Study: Agentic AI Success Hinges on Reinventing Existing Processes

New research from Pegasystems finds the businesses seeing the most success from agentic AI implementation are focused on reimagining existing processes. This suggests businesses should aim to enhance existing functions based on their needs.

Peter van der Putten, director of the AI Lab at Pegasystems, spoke to Tech.co about the most meaningful measure of agentic success being “adoption at scale.” Similarly, he adds, “Organizations must connect AI initiatives to strategic priorities and core business processes and tie them directly to measurable outcomes and metrics.”

The study urges businesses to examine their existing processes, sourcing the ones that can be automated, and use collaborative and innovative approaches to maximize deployment based on clear governance and business goals.

Use Agentic AI to Reimagine Existing Processes

New research from Pegasystems Inc. and research firm Savanta, finds organizations seeing the most success when delivering agentic AI are doing so by rethinking the existing processes they already have in place.

Overall, 96% of respondents said they had achieved success by rethinking existing processes. 53% said they had done this to a “significant” extent, by reimagining everything their company does.

For this report, Pega surveyed 500+ business and IT decision makers worldwide who had successfully implemented agentic AI projects.

Support a Culture of Collaboration and Innovation

The businesses seeing the most success with agentic AI are fostering a culture of collaboration and invention. 80% of respondents report business and IT operations were willing to introduce new technology, innovation, and ideas to explore new possibilities. Most of this stems from a desire to take existing processes and make them more predictable and consistent.

This doesn’t necessarily mean simply replacing entire workflows with agentic capabilities, however. Peter van der Putten, director of the AI Lab at Pegasystems, explained in an interview with Tech.co that human and AI collaboration remains a critical element. 

“Agentic AI should not be pursued in isolation,” van der Putten says. “It must be combined with other forms of artificial and human intelligence and orchestrated within how work is executed across the organization. This includes both straight-through workflows and human-in-the-loop decision-making.”

Similarly, van der Putten expresses the importance of governance and explainability. “Agent behavior must be auditable, measurable, monitored, an controlled to ensure consistent and predictable outcomes.” This not only creates more consistent outcomes, but protects businesses from common AI mistakes like poor data quality.

Prioritize Corporate-Level Strategy

A staggering 95% of businesses who successfully deployed AI agents had a specific, corporate-level strategy and plan for execution. This strategy should be tied directly to success metrics, which are regularly reviewed and evaluated based on progress.

In a press release, chief technology officer at Pegasystems Don Schuerman said, “We’re fast reaching a tipping point with agentic AI where adoption is high within organizations, but maturity is not.”

Curious about what Schuerman believes “mature” AI adoption looks like, I asked van der Putten, who started by defining what it doesn’t look like. He dismissed “large data science teams experimenting in isolation,” and simply providing employee access to tools like Claude or Gemini.

Instead, it “reflects a shift from experimentation to execution, from activity to outcomes, and from isolated agents to agentic AI embedded in orchestrated systems of work.” To achieve this, van der Putten adds, leaders must align business and IT around shared outcomes, and design for “predictability, governance, reduced complexity, and scalability from the outset.”

How Businesses Should Focus Agentic Investments

In terms of what businesses should focus primarily on when deploying agentic AI agents, van der Putten said: “Too often, core and primary business functions, especially those running on legacy systems, are left untouched. This is understandable, as these environments consume the majority of IT resources and governance attention. However, it is also a critical mistake.

“Agentic AI should be used to reimagine these core systems and processes as part of a modern AI-enabled enterprise architecture. The starting point must always be the processes and outcomes that matter most to the business, rather than isolated use cases at the periphery.”

The message for businesses is to be strategic, but also, think holistically. Gaining a strong understanding of how individual processes connect to wider success, sets you up for an agentic solution that supports all business functions.