While AI-powered chatbots have captivated public attention, an even more advanced application of generative AI is gaining traction among business leaders: agentic AI.

“This is not just another buzzword,” wrote tech expert Bernard Marr in his Intelligence Revolution newsletter, “but a groundbreaking shift in AI technology.”

At its core, agentic AI refers to systems with a level of autonomy that can independently work towards specific goals. Unlike traditional AI, which follows prompts or predefined tasks, agentic AI can make decisions, plan actions, and learn from its experiences, all aligned with human-set objectives.

“Agentic AI is the hottest trend right now,” says Jason Wong, VP analyst at Gartner. He explains that it goes beyond basic AI functions like retrieving information or generating responses. This AI can take concrete actions, such as calling an API or even generating code to solve problems. “The agency here is combined with tools,” Wong adds. “It can figure out how to tackle your problem and then execute a solution.”

A Step Beyond Generative AI

According to Scott Dylan, founder of NexaTech Ventures, agentic AI is a major leap beyond generative AI. While generative AI focuses on producing content like text or images, agentic AI has autonomy, making decisions and taking actions without constant human intervention.

“Think of it as a shift from a tool that offers suggestions to one that actually performs tasks independently, learning from the environment it operates in,” Dylan explains.

Dev Nag, CEO and founder of QueryPal, further highlights that agentic AI incorporates advanced capabilities such as self-driven reasoning, dynamic resource allocation, and adaptive problem-solving. “Unlike generative AI, which responds based on prompts, agentic AI can autonomously allocate more time to complex tasks, optimize its reasoning through reinforcement learning, and handle more intricate challenges.”

Transformational Potential for Businesses

Agentic AI could revolutionize industries by automating not only routine tasks but also intricate decision-making. For instance, in supply chain management, this AI could react to disruptions in real time, optimizing logistics without human intervention. Hodan Omaar, senior AI policy analyst at the Center for Data Innovation, believes this technology will drive significant change in various sectors.

Dylan adds, “In finance, agentic AI can enhance personalized customer service and fraud prevention systems, evolving without constant human oversight.”

The healthcare industry could also benefit from agentic AI, Dylan notes. “Imagine a system that not only diagnoses based on symptoms but continually monitors patients and adjusts treatment as it learns from real-time data.”

Nag suggests that agentic AI could significantly impact fields like law and medicine by automating complex cognitive tasks. While it may replace some jobs requiring routine analysis, it will likely create new roles focused on overseeing AI systems and enhancing human-AI collaboration.

“The ability of agentic AI to scale during runtime to solve increasingly difficult problems, without the need for bigger models or more training data, could democratize advanced AI capabilities,” Nag says. This could empower smaller businesses to access powerful AI tools that were once out of reach.

Challenges and Risks

Like generative AI, agentic AI comes with its own set of challenges. “Since AI agents use language models as their ‘brain,’ they inherit the same issues that generative AI faces, and more,” explains Sandi Besen, an applied AI researcher at IBM. When multiple agents work together, their variability compounds, which could create additional risks. However, Besen notes that incorporating human oversight into the system can help mitigate these issues.

Toward Artificial General Intelligence?
Does agentic AI bring us closer to artificial general intelligence (AGI) — AI that can think and learn like humans?

Rogers Jeffrey Leo John, CTO of DataChat, believes it does represent a small but significant step in that direction. “A key trait of general intelligence is adaptability — responding to signals, learning, and applying that knowledge in new contexts. Agentic AI shows progress in this area.” However, he also cautions that we are still far from achieving true general intelligence.

In summary, agentic AI is poised to change the landscape of business and decision-making by giving AI systems autonomy to handle complex tasks. While there are challenges, the technology’s potential to transform industries like healthcare, finance, and supply chain management is enormous, paving the way for a new era of AI-powered operations.

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