Artificial intelligence is accelerating a major shift in how work gets done, with enterprise AI agents emerging as key players in rethinking business automation.

Rather than simply completing tasks, these agents are evolving into autonomous problem-solvers that navigate complex workflows, support decision-making and operate alongside human teams. Industry leaders are signaling a turning point as organizations move from basic automation toward AI-powered orchestration frameworks. The emphasis is now on end-to-end process execution, real-time data adaptation and measurable gains in speed, accuracy and enterprise value, according to Rob Bearden (pictured, left), chief executive officer of Sema4.ai Inc.

“Our approach and model is clearly by providing that horizontal platform that enables the developer and the line of business owner to define an outcome,” Bearden said. “Then our platform leverages the Sema4 AI or Psy AI engine to build those agents, to know how to connect to the data, to know how then to build the reasoning paths and deploy that agent in the best execution environment … then to do that at the highest standard. The way we’ve approached this is through our set of safe services.”

Bearden and Paul Ferguson (right), vice president of global financial services at Emerson Electric Co., spoke with theCUBE’s Scott Hebner at the AI Agent Builder Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how enterprise AI agents are transforming business automation by enabling intelligent, end-to-end process execution. (* Disclosure below.)

How enterprise AI agents transform business value

The evolution of enterprise AI agents has pushed beyond previous generations of automation, such as robotic process automation or task-based assistants. This new model is rooted in orchestration, decision intelligence and cross-functional collaboration. Emerson’s early adoption of these technologies, in partnership with Sema4, offers a compelling look at what’s possible, Ferguson explained.

“Now having agents available in the toolkit, we’re really able to look at end-to-end automation and transformation,” he said. “That’s where I think the real value is both from a service cost perspective as well as knowledge work and moving up the value chain.”

By focusing on high-volume, knowledge-intensive tasks, Ferguson’s team targeted areas where traditional software struggled. One such process was customer payment remittance, which involved matching unstructured payment data with open invoices. Previously, a legacy system could only automate 20–30% of this task, requiring human intervention for the remainder, according to Ferguson.

“As we ramped up the agent, we ended up getting around 70, 80% auto hit rate, which is phenomenal,” he said. “What that did was allow the people [to] not spend their time trying to do that remedial matching and free up their time to add more value add.”

This transformation not only improved accuracy and turnaround times, but also freed employees to focus on strategic initiatives. The success of this use case reinforced Emerson’s belief in scaling agentic capabilities across other workflows. Another key insight from their journey was the importance of starting with a clear process narrative, something the Sema4 platform enabled through its horizontal, runbook-driven architecture, according to Ferguson.

“Being able to describe a process narrative of the steps that the agent needs to take from an end-to-end process, combining it with actions is really powerful,” he said. “To be able to be horizontal and cut across multiple applications in that one run book is really powerful and been really helpful.”

These insights are becoming increasingly relevant across industries. As enterprises consider their own AI agent strategies, the emphasis is shifting toward platforms that support secure deployment, seamless orchestration and explainable decision paths. The goal is no longer just automation, it’s intelligent, autonomous execution with auditability and trust built in.

“As I think about our path forward and what we as a company are doing and what we’re very focused on, we’re very focused on making sure that our platform really empowers the enterprise to build, run and manage safe enterprise AI agents that very simply execute on knowledge work and do that reliably, predictably,” Bearden said.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the AI Agent Builder Summit:

(* Disclosure: Sema4.ai Inc. sponsored this segment of theCUBE. Neither Sema4.ai nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE