Agentic AI is having a moment, as proponents see the benefits of using autonomous AI agents to automate manual tasks across organizations.
Agentic AI, which Forrester rather than content generation. The promise the approach has for impacting business workflows has organizations such as Aflac, Atlantic Health System, Legendary Entertainment, and NASA’s Jet Propulsion Laboratory already . IT service management giant ServiceNow .
With AI agents popping up in so many situations and platforms, organizations interested in the technology may find it difficult to know where to start. A handful of use cases have so far risen to the top, according to AI experts.
Agentic AI will integrate smoothly with ERP, CRM, and business intelligence systems to automate workflows, manage data analysis, and generate valuable reports, says Rodrigo Madanes, global innovation AI officer at EY, a consulting and tax services provider. AI agents, unlike some past automation technologies, can make decisions in real-time, making process automation a primary use case.
“AI agents can automate repetitive tasks that previously required human intervention, such as customer service, supply chain management, and IT operations,” Madanes says. “What sets the technology apart is its ability to adapt to changing conditions and handle unexpected inputs without manual oversight.”
Here are six top uses for AI agents, as seen by several AI experts.
Software development
Agentic AI promises to transform AI coding assistants, or copilots, into smarter software development tools that write , analyst firm Gartner predicts that smarter AI agents will write the majority of code within three years, leading to a need for most software engineers to reskill.
Coding agents will not only write the code, but separate agents will review code for errors, says Sheldon Monteiro, executive vice president and chief product officer at Publicis Sapient, a digital transformation advisory firm.
“With DevOps toolchains already automating workflows, adding AI agents is a natural evolution,” he says. “These agents can autonomously reverse engineer specifications from code, forward engineer test cases and code from specifications, and approve artifacts that that meet certain threshold criteria, improving the overall level of automation.”
RPA on ‘steroids’
Many organizations are already using .
AI agents can also drive efficiency and cost savings by automating routine tasks and security responses, according to Beam.
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.
Agentic AI 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.”
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