UPDATED 10:26 EDT / OCTOBER 24 2024

Discover how AI implementation and agentic AI are transforming automation, optimizing workflows, and driving higher ROI for businesses. AI

AI Implementation: Optimizing automation for maximum ROI

The landscape of enterprise AI is increasingly focused on using data more effectively, particularly by integrating technologies such as automation and agentic AI.

Companies large and small are looking to streamline processes and enhance efficiency through intelligent automation, which addresses issues such as manual data entry and process bottlenecks.

Discover how AI implementation and agentic AI are transforming automation, optimizing workflows, and driving higher ROI for businesses.

Celonis’ Divya Krishnan talks to theCUBE about agentic AI, process optimization and the importance of real-time data sharing among stakeholders.

“Our strategy is really to build a platform to give the tools to not only our customers, but also our partners to enable them to actually create the solution and go after all these different areas of opportunity,” said Divya Krishnan (pictured), vice president of product marketing at Celonis SE.

Krishnan spoke with theCUBE Research’s Rob Strechay and Savannah Peterson at Celosphere 24, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed agentic AI, process optimization and the importance of real-time data sharing among stakeholders. (* Disclosure below.)

Embracing agentic AI and ecosystem innovations

Agentic AI enables users to build agents within their preferred development platforms. This approach allows developers to leverage existing tools while incorporating the data and context needed for effective automation.

“It enables people to … build agents in really the development platform of their choice with the data and the context that’s coming from,” Krishnan said. “It’s not just about building the agents, it’s about where do you put the agents in your process? How do you orchestrate them to make sure that they don’t sort of get plopped into the automation stack and the investments you’ve already been making?”

As organizations continue to invest heavily in RPA and backend automation, AI implementation becomes critical for maximizing the return on these investments. The introduction of agentic AI aims to enhance the effectiveness of these efforts by seamlessly integrating agents into existing workflows.

“People have been putting a lot of good time, energy, effort and money into RPA, into backend automation and into complex workflows,” Krishnan said. “The question is how do you optimize that and then how do you bring agents to play to really dramatically increase the ROI that you can get from all the investments that you’re putting in?”

Additionally, the importance of real-time data sharing among stakeholders is critical, which underscores the shift from static updates to continuous information exchange, Krishnan added.

“It’s not about just a one-time or an ad-hoc status check or communication,” she said. “It’s about how can you do intelligence sharing, mental data sharing in real time.”

Here’s the complete video interview, part of SiliconANGLE and theCUBE Research’s coverage of Celosphere 24:

(* Disclosure: TheCUBE is a paid media partner for Celosphere 24. Neither Celonis SE, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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