Agentic AI may be moving artificial intelligence (AI) to a new level beyond generative AI, with the same characteristics and challenges — but also with some notable distinctions.
Marc Benioff, CEO of Salesforce, calls agentic AI the “third wave” in the rapid evolution of the field. “In just a few years, we’ve already witnessed three generations of AI,” he observed in a recent piece in the New York Times. “First came predictive models that analyze data. Next came generative AI, driven by deep-learning models like ChatGPT. Now, we are experiencing a third wave — one defined by intelligent agents that can autonomously handle complex tasks.”
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AI agents, or intelligent assistants, are intended to serve as digital co-workers, assistants, or customer service representatives, communicating via natural language processing. They “have the potential to augment human capabilities in ways previously unimaginable,” Benioff observed.
“Imagine a world where businesses can deploy an AI workforce of agents to manage customer interactions, analyze data, optimize sales strategies and execute operational tasks in real time and with little human supervision.”
Across the industry, there is agreement that AI agents, with their narrow focus, bring new capabilities and ROI that wider AI cannot deliver effectively. “Agentic AI will be the next wave of unlocked value at scale,” Sesh Iyer, managing director and senior partner with BCG X, Boston Consulting Group’s tech build and design unit, told ZDNET.
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He added that this is “an opportunity to redesign processes fundamentally and unlock significant productivity gains.”
As with both analytical and gen AI, AI agents need to be built with and run along clear ethical and operational guidelines. This includes testing to minimize errors and a governance structure. As is the case with all AI instances, due diligence to ensure compliance and fairness is also a necessity for agents, Iyer said.
As is also the case with broader AI, the right skills are needed to design, build and manage AI agents, he continued. Such talent is likely already available within many organizations, with the domain knowledge needed, he added. “Upskill your workforce to manage and use agentic AI effectively. Developing internal expertise will be key to capturing long-term value from these systems.”
