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WTF is agentic AI? – Digiday


For a while, 2025 was shaping up to look like the time when everyone (at least in the business world) took a collective breath and set an AI path that was less driven by hype and “do not adopt at your own peril” threats and more anchored to ROI assessments .

But it was only a matter of time.

Digital technology has always been prone to buzzwords, and now generative artificial intelligence has entered the mainstream vocabulary and is being pushed out of the way by the latest term du jour: “agentic artificial intelligence.”

So if you’ve seen this term popping up more and more but aren’t quite sure what it is, or even need to know, you’re not alone. Here is the explainer.

What exactly is agent AI and why is it suddenly being discussed?

It refers to a type of artificial intelligence that is designed to take independent action rather than just responding to commands given by humans. It was created by Andrew Ng, a renowned AI researcher, this June. Big tech companies and vendors have begun to push this more aggressively, and the ultimate goal is to have these so-called “AI agents” perform complex tasks on behalf of humans, but with minimal human oversight. They believe this will lead to better organizational efficiency and employee productivity.

How does this relate to generative AI?

To fully understand this, you need to think at the core of all types of AI and what they do.

So-called traditional AI performs tasks based on pre-defined rules and patterns (set by humans.) It is not adaptable and does not learn or improve from new data (such as calculators, logic chess programs, or chatbots with scripted responses. ) Then you have machine learning (ML). – a subset of AI – which involves training a model using large datasets to identify patterns and make decisions. It is customizable and improves as it processes more data. Generative AI is a subfield of ML. Generative AI uses data from large language models to create new content such as text, images, music or code. It’s like a more creative kind of AI versus analytical ML.

We now have agentic AI that takes all the components of traditional and generative AI and uses it to autonomously anticipate needs and execute against them. And it can dynamically adapt, learn from experience and adjust future actions based on new information. It can also be proactive, rather than waiting purely for human commands like other forms of AI.

Give an example of what an AI agent can do for an HR professional.

Like generative artificial intelligence, agentic is being touted as a means of increasing employee productivity by automating tedious and time-consuming routine tasks, allowing people to focus on more strategic work. “It’s important for HR leaders to understand the impact of agent AI on employee performance and well-being, as it brings new dynamics to the employee experience and how work is managed and performed,” said Jay Patel, svp and general manager of Webex Customer Experience Solutions at telecommunications giant Cisco.

Be more specific, let’s give an example.

Take learning and development. Agent AI can benefit employee career development by offering more personalized training and development programs.

Jill Goldstein, global managing partner for HR and talent transformation at IBM Consulting, sums it up this way: Traditional AI will recommend training courses based on an employee’s role and past performance. Generative AI can develop custom learning modules, quizzes, and interact with content based on specific employee agenda needs. Agentic AI manages the employee’s personal learning plan and continuously mines additional information. It adjusts an individual’s learning journey based on new information that becomes available, providing real-time performance, data and feedback that is then fed back into AI, helping employees develop their skills. “So the first one. [traditional AI/ML] triggers, generative AI helps tailor the content, and agentic AI builds on that and helps me solve the problem and actually produce the results associated with it,” she added.

It should also free HR teams from their own time-consuming administrative tasks to focus more on more strategic planning around employee engagement, personalized support and productivity. For example, automating responses to common HR-related questions such as vacation policies, payroll information, or training opportunities. Cisco claims HR professionals can save an estimated 2.5 hours per week.

To read the full article on WorkLife click here



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