4 agentic AI success stories

Agentic AI is an autonomous system that can plan and execute complex tasks and processes as part of an overall workflow that includes humans or functions entirely on its own.

Organizations are leveraging agentic AI for everything from managing customer inquiries to automating logistics, optimizing workflows, detecting fraud, and generating and testing code.

Research firm Grand View Research predicts the global enterprise agentic AI market will reach $24.5 billion by 2030, growing at a CAGR of 46.2% from 2025 to 2030.

Here are four examples of how organizations today are using agentic AI to great benefit.

DeVry University supports students with agentic AI

Hybrid online and on-site university DeVry University has developed an AI agent to help prospective and existing students at any hour since the majority of DeVry’s students have full-time jobs, and many are parents.

“Our students are doing the vast majority of their learning at the end of their workday, after they’ve made dinner and put the family to bed,” says DeVry CIO Chris Campbell. “We see a lot of learning activities happening after 7 p.m. and up until about 1 a.m. Mountain Time.”

DeVry has developed DeVryPro, which provides prospective students with information about courses and the benefits of online learning at all hours. They can start a chat with the agent when it’s convenient for them, and it can respond instantly with current information about the courses, enrollment processes, and learning experience. DeVryPro can also help prospective students find, enroll in, and pay for courses.

Meanwhile, for existing students, the agent extends support and care through the university’s portal, replacing DeVry’s legacy chatbot. Campbell says that in addition to making round-the-clock, on-demand support possible, it’s also scalable, enabling DeVry to support those students without increasing service costs.

Campbell’s advice: Success requires the engagement of the entire C-suite. “You need all the stakeholders in every way, because you’re talking about fundamentally changing how the organization operates,” he says.

AT&T is all-in on agentic AI

Telecom giant AT&T sees agentic AI as the key to unlocking value for its business and customers, and uses autonomous agents to plan and execute tasks from beginning to end.

For example, the company has created the AT&T digital receptionist, a network-based AI agent that can directly engage with callers to determine whether they’re spammers or fraudsters. It can disconnect suspicious calls or take messages if needed, and customers can watch a live transcript of the digital receptionist’s interactions with callers and pick up at any time.

Other use cases include an agent that takes customer service update requests, synchronizes data across systems, and auto-installs information in real time. There’s also a set of agents that network engineers can use to help them resolve network alerts and get customers reconnected after an incident by correlating telemetry to identify where an alert was issued, pulling recent change logs and checking for known issues, and writing new code for a patch.

“There’s not a single person across AT&T who’s not impacted by this,” says Andy Markus, the company’s chief data and AI officer.

Markus’s advice: Generate excitement in the business by showcasing what’s possible. “We have hundreds of business cases that are waiting for us to prioritize,” he says. “That’s the result of the enthusiasm and passion of the business because they’re seeing the value here.”

Agentic AI helps AUM Biotech punch above its weight

Biotechnology startup AUM Biotech has fewer than 10 employees, but AI agents are helping it stay on top of leads and support customers across the globe and around the clock.

AUM Biotech specializes in genetic research tools for gene silencing and regulation, and its customers include some of the world’s biggest pharmaceutical companies. With no venture backing, it depends entirely on sales, and with limited personnel, agentic AI has allowed it to automate many internal processes, like customer support.

A sales development representative agent (SDR) helps the company scale its top of funnel sales efforts, streamline prospect qualification, and generate a 24/7 pipeline. After the first few interactions, the agent can transfer the effort to a human agent to close the deal.

Another agent sits on customer calls to record and summarize them, and can use that data to personalize emails back to customers. Meanwhile, a web agent answers product queries on the company’s website.

“Being a small company with limited resources, you have to figure out a way to optimize things,” says AUM Biotech founder and CEO Veenu Aishwarya.

Aishwarya’s advice: You don’t require specialized skills to start. For all intents and purposes, Aishwarya isAUM Biotech’s IT department. “I’m not a coder, I’m a cancer researcher,” he says. “But for the past several months, I’ve drawn myself into learning through YouTube and Google.”

Smarsh turns to Salesforce AI agent for customer service

AI communications data and intelligence company Smarsh has turned to agentic AI for customer support.

In 2024, the Smarsh board started inquiring about how AI could increase efficiency. After some research, the company identified a portfolio of initial use cases in Q4 2024. It then acquired the Agentforce platform in Q1 2025 and started implementing customer cases in Q2.

“The number-one use case to really get used to it was the creation of automatic knowledge base articles,” says chief customer officer Rohit Khanna.

The company had been developing its knowledge base for several years, but the effort required support engineers around the world tasked with creating thousands of articles.

Also starting in Q2 2025, the company unveiled an agent that could create those articles autonomously. Then in Q3, it replaced the customer-facing chatbot on Smarsh Central with an Agentforce Service Agent called Archie, complete with an animated avatar to give a face to the agent. The company has also been working on agents for billing, and to help customers with user access control.

Khanna’s advice: Use agents for basic support functions and focus human support representatives on more critical tasks. “We didn’t let people go,” Khanna says. “We just halted growth in level one support reps. Now we’re challenging and pushing our team members to sharpen their skills and go to level two or three, what we call business critical support.”