.C., in a discussion with TechNewsWorld.

“Companies are facing a significant transformation with the onset of agentic AI,” Dylan remarked. “It’s not merely about automation but about equipping systems to manage intricate decision-making autonomously. In the finance sector, such autonomy could allow for more customized customer service and fraud prevention mechanisms that adapt to changing threats without constant human monitoring.”

“What truly excites me is its application in areas like healthcare,” he continued. “Consider a healthcare system that doesn’t just diagnose based on symptoms but also continuously monitors patients after diagnosis, adjusting treatment plans as it learns from patient data. While this scenario is for the future, the foundation that agentic AI is building today is leading us towards this possibility.”

Nag emphasized that agentic AI could transform sectors like law, medicine, and finance by automating complex cognitive tasks. This shift might reduce jobs that rely heavily on routine analysis but could also generate new opportunities focused on managing AI systems and fostering collaboration between humans and AI.

“The ability of agentic AI to scale at runtime to solve increasingly difficult problems without necessarily requiring larger models or more training data could democratize access to advanced AI capabilities, allowing smaller businesses to leverage powerful AI tools,” he added.

“This new paradigm of runtime scaling introduces a novel dimension to AI development beyond just hardware and training data scaling, which have been the battleground among AI companies for the last two years,” he said.

Like generative AI, agentic AI has its problems. “Inevitably, because AI agents use a language model as their ‘brain,’ they share at least all the problems that generative AI does and then some,” noted Sandi Besen, an applied AI researcher at IBM and Neudesic, a global professional services company.

“Additionally, when you start using multiple agents in tandem and provide them with the ability to work with one another, the innate variability that exists in generative AI is compounded,” she told TechNewsWorld. “However, there are certainly methods you can use to mitigate against this, such as ensuring there is proper evaluation and human in the loop included in the AI system.”

“Agentic AI, like other forms of AI, has the potential to advance users’ productivity. By carrying out the multiple steps involved in many tasks, it is able to automate more work and save users both time and money,” added David Inserra, a fellow for free expression and technology at the Cato Institute, a Washington, D.C.-based think tank.

“While some will inevitably use such an AI tool for malicious reasons or to create content that some find offensive, the many positive applications of this technology means it should be allowed to flourish, free from burdensome government regulation like what we see in the EU,” he told TechNewsWorld. “As a result of such regulations, major tech companies are already withholding new AI tools in Europe, leaving Europeans worse off.”

Since agentic AI gives gen AI the power to act, does it advance the field closer to the holy grail of artificial general intelligence (AGI) and true thinking machines?

“A fundamental trait of general intelligence, whether in humans or animals, is the ability to adapt — sensing environmental signals, responding to them, and learning from those responses. In this regard, agentic AI marks a small yet meaningful step toward general intelligence.” Rogers Jeffrey Leo John, co-founder and CTO of DataChat, a no-code, generative AI platform for analytics, in Madison, Wisc., told TechNewsWorld.

“However,” he added, “we are still far from reaching true general intelligence, which would be capable of applying knowledge acquired from one situation to a completely different context.”

Shawn DuBravac, CEO and president of the Avrio Institute, a technology consulting firm for CxOs and executives, also in Madison, doubted agentic AI would be a path toward AGI. “I would argue that agentic AI is not a precursor of AGI,” he told TechNewsWorld. “It’s not clear we reach AGI through linear progression from current AI technologies like agentic AI.”

“In fact, I think it will be unlikely,” he continued. “If we reach AGI, I believe the path will involve breakthroughs and new paradigms of intelligence that differ significantly from what we have accomplished so far and what we are likely to accomplish in the coming years.”

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