Agentic AI: 9 promising use cases for business

That’s the way it was done in the past, until gen AI came along. Human experts now enhance reports generated by AI.

“Now we can feed AI all the contact and public documentation, and it can spin out a report in minutes instead of days with tremendous accuracy and detail,” he says. “AI plus human expertise is a tremendous boost in quality,” he says.

Now, with AI agents, the process is changing yet again. EY will release an agent-drive version of the process to evaluate vendors. “It’ll be a continuous monitoring of vendors, which was previously not possible,” Schuller says.

AI agents aren’t just about optimization use cases, he adds. “The real value is this expansion of the market, and expansion of revenue opportunities.”

HR and employee support

Another relatively low-risk, high-value use case for AI agents is answering employee questions and handling simple tasks on their behalf. A January IBM survey on gen AI development, in fact, concluded that 43% of companies use AI agents for HR.

Indicium, a global data services company, began deploying AI agents in mid-2024, for example, when the technology started to mature.

“You’d start seeing off-the-shelf applications — both open source and proprietary — that made it easier to build them,” says Daniel Avancini, the company’s CDO.

The agents are used to making things easier for HR, he says, including tasks such as internal knowledge retrieval, tagging, and documenting, as well as other business processes.

Each agent is like a microservice, specializing in one particular thing. “And they all talk to each other in a multi-agent system,” he says.

And these prompt-based conversations can get peculiar. The tricky thing is there’s a possibility of hallucinations and all the other problems that come with gen AI. “So there’s a lot of tweaking of the model so they don’t do the wrong thing or access the wrong information,” he says.

On the positive side, the AI agents can handle a lot of questions autonomously, creating a another business benefit. “And we’re finding things that aren’t correctly documented, so it helps us make the processes better,” Avancini adds.

Business intelligence

Another area where AI agents will have a large impact is business intelligence. While BI dashboards are relatively simple to use, gaining insights that go beyond the standard categories has often taken the work of a data team to extract, says Ryan Janssen, co-founder and CEO at Zenlytic, an AI-powered BI vendor.

An AI agent paired with a BI solution could give more employees access to useful analytics, he says. For example, an AI agent for BI could advise a marketing team about where to spend its budget or create a chart based on an example drawn on a napkin, Janssen says.

AI agents that understand voice inputs can generate business data insights based on spoken questions such as, “What are our top three marketing channels?”

“That’s a very natural question, but it’s ambiguous,” Janssen says. “What you can’t do with the chatbot versus an agent is disambiguating that ambiguous question. What do you mean by ‘top’? The agent, when well built, will say, ‘Oh, wait, this is ambiguous; I need to go back and use a tool for this.’”

Many organizations are just at the start of their agentic AI journeys, and there are hundreds of uses yet to be discovered, Janssen adds. Coding agents are an early use case because programming is detail-driven and time consuming, but now coding hobbyists are building apps using coding assistants.

“The way that they are best applied is when you have work that is grindy, takes a lot of work, or requires a lot of attention to detail,” Janssen says.

When dozens of agents get strung together and organized, enterprises will see new breakthroughs, he adds.

“We haven’t even scratched the surface yet with what agents can do,” he says. “We don’t know what an organization looks like yet, how they’re supposed to interact, and how it is governed. But I have no doubt that over the next couple of years, we’re going to figure that out.”