Agentic AI adoption is transforming workflows across industries, helping companies accelerate development and decision-making. But as agentic AI adoption grows, trust is becoming essential to realizing lasting business value.

One sector feeling this shift firsthand is financial services. There, generative AI aids in summarizing complex documents, while agentic AI enhances data retrieval and improves quality across diverse sources, according to Jayeeta Putatunda (pictured, middle), lead data scientist and director for AI center of excellence at Fitch Group Inc.

“We all know retrieval was tough. Connecting all the knowledge bases, web searches, different variations of data points that we might have,” Putatunda said. “We are just … making sure that there’s no garbage in, garbage out problem that we are still seeing with generative AI.”

Leaders in software and tech marketplaces are also seeing agentic AI reshape the landscape. For them, now is the time for brutally honest assessments of what’s really happening on the ground as companies invest in and build out AI agents and agentic AI initiatives.

Putatunda; Paul Sciaudone (left), vice president of print cloud platform engineering and quality at HP Development Company LP; and Tim Sanders (right), vice president for research insights at G2.com Inc., spoke with theCUBE Research’s Scott Hebner for the AI Agent Builder Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how agentic AI adoption is streamlining workflows while raising new challenges around trust and governance. (* Disclosure below.)

Agentic AI adoption changing industries

Agents are also taking software development to the next level. They’re changing how applications and services are built, reducing the need for traditional coding and development, according to Sciaudone.

“You’ve now got an ecosystem of agents that essentially become the LEGO blocks to build new capabilities and new services. You think about prototyping, getting software out there quickly, you don’t even need to be a software developer to do it with agents,” he said. “You can get product people building things quickly, rapid prototyping, even our customers can work with us to prototype together.”

Agents solve the delivery problem that generative AI doesn’t, according to Sanders. Unlike generative AI, which offers suggestions, agents take action continuously.

“You really couldn’t do that with generative AI. It was more Waze; agents is more Waymo,” Sanders said.

Moving forward, a key development will be greater standardization and interoperability between agents and platforms. Google LLC’s recent announcement of its Agent2Agent Protocol is a big step forward in making it easier for companies to integrate agentic capabilities at scale, according to Sciaudone.

“I think what’s been happening in the past 12 to 18 months, is everyone’s been rushing to get out there first, and build out these new agent capabilities,” he said. “Now, with that proliferation, [there] needs to be some sort of standardization to build that trust and security, and make sure it is reliable and standardized, so enterprises can actually rely on building agentic capabilities that isn’t going to change three months from now.”

In industries such as financial services, which requires strict guardrails and governance requirements, there’s still much to be considered. Agentic AI must be layered with human-in-the-loop review and grounded in trusted processes to ensure responsible implementation, according to Putatunda.

“I think it’s a great exciting world, but we have to kind of balance it just to make sure we sell to our clients, as well as leadership, a trustworthy solution,” she said.

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

(* Disclosure: TheCUBE is a paid media partner for the AI Agent Builder Summit. The sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE